C · ★ 8,236 · 🍴 627 · 📈 1,058 stars today
High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
中文介绍 这款高性能代码智能MCP服务器，能将代码库快速索引成持久化知识图谱，支持158种编程语言。它通过毫秒级查询和大幅减少token消耗（约99%），显著提升AI编码助手或代码分析工具理解代码库的效率与成本效益，最终以单一静态二进制文件的形式分发。
Python · ★ 24,084 · 🍴 2,273 · 📈 1,510 stars today
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
中文介绍 由Google Research开发的时间序列基础模型（TimesFM）。它通过在大量时间序列数据上进行预训练，为预测任务提供了一个强大的通用基础模型，旨在帮助数据科学家和研究人员简化并提升时间序列预测的性能。
Swift · ★ 1,912 · 🍴 188 · 📈 756 stars today
macOS video editor built for AI
中文介绍 一款专为macOS设计、并深度整合了AI能力的视频编辑器。它旨在利用人工智能技术简化复杂的视频编辑流程，主要面向内容创作者和视频制作者，提供智能化的剪辑与后期处理体验。
TypeScript · ★ 57,243 · 🍴 9,138 · 📈 156 stars today
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
中文介绍 一个实时全球智能监控仪表板。它集成了AI驱动的新闻聚合、地缘政治监测和基础设施追踪功能，为分析师、研究人员或决策者提供一个统一的态势感知界面，以快速掌握全球动态。
HTML · ★ 27,628 · 🍴 5,738 · 📈 107 stars today
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
中文介绍 这是一个关于生成式AI的一站式资源库。它系统地整理了最新的研究动态、面试准备资料、代码实践Notebook等丰富内容，旨在帮助开发者、研究者和求职者高效学习与跟进生成式AI领域。
TypeScript · ★ 1,048 · 🍴 117 · 📈 147 stars today
A framework for building agent-native applications.
中文介绍 一个用于构建原生代理应用（Agent-Native Applications）的开发框架。它为开发者提供了一套工具和结构，用于创建以AI代理为核心交互和执行逻辑的应用程序。
Python · ★ 38,727 · 🍴 2,643 · 📈 4,005 stars today
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
中文介绍 一个在工具输出、日志、文件或RAG数据块送入大语言模型（LLM）前，对其进行智能压缩的工具库。它能在保持答案质量的同时，减少60-95%的token消耗，显著降低LLM推理成本，可作为库、代理或MCP服务器使用。
Python · ★ 6,289 · 🍴 1,082 · 📈 156 stars today
World's first open-source, agentic video production system. 12 pipelines, 52 tools, 500+ agent skills. Turn your AI coding assistant into a full video production studio.
中文介绍 世界上首个开源的代理式（Agentic）视频生产系统。它包含12条流水线、52个工具和超过500项代理技能，旨在将AI编程助手转变为一个功能全面的视频制作工作室，赋能自动化视频内容创作。
★ 4,584 · 🍴 461 · 📈 480 stars today
GLM-5: From Vibe Coding to Agentic Engineering
中文介绍 GLM-5模型及相关方法，主题聚焦于从“Vibe Coding”（直觉式编码）向“代理式工程”（Agentic Engineering）的演进。它可能代表了一种新的AI编程或软件工程范式，强调通过自主代理来理解和构建软件系统。
TypeScript · ★ 5,840 · 🍴 323 · 📈 309 stars today
The sandbox agent framework.
中文介绍 一个沙盒代理（Sandbox Agent）框架。它为开发者提供了一个安全、隔离的环境来构建和运行AI代理，使得代理可以在受控条件下与外部环境交互，适用于开发和测试需要权限控制的代理应用。
Rust · ★ 10,248 · 🍴 466 · 📈 302 stars today
IP addresses break, dial keys instead. Modular networking stack in Rust.
中文介绍 一个用Rust编写的模块化网络协议栈，其核心创新是“用密钥替代IP地址进行拨号”。它旨在解决IP地址可能变更或不可靠的问题，通过基于密钥的寻址提供更稳定、灵活的网络连接方案，适用于P2P应用或需要可靠身份识别的场景。
Shell · ★ 233,356 · 🍴 20,724 · 📈 1,110 stars today
An agentic skills framework & software development methodology that works.
中文介绍 这是一个结合了代理技能（Agentic Skills）框架与软件开发方法论的项目。它旨在通过结构化的方法和工具，增强AI在软件开发流程中的能力，目标是提供一种可实践的、能提升开发效率的AI辅助工程方法。
Clojure · ★ 50,587 · 🍴 3,268 · 📈 85 stars today
Penpot: The open-source design tool for design and code collaboration
中文介绍 Penpot是一款开源的设计与代码协作工具。它允许设计师和开发者在同一个平台上进行UI/UX设计、原型制作，并直接生成可用的代码，旨在打破设计与开发之间的壁垒，促进团队高效协作。
TypeScript · ★ 38,979 · 🍴 2,300 · 📈 292 stars today
The open-source, cross-platform API client for GraphQL, REST, WebSockets, SSE and gRPC. With Cloud, Local and Git storage.
中文介绍 一款开源的、跨平台的API客户端。它支持GraphQL、REST、WebSockets、SSE和gRPC等多种协议，并提供云存储、本地存储和Git版本控制等灵活的数据管理方式，是API开发者和测试工程师进行API调试、测试和文档管理的常用工具。
Python · ★ 7,672 · 🍴 1,220 · 📈 196 stars today
Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.
中文介绍 这是Lightricks公司LTX-2音视频生成模型的官方Python工具包。它提供了模型的推理功能和用于微调的LoRA训练器，供开发者将该先进的音视频生成模型集成到自己的应用中，或根据需求定制模型。
@horizon_trade_x · 4.4K 粉丝 · 1.3M 阅 · 507 赞 · 59 转
Your backtest looked flawless. You went live. Two weeks later, the strategy was bleeding. Every quant has lived this. The answer is a loop: generate a strategy, test it, score it, feed the result
中文介绍 分享量化交易中的「循环工程」框架。核心是通过「生成策略、测试、评分、反馈」的自动化循环来寻找并优化Alpha，以解决策略上线后效果衰减的常见问题。
@sairahul1 · 117.4K 粉丝 · 511.9K 阅 · 500 赞 · 84 转
Your AI agent works great for the first 10 steps. Then somewhere around step 15, it starts getting sloppy. Wrong tool calls. Forgetting your original instructions. Low-quality outputs. Most people
中文介绍 探讨AI Agent的上下文工程。指出了Agent在多步操作后（如第15步）表现下降、工具调用错误的普遍问题，并提供了完整的上下文管理策略来解决记忆和指令遵循的挑战。
@djfarrelly · 3.8K 粉丝 · 344.7K 阅 · 501 赞 · 61 转
Everyone's asking "WTF is a loop?" Here's the question nobody's asking: what runs the loop? The AI discourse has converged on loops as a core primitive of agentic systems. Matt Van Horn (@mvanhorn)
中文介绍 讨论「循环」作为AI Agent系统核心原语背后的运行机制。博主认为，当前AI讨论聚焦于循环本身，但更关键的问题是「什么在驱动这个循环」。
@0xMovez · 26.7K 粉丝 · 208.0K 阅 · 504 赞 · 59 转
A free open-source model is running 300 parallel agents across 4,000 coordinated steps from a single prompt, and it scores higher on real research tasks than models you pay 5x more for. Most people
中文介绍 介绍一个由免费开源模型Kimi K2.6驱动的300代理集群实验。该集群从单一提示出发，执行4000步协调任务，在真实研究任务上的得分超过了价格高5倍的模型。
@EXM7777 · 118.9K 粉丝 · 107.7K 阅 · 509 赞 · 44 转
for a few days, we had something that felt like AGI... Fable 5 showed up, effectively unlimited inside the plans, and the ceiling on what you could build lifted overnight but then Anthropic killed it,
中文介绍 怀念Fable 5（Anthropic模型）曾带来的类AGI体验。博主指出，Fable 5曾提供几乎无限的能力上限，极大提升了创作潜力，但随后被调整限制。
@OracleMindAI · 21.0K 粉丝 · 105.0K 阅 · 2.8K 赞 · 582 转
In 2026, autonomous AI agents have become one of the most effective strategies on prediction markets. Over 30% of all activity on Polymarket now comes from algorithmic and AI-powered wallets. We
中文介绍 介绍OracleMind AI代理在预测市场Polymarket上进行自主交易。到2026年，AI代理已成为预测市场最有效的策略之一，目前超过30%的市场活动来自算法和AI驱动的钱包。
@Designarena · 13.9K 粉丝 · 80.4K 阅 · 518 赞 · 39 转
GLM 5.2 ranks 1st overall on Design Arena’s single-turn, HTML Web Design (Non-Agentic) evaluation, 5 places higher than its predecessor GLM-5.1. To do so, it beat Claude Fable 5, Opus 4.6, and Opus
中文介绍 在Design Arena的单轮、非代理式HTML网页设计评测中，GLM-5.2排名超越Claude Fable 5、Opus 4.6等模型，获得总分第一。其排名比前身GLM-5.1高出5位。
@nifinet · 10.4K 粉丝 · 62.8K 阅 · 519 赞 · 38 转
A GTM team looks like a sending operation. Most of its real work is judgment: which company is worth a message this week, what to say that proves you noticed, which no-show to chase, what actually
中文介绍 分享如何利用Claude Code构建一个可独立运营的GTM（市场进入）团队。该工作流主要运用AI的判断力，完成从潜客筛选、个性化信息编写到跟进任务等核心市场拓展工作。
@heynavtoor · 143.5K 粉丝 · 47.7K 阅 · 538 赞 · 70 转
Most people use Claude like a search box. Ask, answer, close tab. They are leaving the best feature locked. Save this :) Stanford built a research system called STORM. In peer reviewed testing it
中文介绍 介绍如何将斯坦福大学的STORM研究系统方法应用于Claude。该系统能让AI在几分钟内进行博士级别的深度研究，远超简单的问答使用方式。
@contralabs_ai · 2.9K 粉丝 · 46.6K 阅 · 501 赞 · 37 转
Everyone keeps talking about taste. But you can't improve what you can't measure. So we measured it. Design Crit is a dataset of ten professional designers ranking four frontier image models across
中文介绍 发布Design Crit数据集，用于让AI像专业设计师一样评判设计。该数据集包含10位专业设计师对4个前沿图像模型的排名数据，旨在解决「品味」难以量化的问题。
@Just_sharon7 · 44.1K 粉丝 · 32.5K 阅 · 502 赞 · 18 转
If you're still switching between 10 tools to make UGC ads, analyze performance, and iterate... your workflow is outdated. Arcads just dropped MCP support, and pairing it with Claude (especially Fable
中文介绍 介绍广告创作工具Arcads集成MCP后与Claude（特别是Fable 5）的协同工作流。该集成旨在简化UGC广告的创建、性能分析与迭代流程，减少在多工具间切换。
@soniajoseph_ · 16.9K 粉丝 · 13.9K 阅 · 861 赞 · 21 转
There has been a lot of confusion around world models. Depending on who you ask, a world model is a generative model, a 3D reconstruction model, or a latent-space prediction model. I would like to
中文介绍 阐述对「世界模型」概念的澄清观点。博主认为，世界模型与模型可解释性本质上是同一枚硬币的两面，并对当前关于世界模型（生成模型、3D重建等）的不同理解进行了梳理。
@ActionModelAI · 57.8K 粉丝 · 5.7K 阅 · 501 赞 · 366 转
Most people think AI is still in its early stages. They're right. And that's exactly why these facts are so crazy. 1. AI could add $15.7 trillion to the global economy by 2030 According to PwC, AI
中文介绍 汇总10条AI领域令人惊讶的事实。包括普华永道预测AI到2030年将为全球经济贡献15.7万亿美元、AI在2024年美国大选中的潜在影响等统计数据和趋势。
@OptimaiNetwork · 99.4K 粉丝 · 5.3K 阅 · 511 赞 · 360 转
The old internet was built for humans browsing pages, clicking ads, and buying subscriptions. The autonomous internet needs something else: live context, verified signals, permissioned execution, and
中文介绍 提出「自主时代神经系统」的概念。指出为人类设计的旧互联网（浏览、广告、订阅）已不适用于自主互联网，后者需要实时上下文、验证信号、许可执行等基础设施。
@Trade_OracleAI · 21.1K 粉丝 · 60 阅 · 2.8K 赞 · 584 转
In 2026, autonomous AI agents have become one of the most effective strategies on prediction markets. Over 30% of all activity on Polymarket now comes from algorithmic and AI-powered wallets. We
中文介绍 介绍AI代理在预测市场Polymarket的交易表现。强调到2026年，AI代理已成为主流策略，超过30%的市场活动由算法和AI钱包驱动，并分析了其高效的原因。
Miami-based AI startup Subquadratic came out of stealth mode last month with a huge claim. It announced that it had solved a mathematical bottleneck that had been holding back large language models for almost a decade. The details were thin, and many people were unconvinced. But Subquadratic has sta
中文介绍 迈阿密AI初创公司Subquadratic声称突破阻碍大型语言模型近十年的数学瓶颈，但具体细节未公开，业界存疑。
With GLM-5.2 passing everyone's vibe check, the open models story finally becomes a real frontier story.
中文介绍 GLM-5.2模型通过评估，表现优于GPT，开放模型成为前沿焦点。Z.ai预测Open Fable将于12月前发布。
中文介绍 GPT-5.6模型于周二发布，Claude推出代码工件，Perplexity新增Brain记忆功能。
中文介绍 MosaicLeaks项目探讨研究代理的保密能力，涉及AI代理安全。
We talk about how this legendary investor went from humble beginnings in Singapore to leading rounds in Anthropic, Mistral, Black Forest Labs, and Periodic Labs... and the AMP secret master plan!
中文介绍 投资者Anjney Midha从新加坡起步，领导Anthropic、Mistral等AI公司投资，揭示AMP秘密计划。
OpenAI introduces new spend controls and usage analytics for ChatGPT Enterprise, helping organizations manage costs and scale AI with confidence.
中文介绍 OpenAI为ChatGPT企业版推出新支出控制和使用分析功能，助力企业成本管理和AI扩展。
Learn how GPT-5.5 Instant improves ChatGPT’s health and wellness responses with stronger reasoning, better context, clearer communication, and physician-informed evaluations.
中文介绍 GPT-5.5 Instant增强ChatGPT的健康响应能力，包括推理、上下文、沟通和医疗评估。
Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.
中文介绍 研究人员利用OpenAI推理模型辅助诊断儿童罕见遗传病，在未解案例中发现18个新诊断。
The only bootstrapped frontier lab announces its second product and second
中文介绍 Midjourney Medical发布第二款产品，实现类似称重的器官扫描功能。
中文介绍 探讨超越LoRA的微调技术，评估能否优于现有流行方法。
中文介绍 评估开放模型在工具使用上的代理能力，进行基准测试。
中文介绍 ChatGPT市场份额下滑，Vercel发布新功能，Replit集成Claude模型。
Radical AI's Joseph Krause on why the moat in materials is the lab, not the model
中文介绍 Radical AI的Joseph Krause认为，材料科学中实验室比模型更具竞争力。
中文介绍 MolmoMotion项目实现语言引导的3D运动预测。
中文介绍 通过Strands Agents和LeRobot，将Hugging Face Hub模型部署到机器人硬件。
周末 arXiv 通常无新公告。当前展示最近一次可用公告批次。
第一作者: Shanghao Shi · 方向: 隐私保护
联邦学习隐私后门参数高效微调语言模型神经印记
Abstract:Federated learning (FL) enables multiple parties to collaboratively fine-tune language models for domain-specific tasks without sharing raw data. Since full model fine-tuning is often prohibitively expensive for FL clients, parameter-efficient fine-tuning (PEFT) has become the de facto approach in practice, freezing the base model and training only a small set of adapters. In this paper, we show that a malicious parameter server can stealthily corrupt a PEFT adapter into a privacy backdoor that implicitly memorizes the client's training samples as isolated per-sample parameter updates stored in separate neurons, without degrading model utility. Concretely, our attack, NeuroImprint, assigns a dedicated memorization neuron to each training sample and constrains that each neuron is updated at most once along the local fine-tuning trajectory. This design mitigates both...
论文介绍 本文研究了联邦学习中参数高效微调的隐私风险。攻击者（恶意服务器）可将适配器模块转化为隐私后门，隐式记忆客户端的训练样本。所提「NeuroImprint」方法通过为每个样本分配专属记忆神经元，并约束其在本地微调中仅更新一次，从而在不损害模型效用的情况下窃取数据隐私。这揭示了联邦微调中一种新型的安全威胁。
第一作者: Jun He · 方向: 系统安全
自主智能体系统安全主权执行代理证书绑定运行时强制执行
Autonomous agents are increasingly connected to cloud, deployment, and data-control workflows, but production mutation authority should not reside inside non-deterministic reasoning processes. Existing access-control mechanisms authorize identities, while assurance layers certify proposed actions; neither alone provides a mandatory enforcement point for certified authority at the moment of mutation. This paper introduces the Sovereign Execution Broker (SEB), a runtime enforcement boundary for certificate-bound agentic infrastructure. SEB consumes certificates issued by the Sovereign Assurance Boundary (SAB), verifies that the requested mutation matches the certified execution contract, checks validity windows, policy epochs, revocation epochs, and live-state drift, mints scoped execution identity, invokes infrastructure APIs, and records signed decision and outcome records. By...
论文介绍 为解决自主智能体在关键工作流中可能拥有不适当变更权限的问题，本文提出了「主权执行代理」(SEB)。SEB 作为一个运行时强制执行边界，通过消费由主权保证边界颁发的证书，在变更发生时验证请求是否符合经认证的执行契约，并检查策略有效性、撤销状态等，从而确保对智能体行为的强制授权。该架构旨在为智能体基础设施提供可信的权限执行点。
第一作者: Alaia Solko-Breslin · 方向: 安全研究
AI代理形式化验证概率策略Datalog分布鲁棒优化
Securing AI agents that operate in complex digital environments has become a critical need, and runtime monitoring approaches that formulate and enforce policies expressed in a formal language like Datalog offer a promising solution. However, existing approaches are restricted to deterministic policies. In many practical applications of AI agents, there is a need to enforce security policies in the face of ambiguity, leading to probabilistic predicates or state transitions (for example, a declassifier or Personally Identifiable Information (PII) detector that has some failure probability on each invocation). Furthermore, in many such applications, one cannot easily make the independence assumptions necessary to invoke prior work on probabilistic inference in Datalog. We address this by introducing a sound and efficient framework for such verification based on distributionally robust...
论文介绍 现有对AI代理的运行时监控通常局限于确定性策略，难以处理实际中普遍存在的模糊性与概率性（如具有失败率的PII检测器）。本文引入了一种基于分布鲁棒优化的框架，用于对这类包含概率谓词或状态转换的策略进行可靠且高效的验证。该框架无需依赖传统概率推理所必需的独立性假设，从而能更广泛地应用于复杂代理环境的安全策略执行。
第一作者: Arastoo Zibaeirad · 方向: 软件安全
大型语言模型漏洞检测微调限制数据污染CWE-Trace框架
Abstract:Whether LLMs scoring well on vulnerability benchmarks genuinely reason about security or merely pattern-match on contaminated data remains unresolved. We present CWE-Trace, a framework for LLM vulnerability detection built from 834 manually curated Linux kernel samples spanning 74 CWEs. The framework enforces a strict temporal split (pre-2025 historical set / post-cutoff leakage-free set), preserves context-aware vulnerable--patched pairs, and introduces two diagnostic metrics: the Directional Failure Index (DFI) and Hierarchical Distance and Direction (HDD). We evaluate eight vanilla LLMs and 15 LoRA fine-tuned variants across non-targeted detection, targeted detection, and CWE classification. Our analysis yields two key results. First, data contamination provides no measurable advantage. Function-level analysis shows that 84% of nominally contaminated samples carry no usable...
论文介绍 研究大型语言模型在系统软件漏洞检测中是否真正理解安全问题。本文提出CWE-Trace框架，基于834个手动策展的Linux内核样本和74个CWEs，实施严格时间分割以防止数据泄漏，并引入方向性失败指数和层次距离与方向两个诊断指标。评估了多种LLM和LoRA微调变体，发现数据污染无显著优势，为LLM在安全应用中的校准提供诊断工具。
第一作者: Tamara Tagliavia · 方向: 隐私保护
大语言模型漏洞检测软件安全数据污染校准
Abstract:In the information age, one of the leading problems is how to ensure individual's privacy. Depending on the context in which privacy is considered, various data privacy models have emerged. However, the domain of formal verification of these models is still not sufficiently explored even when it comes to the most basic models. An attempt to verify privacy requirements is the Compliance Assertion Language (COMPASS). In COMPASS, one can specify an anonymity condition that a table needs to satisfy, and an action that will modify the table if the condition is not satisfied. It is designed to operate on preprocessed tables in a form one record - one group of people. In this paper, we modify the COMPASS language in order to operate on microdata tables in their usual form of one record - one person. The modified language is called A-COMPASS. Along with checking of previously applied...
论文介绍 本文质疑了大语言模型在漏洞基准测试中的高分是否源于真正的安全推理。研究者构建了严格按时间划分、防止数据泄漏的CWE-Trace评估框架，并引入了定向失败指数等诊断指标。实验发现，数据污染并未带来可衡量的优势，且模型性能提升主要源于校准而非对漏洞的理解。这揭示了当前LLM在系统软件漏洞检测应用中的局限性。
第一作者: Reza Soosahabi · 方向: 系统安全
智能体AI提示注入防御误导模型引导攻击对抗分析
Abstract:Agentic AI systems increasingly rely on language-model components to interpret instructions, process external data, invoke tools, and coordinate with other agents. These capabilities make prompt-injection and jailbreak attacks more consequential, especially as attackers adopt model-guided automation to scale probing, prompt refinement, and response evaluation. This work analyzes the resulting attack-defense setting through a probabilistic model of a target system, its defense mechanism, and the attacker's automated judge. Our analysis shows that conventional detect-and-block defenses can allow attacker success rate (ASR) to approach one as the query budget grows, since predictable refusals provide useful feedback to automated search. We then examine detect-and-misdirect, where detected malicious interactions receive controlled, non-operational responses designed to induce...
论文介绍 随着智能体AI系统更易受到模型引导的自动化攻击，本文分析了「检测与误导」的防御策略。与仅阻止恶意查询的传统「检测与阻止」防御相比，误导策略通过向检测到的恶意交互提供受控的、无操作的虚假响应，旨在诱导攻击者的自动化评判模型做出错误判断，从而消耗其查询预算并降低攻击成功率。研究通过概率模型展示了其在对抗环境下的潜在优势。
第一作者: Ans Ibrahim · 方向: 密码学协议
图像加密卷积神经网络动态S盒密码学安全性评估
The paper proposes a dynamic approach to image encryption, combining the use of Convolutional Neural Networks (CNNs) and classical cryptography to improve the security and flexibility of image encryption. The main concept is to create adaptive Substitution boxes (S-boxes) based on characteristics that are learned by a trained CNN. The CNN-based S-boxes can be relied on for more non-linearity, uniqueness, and input image dependence than the conventional fixed S-boxes because they are susceptible to the linear and differential attacks. This dynamic behaviour enhances the confusion property and makes it more resistant to statistical and structural attacks. The encryption algorithm consists of CNN-based feature extraction and the creation of a personalised S-box to replace the pixels. Entropy, histogram analysis, correlation, NPCR, and UACI enable security assessment of generated S-boxes...
论文介绍 为提升图像加密的安全性，本文提出了一种结合卷积神经网络与经典密码学的方法。其核心是利用CNN从图像特征中学习，动态生成依赖于输入图像的替代盒（S-box），而非使用传统固定的S-box。这种动态生成的S盒具有更强的非线性和唯一性，理论上能更好地抵抗线性与差分攻击，并增强了加密的混淆特性，提升了对统计与结构攻击的抵抗力。
第一作者: Bercan Turkmen · 方向: 软件安全
恶意软件分类大语言模型多视角反编译二进制分析特征融合
Abstract:Malware analysts often inspect compiled binaries through decompiled pseudo-C, when source code is unavailable. Recent work suggests that large language models (LLMs) can assist this process by classifying decompiled code as benign or malicious, but existing pipelines typically rely on a single decompiler view. We argue that this assumption is fragile: decompilers are lossy heuristic tools, and different decompilers can expose different artefacts of the same binary. We curate a benchmark of benign utilities and malicious programs spanning a range of threat behaviors. Each sample is compiled and decompiled with both Ghidra and RetDec, yielding matched pseudo-C views. Across a range of LLMs from major model families, we find that providing both decompiler views improves malicious-class F1, mainly by increasing recall on malicious samples. Agreement analyses further show that...
论文介绍 针对现有基于大语言模型的恶意软件分类仅依赖单一反编译器视图的问题，本文提出利用多视角反编译。研究者使用Ghidra和RetDec对同一二进制文件生成不同的伪C代码视图。实验表明，向LLM提供多种反编译视角能通过提高恶意样本的召回率来改善分类性能。这证明了不同反编译器能暴露同一二进制的不同特征，多视图融合可提升分析的鲁棒性。
第一作者: Hanwool Lee · 方向: 密码学协议
LLM代理安全多轮红队测试越狱基准对抗鲁棒性安全关键系统
Large language model (LLM) agents are increasingly proposed as supervisory components for safety-critical systems, yet their robustness under sustained, adaptive adversarial pressure remains poorly characterized. We present NRT-Bench, a benchmark for multi-turn red-teaming of LLM agents acting as operators of a safety-critical system, instantiated in a simulated nuclear power plant control room. A five-role operator team, each backed by a configurable LLM, runs a plant governed by six critical safety functions (CSFs), while adversaries inject messages over four channels in bounded multi-turn sessions with per-turn feedback. Harm is an objective signal rather than LLM-judged text: a run terminates the moment any CSF is lost, attributed to the causing message. Evaluating four frontier operator models under a fixed-attack paired-replay protocol, we find that adaptive multi-turn attacks...
论文介绍 本研究关注大语言模型代理在安全关键系统中的鲁棒性问题。研究提出了NRT-Bench基准，用于在模拟核电站控制室场景中对LLM代理进行多轮红队测试。通过模拟五人操作团队和注入攻击消息，以客观安全信号（如安全功能失效）来评估前沿模型。该研究旨在系统性评估和改善LLM代理在对抗压力下的可靠性。
第一作者: Kaihsun Yang · 方向: AI 安全
量化后门攻击任务算术模型安全AI安全
Abstract:Model quantization is widely adopted to reduce memory usage and inference cost when deploying deep neural networks on resource-constrained devices. However, recent studies have revealed a new security threat known as Quantization-Conditioned Backdoors (QCBs), where a model behaves normally in full precision but activates malicious behavior only after quantization. Existing defenses typically modify quantization procedures or correct activation statistics, often introducing additional computational overhead or relying on specific quantization settings. Here, we present QVec, a parameter-space perspective for defending against QCBs. We observe that the weight difference between a full-precision model and its quantized counterpart encodes a structured behavioral shift, which can be interpreted as a malicious task vector rather than random quantization noise. Based on this...
论文介绍 本文研究量化过程中引入的一种后门威胁，即量化条件后门，该后门仅在模型量化后被激活。作者提出QVec防御方法，从参数空间视角出发，将全精度模型与其量化版本之间的权重差异视为一个恶意任务向量，通过任务算术来移除该后门向量，从而在不影响模型正常精度的前提下防御此类攻击。
第一作者: Yu Shen · 方向: 密码学协议
混合网络移动自组网匿名性去中心化协议
Mix networks are a highly effective way to achieve anonymity, defending against a wide range of traffic-analysis attacks. However, mix networks are usually designed for infrastructure networks and cannot be directly applied in the context of mobile ad hoc networks (MANETs). The few existing solutions for MANETs require advance knowledge of the topology or a trusted central party. In this paper, we present TrustMix, a mix protocol for MANETs that operates without any central trusted party. In TrustMix, parties join groups and then messages are forwarded via multiple groups to provide anonymity. With TrustMix, users only need to find a party nearby that they consider trusted. They then forward the message to this party's group, and the party shuffles messages before forwarding to other groups, meaning that the original message and the forwarded message cannot be linked. Furthermore, even...
论文介绍 传统混合网络难以直接应用于移动自组网。本文提出TrustMix协议，它无需中心可信方或预知网络拓扑。用户仅需找到附近的可信节点，将消息转发至其所在组，该节点在组内对消息进行洗牌后再转发至其他组，从而切断消息关联，为MANETs提供去中心化的匿名通信能力。
第一作者: Adolfo P. Jimenez · 方向: 软件安全
GNSS欺骗V2X通信软件定义无线电车联网安全威胁分析
Abstract:Global Navigation Satellite Systems (GNSS) constitute a core technology for delivering crucial positioning, navigation, and timing (PNT) services in the Vehicle-to-Everything (V2X) domain, where they are indispensable for generating Cooperative Awareness Messages (CAM) that uphold network reliability and vehicular safety. Yet, GNSS signals are acutely exposed to spoofing, an advanced attack in which an adversary transmits crafted signals that replicate legitimate satellite characteristics, misleading the receiver into computing a false position. This work presents a methodology for conducting physical spoofing with inexpensive Software Defined Radio (SDR), describing a coordinate generation pipeline that employs Haversine-based distance calculations, temporal discretization to emulate constant velocity, and linear interpolation to produce high-fidelity GPS baseband signals...
论文介绍 全球导航卫星系统信号面临欺骗威胁，这对依赖其提供定位、导航和授时服务的车联网至关重要。本文描述了一种使用低成本软件定义无线电进行物理GNSS欺骗的方法论，包括生成高保真GPS基带信号的坐标计算管线，旨在评估此类攻击对V2X通信安全的具体威胁。
第一作者: Aymen Bouferroum · 方向: AI 安全
工业物联网信任管理机器学习网络质量信任收敛
Abstract:In Industrial Internet of Things (IIoT) environments, trust management plays a vital role in securing systems, especially when dealing with resource-constrained devices. Traditional trust models often overlook the impact of fluctuating network quality, leading to slower trust convergence and inaccurate assessments. In this paper, we propose a dynamic trust management solution, known as the Trust Convergence Acceleration (TCA) approach, which integrates Machine Learning (ML) to accelerate trust convergence under poor network conditions. Our model predicts the number of time units needed for trust convergence based on key network metrics and dynamically adapts transition probabilities in the trust model to enhance convergence speed. Using a simulation framework that incorporates realistic Wi-Fi channel conditions based on the IEEE 802.11 standard, we demonstrate the...
论文介绍 传统信任管理模型在工业物联网中因忽略网络质量波动而导致信任收敛缓慢、评估不准确。本文提出TCA方法，集成机器学习以预测不同网络指标下的信任收敛所需时间，并动态调整信任模型的转移概率，从而在恶劣网络条件下加速信任收敛过程，提升评估准确性。
第一作者: Junchao Li · 方向: 系统安全
具身AI移动应用密码误用安全测量基准测试
Abstract:Embodied AI (EAI) mobile applications are evolving from auxiliary user interfaces into active control-path components, directly linking mobile-side cryptographic security to cyber-physical trust. Despite this shift, existing security research predominantly focuses on embodied AI devices and cloud infrastructures, leaving the mobile control layer largely unexplored as a critical attack surface. To bridge this gap, we present the first large-scale measurement study of cryptographic misuse within the EAI mobile ecosystem. We construct EAIAppZoo, a benchmark of 507 real-world applications across six EAI domains, and employ an automated semantic-aware analysis pipeline to measure the prevalence and characteristics of five major cryptographic failure modes. Our measurement yields 12,975 misuse findings (with an evaluated precision of 80.74\%), revealing that these cryptographic...
论文介绍 本文首次对具身AI移动应用中的密码误用进行大规模测量研究。研究者构建了涵盖六个领域、507个真实应用的EAIAppZoo基准，并采用自动化语义感知分析流程，测量了五种主要密码故障模式的普遍性与特征，揭示了该生态系统中广泛存在的密码安全漏洞。
第一作者: Johannes Wilson · 方向: 密码学协议
形式化验证协议实现Tamarin语言优先符号执行
Formal verification is a challenging but important task for ensuring the security of cryptographic protocols. While modern protocol verification tools significantly reduce verification effort, modelling remains challenging to practitioners without a background in formal verification. In addition, transferring verification results to a concrete protocol implementation requires expert knowledge. In this paper, we present a novel language-first method for verification of trace properties using a domain-specific language for protocol implementations. We target the Tamarin prover for verification, and we prove that verified universal trace properties translate back to the implementation. We additionally integrate symbolic execution in order to analyse the memory safety of protocol implementations. We use our tool to implement and generate accurate models for a signed Diffie-Hellman...
论文介绍 为了解决密码协议形式化建模难和验证结果难以转移到具体实现的问题，本文提出一种语言优先的方法。该方法针对协议实现定义了一种领域特定语言，并能自动生成用于Tamarin证明器的精确模型，从而实现对追踪性质的验证。工具还集成了符号执行来分析实现的内存安全性。
第一作者: Chaeyun Kim · 方向: AI 安全
金融LLM红队测试安全评估基准生成合规风险
Existing safety benchmarks target general adversarial scenarios but miss finance-specific risks. Financial LLMs face regulatory compliance violations, fraud facilitation, and systemic trust erosion that require targeted evaluation. We introduce FinRED, an expert-guided red-teaming framework for financial LLM safety evaluation developed with financial experts. FinRED uses a novel two-level taxonomy mapping global standards (e.g., FATF and EU DORA) to threats ranging from regulatory evasion to complex fraud, integrated with a scalable pipeline that converts real financial documents into context-rich red-teaming Behavioral Prompts (seeds) through an expert-defined schema. Rigorous expert validation confirms seed plausibility and realism for meaningful LLM safety evaluation. We also provide an expert-validated, finance-specific rubric that goes beyond disclaimer checks, aligns more closely...
论文介绍 通用安全基准无法覆盖金融大语言模型面临的特定风险，如违反监管、助长欺诈等。本文提出由金融专家指导的FinRED红队测试框架，它基于两层分类法将全球标准映射到具体威胁，并通过可扩展的流程将真实金融文档转化为富含上下文的测试提示，用于更精准地评估金融LLM的安全性。
第一作者: George Alexakis · 方向: 密码学协议
全同态加密数论变换脉动阵列多精度计算AI专用集成电路
Abstract:Fully Homomorphic Encryption (FHE) ensures robust data privacy but suffers from prohibitive computational overhead. Accelerating FHE on AI hardware like Tensor Processing Units (TPUs) is promising, yet fundamentally limited by a precision mismatch: TPUs are optimized for 8-bit arithmetic, whereas FHE and its critical parts such as the Number Theoretic Transform (NTT), demand high precision. Current approaches bridge this gap using matrix decomposition to execute NTT computations on low-precision matrix engines. However, reconstructing the full-precision results requires shift-and-add accumulation that does not match the dataflow of matrix multiplication. This forces offloading full-precision reconstruction from matrix engines to vector processors that disrupts the matrix multiplication dataflow, creating significant performance bottleneck. To resolve this limitation, we...
论文介绍 研究全同态加密在AI硬件如TPU上加速时面临的精度不匹配瓶颈。提出低成本多精度脉动阵列架构，直接支持高精度数论变换计算，避免全精度重建卸载到向量处理器导致的数据流中断，从而优化性能并降低成本，有望提升FHE在隐私保护计算中的效率。
第一作者: Prashanti Nilayam · 方向: AI 安全
异构大语言模型辩论对抗性同伴有害修订安全性
Abstract:Heterogeneous LLM debate is motivated by the promise that diverse peers correct one another, but the same exchange that carries correction also carries adversarial influence. We measure which dominates by tracking how a heterogeneous peer changes the honest agents' revision behavior: how often they change their answer, and whether the change is corrective or harmful. We compare matched panels (homogeneous baseline, honest-mixed, and adversarial-mixed) and contaminated panels in which a malicious same-family peer is already present, spanning four model families and three reasoning benchmarks. An honest heterogeneous peer sharply lowers harmful revision, and an adversarial one reverses it. For Llama-3.1-70B defenders on MATH-hard, the honest-slot harmful-revision rate falls from 89% in the homogeneous panel to 35% with an honest peer, and an adversarial peer returns it to 90%...
论文介绍 探讨异构大语言模型辩论中同伴的影响，特别是对抗性同伴的风险。通过实验比较同质、诚实混合和对抗混合面板，测量有害修订率的变化。发现诚实同伴能显著降低有害修订，而对抗性同伴则增加风险，为LLM辩论的安全应用提供实证见解。
第一作者: Tasneem Suha · 方向: 密码学协议
侧信道攻击运行时漏洞硬件软件协同缓解策略时序泄露
Abstract:Program runtime or timing attacks exploit variations in a program's execution times to extract sensitive information from the program (e.g. encryption keys, sensitive variable data, intellectual property). State-of-the-art solutions to runtime side-channel attacks attempt to balance the execution time of the sensitive code for different control flow paths to eliminate the timing leakage. However, during the mitigation process, most techniques do not consider the underlying hardware or device on which the target program is supposed to run on. This can lead to over-fixing (unnecessary extra operations), under-fixing (not solving the imbalance properly), and even failures. We propose DISARM, a joint hardware-software methodology (unlike any existing solution) for mitigating runtime side-channel vulnerabilities that utilizes timing values from real embedded devices to generate...
论文介绍 针对程序运行时侧信道攻击，提出DISARM方法。该方法结合硬件和软件，利用目标电子设备的实际时序值生成缓解策略，平衡不同控制流路径的执行时间以消除时序泄露。旨在解决现有技术中过度修复或不足修复的问题，提升嵌入式系统安全性。
第一作者: Haotian Xu · 方向: AI 安全
推测推理大语言模型安全动态反射采样风险估计安全框架
Abstract:Speculative inference accelerates large language model (LLM) decoding but provides no inherent safety guarantees. Existing safety defenses are largely incompatible with speculative inference: they either introduce additional computation or disrupt the draft-verify mechanism, negating acceleration benefits. This reveals a fundamental incompatibility between current safety methods and speculative decoding. We propose SafeSpec, a safety-aware speculative inference framework that integrates risk estimation directly into the verification process. SafeSpec attaches a lightweight latent safety head to the target model to jointly evaluate semantic validity and safety in a single forward pass. When unsafe generations are detected, SafeSpec applies rollback and safety-guided reflective multi-sampling to recover safe continuations rather than terminating generation. We model jailbreak...
论文介绍 提出SafeSpec框架，将安全性集成到大语言模型的推测推理中。通过附加轻量级安全头，在验证过程中评估语义有效性和安全性，检测到不安全生成时进行回滚和反射采样以恢复安全输出。旨在保持加速解码的同时，提供安全保证，解决现有安全方法与推测推理的兼容性问题。
第一作者: Prashant Kumar Pathak · 方向: 安全研究
向量检索枢纽问题检索增强生成安全准入控制各向异性
Vector hubness, where a few points become nearest neighbors of many queries, creates a poisoning risk in retrieval-augmented generation (RAG): one injected document can influence unrelated requests. Existing defenses use periodic reverse-kNN scans, leaving an exposure window and repeated corpus-wide work. We study admission-time control, scoring each candidate against sentinel queries and quarantining hub-like documents before insertion. Across two 100,000-document corpora, five encoders, and disjoint attacker and defender query sets, a global gate achieves recall 1.0 at the decisive embedding-space point (>=0.92 across the effective range) and 0.91 +/- 0.07 on HotFlip attacks, with 1% false positives on general documents. A per-topic gate provides no reliable benefit, consistent with anisotropy coupling local and global visibility. Thresholds are maintained incrementally, with...
论文介绍 研究向量检索系统中的枢纽问题对检索增强生成安全的威胁，提出准入时间控制机制。在文档插入前使用哨兵查询评分，隔离类枢纽文档以防止中毒攻击。实验显示该方法能有效防御HotFlip攻击，同时保持低误报率，增强RAG系统的安全性。
第一作者: Gulshan Saleem · 方向: AI 安全
提示注入检索增强生成聊天机器人安全框架分层防御间接注入
Abstract:Prompt injection is ranked as the most critical vulnerability in large language model (LLM) deployments by the OWASP Top 10 for LLM Applications, yet existing defenses operate at isolated pipeline stages and remain incomplete. Input filters cannot inspect retrieved documents, while output monitors cannot prevent malicious payloads from reaching the model. Consequently, retrieval-augmented generation (RAG) chatbots remain vulnerable to indirect injection, where a poisoned knowledge-base document compromises every user whose query retrieves it. We present a three-layer framework that intercepts both direct and indirect prompt injection throughout the inference pipeline. Layer 1 screens user input using a rule-based pattern library and a fine-tuned semantic anomaly classifier. Layer 2 enforces a provenance-based instruction hierarchy during context assembly, preventing retrieved...
论文介绍 针对RAG聊天机器人的提示注入漏洞，提出三层安全框架。第一层筛选用户输入，第二层在上下文组装时执行指令层次，第三层监控输出。该框架拦截直接和间接注入攻击，旨在全面保护LLM部署，解决现有防御在管道阶段孤立操作的问题。
第一作者: Shangzhi Xu · 方向: 系统安全
正则表达式拒绝服务攻击漏洞检测攻击字符串生成资源耗尽防御机制
Abstract:ReDoS attacks constitute a critical class of resource-exhaustion vulnerabilities. In such attacks, adversaries exploit the pathological worst-case execution behavior of regular expression (regex) engines to induce highly asymmetric computational workloads, ultimately exhausting system resources and degrading service availability. To protect systems against ReDoS attacks, numerous detection techniques have been proposed that simulate the attack process by generating attack strings to proactively exploit ReDoS vulnerabilities at the early development stage and facilitate remediation. Existing techniques broadly fall into two classes: static analyses that search for pathological regex structures, and dynamic exploration methods that synthesize candidate attack strings. However, the generated attack strings are often impractical for real-world exploitation because they usually...
论文介绍 提出PUFFERDOS方法，用于高效生成实际可利用的ReDoS攻击字符串。该方法结合静态分析和动态探索，克服现有技术生成的攻击字符串不实用的问题，助力早期漏洞检测和修复，保护系统免受正则表达式引擎病态行为导致的资源耗尽攻击。
第一作者: Baigang Chen · 方向: 系统安全
桥接分发隐私保护两方计算群组自适应审查规避
Abstract:We present G-Lox (group-adaptive Lox), a bridge-distribution system that preserves Lox-style distributor blindness while enabling hidden, stateful group-level adaptation. G-Lox places adaptive assignment logic behind a two-server privacy wall, so no single server learns group identifiers or group-to-bridge assignments. Private state access and state-dependent updates use two-server DPF/FSS protocols and secure two-party computation, supporting blockage reporting, transport-aware reassignment, and privacy-preserving group splitting. We evaluate G-Lox through system measurements and policy simulation. In our C++/EMP implementation over real TCP sockets, private state access has low client-visible overhead: across state sizes up to 2^16, communication remains in the low-KiB range per iteration. At M=1024, the client sends 1,968 bytes, receives 1,280 bytes, and completes an...
论文介绍 介绍G-Lox系统，一种隐私保护的桥接分发方案。它使用两方计算将自适应分配逻辑置于两个服务器后，保护群组标识符和分配隐私，支持阻塞报告、传输感知重分配和隐私保护群组分割。旨在增强审查规避系统的隐私性和自适应能力，避免单点信息泄露。
第一作者: Nils Loose · 方向: 软件安全
大语言模型后门攻击平台依赖性浮点算术安全漏洞
Abstract:Large language models (LLMs) are increasingly deployed in sensitive settings such as software engineering, where their outputs directly shape downstream artifacts. Recent work has shown that an identical model can produce measurably different outputs depending on the deployment platform, a consequence of non-associative floating-point arithmetic and divergent kernel implementations. We study the security implications of this platform-dependent variability and uncover a novel attack surface on LLM deployments. We introduce FloatDoor, the first input-independent, platform-triggered backdoor attack against generative LLMs. The compromised model exhibits adversary-chosen behavior when served on a target platform and is otherwise benign. FloatDoor is realized through two lightweight LoRA adapters, one that amplifies inter-platform numerical divergence and one that binds the...
论文介绍 该研究探讨大型语言模型在不同部署平台上的输出差异所引发的安全问题，提出FloatDoor，一种输入无关、平台触发的后门攻击方法。该方法利用两个轻量级LoRA适配器，一个放大平台间数值分歧，一个绑定恶意行为，使模型在特定平台上执行对手选择的行为，而在其他平台上保持良性。
第一作者: R.D.N. Shakya · 方向: 密码学协议
后量子密码学安全编码LLM辅助开发编码漂移游戏化修复
Abstract:The transition to Post Quantum Cryptography (PQC) introduces considerable implementation complexity, requiring strict adherence to constant-time execution, side channel resistance, and precise parametrisation. Simultaneously, large language models (LLMs) are heavily embedded in software development workflows, including cryptographic engineering. While LLMs improve productivity, evidence shows that they frequently generate insecure or suboptimal code, particularly in security critical domains. This paper introduces Secure Coding Drift in PQC, a novel socio technical vulnerability model capturing the gradual degradation of secure coding practices due to sustained reliance on LLM-generated code. Unlike prior work that focuses on static vulnerabilities, we conceptualise security risk as a longitudinal behavioural phenomenon rising from human AI interaction. To mitigate this, we...
论文介绍 论文分析在后量子密码学开发中，持续依赖LLM生成代码可能导致的安全编码漂移问题。不同于静态漏洞，这被概念化为纵向行为现象。为缓解此问题，提出一种游戏化方法，旨在通过交互式干预改善编码实践。
第一作者: Christos Galanopoulos · 方向: 密码学协议
基因组Beacon全同态加密智能合约隐私保护以太坊虚拟机
The Global Alliance for Genomics and Health (GA4GH) Beacon protocol lets researchers ask whether a genomic variant has been observed in a participating cohort and receive aggregate variant-level counts. As Beacon networks grow, two privacy risks remain: host institutions can see plaintext queries, and repeated rare-variant queries can support membership-inference attacks. We present bioETH-Beacon, a smart-contract prototype that runs the Beacon "aggregate count" query over encrypted data on a fully homomorphic Ethereum Virtual Machine (fhEVM). Hospitals upload encrypted marker-count entries, authorized researchers submit encrypted marker queries, and the contract returns an encrypted answer that is released, via an off-chain key-management service, only to the requester named in the contract's on-chain ACL. The design is organized as a 3x4 tier-by-query-family grid spanning genotype...
论文介绍 针对基因组Beacon协议中的隐私风险，如主机机构查看明文查询和成员推理攻击，提出bioETH-Beacon智能合约系统。该系统在全同态以太坊虚拟机上运行加密数据的查询，通过加密计数和过滤器，结合离链密钥管理，确保只有授权研究者获取结果。
第一作者: Mikael Alemu Gorsky · 方向: 软件安全
人工智能网络安全非洲排斥前沿模型技术垄断
Abstract:In 2025 and 2026, two events settled questions that had until then been speculative. In the first, a large language model executed the great majority of a state-aligned cyber-espionage campaign on its own, with human operators intervening at only a few decision points. In the second, the most capable cyber-relevant model was placed under a controlled-access program limited to a vetted set of United States technology firms, allied governments, and European standards bodies; that perimeter included no African government, operator, or university. Together the two events establish the argument of this paper: frontier language models have become a decisive instrument of cyber operations, and that instrument is built, owned, and rationed within a small circle from which Africa is absent. The paper documents Africa's exclusion on every count. The continent does not build frontier...
论文介绍 基于2025-2026年事件，论文指出前沿AI模型已成为网络操作的关键工具，但该技术被少数美国公司和盟友垄断，非洲被排除在外。文档化了非洲在技术构建、拥有和获取方面的全面缺失，强调这对全球安全的影响。
第一作者: Zunchen Huang · 方向: AI 安全
LLM-求解器循环叙述差距形式化验证提示注入安全关键
Formal tools such as SAT and SMT solvers are increasingly embedded in language model reasoning pipelines when a safety or security critical question can be formulated in logic. Unlike chain of thought whose steps are sampled from the model distribution without formal guarantee, a solver produces a sound and independently verifiable answer. However, the soundness guarantee can be lost in the interaction between the solver and the model. The hybrid pipeline has three components: formalizing the question, deciding it, and narrating the result. Prior work has studied the formalization and decision, but not narration, which is the step that turns a formal tool's output into the user answer. To fill the narration gap, we first model the LLM-solver loop as a verified decision procedure. We further evaluate five open-sourced models under prompt injection, and we find certificate gating makes...
论文介绍 研究LLM与形式化求解器（如SAT/SMT）交互中的叙述步骤，即将求解器输出转化为用户答案的过程。通过建模验证决策程序，评估开源模型在提示注入下的表现，发现证书门控能提升安全性，填补叙述环节的可靠性空白。
第一作者: Luis Adrián Lizama-Pérez · 方向: 安全研究
量子密钥分发Bell态被动用户无量子检测器密钥建立
Abstract:We propose and analyze a Bell-state extension of the Loop-Back quantum key distribution architecture for secret-key establishment between two passive users that do not require quantum transmitters or quantum detectors. In the proposed setting, a single active station, Alice, provides the entangled-state infrastructure, retains one qubit of an initially prepared Bell pair, and sends the traveling subsystem through two passive users, denoted by $B_1$ and $B_2$. Each passive user applies a local Pauli operation to the same traveling subsystem, so that the operation observed by Alice is only the effective composition $U_{\mathrm{eff}}=U_2U_1$. After the subsystem returns, Alice performs a Bell-state measurement and, using her private knowledge of the initial Bell state, deterministically identifies the effective Pauli operation. However, the individual factors $U_1$ and $U_2$...
论文介绍 提出一种扩展的Bell态回环量子密钥分发架构，允许两个被动用户无需量子发射器或检测器即可建立密钥。主动站点提供纠缠态基础设施，通过Pauli操作和Bell态测量，识别有效的复合操作，但个体操作因子不可区分，增强隐私。
第一作者: Sizhe Yang · 方向: 机器人操作 · 来源: cs.RO
世界动作模型持久内存机器人操作记忆效率非马尔可夫
Abstract:Robust robotic manipulation in the real world requires not only an understanding of the current observation, but also memory and dynamics modeling. World action models (WAMs) possess these capabilities by jointly modeling visual foresight and actions conditioned on both current and historical observations, making them a promising paradigm for robotic manipulation. However, existing WAMs face a fundamental trade-off: methods with efficient inference typically condition only on a bounded window of recent observations and therefore struggle in non-Markovian environments, whereas methods that preserve long histories incur time and space costs that grow substantially with sequence length. To address this challenge, we introduce MemoryWAM, a world action model with efficient persistent memory. MemoryWAM uses a hybrid memory design that combines recent frames, event-boundary anchor...
论文介绍 针对现有世界动作模型在长期记忆和推理效率之间的权衡，提出MemoryWAM。该模型采用混合内存设计，结合近期帧和事件边界锚点，实现高效持久记忆，使机器人能在非马尔可夫环境中进行鲁棒操作。
第一作者: Sha Yi · 方向: 机器人操作 · 来源: cs.RO
机器人手生成人类演示数据驱动逆运动学组合优化
Abstract:Robot learning has advanced rapidly in learning control, but learning the physical body of a robot remains much more difficult because jointly searching over design and control creates a very large combinatorial problem. Here, we present a data-driven framework for generating robot hands from human demonstrations. Instead of learning a complex controller together with each candidate design, we generate robot hand designs using the same simple control policy used after fabrication: matching fingertip positions through inverse kinematics. Using more than 4 million frames of human fingertip motion from everyday manipulation, our algorithm optimizes tree-structured robot hands to reproduce desired target motions. The framework produced both a 6-degree-of-freedom (DoF) general-purpose hand and lower-DoF task-specific hands with spatial four-bar mimic joints. To accelerate the...
论文介绍 提出一个数据驱动框架，从人类演示中生成机器人手设计。使用超过400万帧人类指尖运动数据，通过逆运动学匹配指尖位置，优化树状结构机器人手，产生通用或特定任务的手设计，加速机器人学习进程。
第一作者: Oxana Shamilyan · 方向: 导航与运动 · 来源: cs.RO
连续体机器人运动规划层次分析法韧性
Abstract:This paper presents an experimental study of motion planning for resilient continuum robots. In this study we mainly focused on multi-criteria decision-making, its application for path-planning algorithms, impact on the generated path and execution time. To do this, we used two well-known algorithms for path planning, namely Genetic algorithm and A star algorithm, and modified them by adding the Analytical Hierarchy Process algorithm to evaluate the quality of the paths generated. In our experiment the Analytical Hierarchy Process considers four different criteria, i.e. distance, motors damage, mechanical damage of the robot's arm and accuracy, each considered to contribute to the resilience of a continuum robot. The use of different criteria is necessary to increase the time to maintenance operations of the continuum robot. We conducted the experiments using two different...
论文介绍 本文针对连续体机器人的韧性提升问题，提出基于多准则决策的运动规划方法。研究修改遗传算法和A*算法，集成层次分析法评估生成路径质量，综合考虑距离、电机损伤、机械臂损伤和精度四个标准。该方法旨在优化路径选择，减少维护需求，从而增强机器人在复杂环境中的长期可靠性和耐用性。
第一作者: Fatma Youssef Mohammed · 方向: 导航与运动 · 来源: cs.RO
人类注意力预测扫描路径液态神经网络MobileNetV3自主导航
Abstract:Human visual attention relies on structured scanpaths to efficiently process scenes, yet instilling this behavior into robot autonomy is in its infancy and hindered by the high,computational costs of existing predictive models. To address this, we introduce GazeLNN, a computationally lightweight,scanpath prediction model that leverages Liquid Neural Networks as its recurrent engine and employs MobileNetV3 for feature extraction. Operating auto-regressively, the architecture predicts sequential fixation heatmaps conditioned on the current visual stimulus and fixation history. Despite requiring only 0.61 GFLOPs, GazeLNN achieves state-of-the-art performance on the MIT Low Resolution dataset achieving 0.47 ScanMatch score. It outperforms existing recurrent baselines across diverse evaluation metrics, while reducing computational costs by 99.40% and accelerating inference by up to...
论文介绍 为提升自主导航中的主动感知能力，本文提出GazeLNN模型用于快速预测人类视觉注意力扫描路径。该模型采用液态神经网络作为循环引擎，并使用MobileNetV3进行特征提取，能自回归地生成序列化的固定点热图。GazeLNN计算成本低，在MIT低分辨率数据集上达到先进性能，为机器人导航提供高效注意力引导。
第一作者: Zhenghao "Mark'' Peng · 方向: VLA 通用模型 · 来源: cs.RO
城市导航视觉语言模型轨迹规划延迟弹性人行道导航
Abstract:Learning-based planners for sidewalk navigation can generate diverse candidate trajectories in real time, yet their scoring functions often fail to select the best trajectory in challenging situations, outputting trajectories that make the mobile robot drive onto grass, toward pedestrians, or in the wrong direction, even when better candidates exist in the same set. We call this the trajectory scoring gap: in real-world sidewalk navigation, the gap between an anchor-based planner's top choice and the best possible candidate is substantial, likely due to limited high-level scene understanding capability of the planner. Rather than replacing the planner with an end-to-end Vision-Language-Action model, we propose a VLM-Planner interface that uses a VLM to select a candidate index from the planner's proposal set and then fuse it with the planner's initial output. However, VLMs...
论文介绍 本文解决人行道导航中基于学习的规划器轨迹评分差距问题。核心方法是提出VLM-Planner接口，利用视觉语言模型从规划器生成的候选轨迹集中选择最佳索引，并与规划器输出融合。该方法旨在克服现有规划器在复杂场景下的局限性，提升移动机器人在城市环境中的导航安全性和可靠性。
第一作者: Hengfei Zhao · 方向: 策略学习 · 来源: cs.RO
视觉触觉传感器有限元法仿真框架Cauchy应力Isaac Sim
Abstract:Vision-based tactile sensors require high-fidelity simulation for reinforcement learning, yet existing approaches struggle to provide accurate mechanical stress fields within GPU-accelerated robotics platforms. We present TaCauchy, an extensible Finite Element Method (FEM) framework that integrates rigorous physics-based force computation into Isaac Sim. Built on the Unified Incremental Potential Contact (UIPC) solver, TaCauchy directly computes Cauchy stress tensors from hyperelastic constitutive laws and projects them onto contact surfaces to obtain traction forces and pressure distributions, providing mechanical ground truth from first principles rather than empirical estimation. Our framework features automatic mesh generation with geometry-aware adaptive refinement and a modular sensor interface enabling rapid integration of diverse sensors (GelSight Mini, DIGIT, 9DTact)...
论文介绍 针对视觉触觉传感器在强化学习中的高保真仿真需求，本文提出TaCauchy框架。该框架基于有限元法，集成到Isaac Sim中，能直接计算Cauchy应力张量并投影到接触表面，提供精确的机械真实数据。框架支持自动网格生成和模块化传感器接口，适用于多种触觉传感器仿真，促进机器人触觉感知研究。
第一作者: Ziyuan Tang · 方向: 机器人操作 · 来源: cs.RO
连续体机器人3D打印同构遥操作开源平台可重复性
Abstract:Continuum robots offer strong potential for manipulation tasks due to their high degrees of freedom, compliant structures, and operational safety. However, their adoption in both research and practical applications has been hindered by reproducibility issues arising from complex fabrication and assembly processes, challenging kinematic modeling, and a lack of intuitive control interfaces. To address these challenges, we present a novel open-source continuum robot design. The platform features a simplified fabrication pipeline enabled by multi-material 3D printing, allowing the arm to be fabricated as a monolithic compliant structure with minimal assembly. Control is achieved through an isomorphic teleoperation interface that establishes a direct actuator-level mapping, eliminating the need for explicit kinematic modeling and providing a singularity-free mapping. Building on...
论文介绍 本文针对连续体机器人可重复性挑战，提出开源设计平台CoLI。平台利用多材料3D打印技术实现整体式柔性结构制造，并通过同构遥操作接口提供直观控制，无需显式运动学建模。该设计简化了制造和控制流程，旨在促进连续体机器人在研究和实际应用中的普及。
第一作者: Paolo Golinelli · 方向: 导航与运动 · 来源: cs.RO
移动机器人团队相对定位去中心化协同范围测量无基础设施
Abstract:The ability to localise teams of robots is essential for applications ranging from robotic fleets in unstructured environments to cooperative control and navigation tasks. In such contexts, fixed infrastructure is often unavailable, deployments must be fast and flexible, and system requirements must be minimal. We present a decentralised cooperative localisation algorithm that addresses all these challenges at once. The method is anchor-less, fully decentralised, and, unlike most existing approaches, does not require controlling the robots motion to ensure team observability. It relies only on local odometry, sparse inter-agent ranging measurements, and short-range communication, all of which are widely available in practice. The algorithm adopts a multi-hypothesis Bayesian framework that maintains the entire set of feasible solutions, ensuring robustness under transient...
论文介绍 本文提出一种无基础设施、控制独立的移动机器人团队相对定位算法。该方法基于去中心化协同，仅依赖本地里程计和稀疏范围测量，采用多假设贝叶斯框架保持所有可行解。算法无需控制机器人运动即可确保团队可观测性，适用于快速灵活部署的场景，如非结构化环境中的机器人车队。
第一作者: Yandong Wang · 方向: VLA 通用模型 · 来源: cs.RO
双臂操作视觉语言动作模型协调感知结构化动作建模机器人操纵
Abstract:Vision-language-action (VLA) models show strong capabilities in single and dual-arm robotic manipulation. Prior works show coordinated bimanual behaviors can emerge from end-to-end learning, leveraging large vision-language backbones with continuous action prediction. However, as bimanual tasks become tightly coupled and execution constraints become critical, implicit coordination alone is insufficient to ensure reliable, interpretable, and stable behavior. In this work, we propose Co-VLA, a coordination-aware bimanual manipulation framework introducing explicit structural priors into VLA models. We instantiate our method on a state-of-the-art vision-language backbone by replacing its monolithic action head with a Structured Action Expert (SAE) designed for bimanual coordination. Specifically, we introduce explicit structure at the action generation level with a modular...
论文介绍 本文针对双臂操作任务中隐式协调不足的问题，提出Co-VLA框架。该框架在视觉语言动作模型中引入显式结构先验，通过结构化动作专家实现双臂协调。方法旨在提高双臂操作的可靠性、可解释性和稳定性，适用于紧密耦合和约束关键的任务。
第一作者: Paul Koch · 方向: 具身智能 · 来源: cs.RO
认知机器人合成数据生成领域适应AI视觉模型数据驱动
Abstract:AI vision models are a driving factor for the potential use case scenarios of cognitive robotics within in the industry and household applications. A large array of methods from semantic environment analysis towards 6D and grasping pose estimation have been proposed based on the latest AI achievements. However, such advancements require further strong and efficient methods w.r.t. training data and AI-architectures, which are capable in synergy to tackle current challenges, precision limits, and scalability beyond domain gaps. In this paper, we discuss these current limits and trends in the related state-of-the-art which are challenging those. Further we discuss our current work in progress on bridging the domain gap between simulations and real world applications by linking those in the training data generation.
论文介绍 本文讨论AI视觉模型在认知机器人应用中的当前限制，特别是训练数据和架构的挑战。核心方法是通过高效链接模拟和真实场景数据生成来弥合领域差距，以提升模型精度和可扩展性。该工作旨在推动认知机器人在工业和家庭应用中的发展，解决数据稀缺和领域差异问题。
第一作者: Gia-Binh Nguyen · 方向: VLA 通用模型 · 来源: cs.RO
VLA模型层冗余结构压缩训练无关
Abstract:Vision-Language-Action (VLA) models pre-trained on massive video-robot datasets have revolutionized robotic manipulation, yet their multi-billion parameter architectures impose prohibitive computational burdens during downstream fine-tuning and real-time inference. In this work, we reveal a highly non-trivial architectural characteristic of these continuous control foundation policies (e.g., pi_0, GR00T-N1.5): despite being trained on diverse physical trajectories, they exhibit severe layer-wise representational redundancy. To exploit this, we introduce a structural compression pipeline that is entirely training-free, bypassing the need of existing methods to load full-scale models to learn optimized token reductions or dynamic layer selectors. Instead, using only a single forward pass via Centered Kernel Alignment to identify redundant layer features, we remove twin layers to...
论文介绍 针对大规模视觉-语言-动作模型微调计算成本高昂的问题，本文揭示了其架构中存在严重的层间表征冗余。为此，研究提出了一种无需训练的结构压缩流程，仅通过一次前向传播和中心核对齐识别冗余层，即可移除冗余层对，从而大幅降低模型微调和实时推理的计算开销。
第一作者: Francesco Argenziano · 方向: 导航与运动 · 来源: cs.RO
流匹配物体动态时空理解3D场景
Abstract:Joint spatial and temporal understanding of 3D scenes is a crucial requirement for robots deployed in everyday household environments. Such agents must not only comprehend and navigate spatial layouts, but also reason about how these spaces evolve over time. In particular, humans interact with objects daily, causing them to change position throughout the environment and making it difficult for robots to reliably associate current observations with previously seen objects. However, these interactions are not random: human habits and routines induce spatio-temporally consistent patterns in object locations, which robotic agents can potentially learn and then exploit for downstream tasks such as navigation. To this end, we introduce FlowMaps, a latent flow matching model for estimating multimodal distributions over the future locations of dynamic objects in a continuous 3D space...
论文介绍 机器人需理解家庭场景中物体随时间的位置变化。本文提出FlowMaps，一种基于隐流匹配的模型，用于估计动态物体在连续3D空间中未来位置的多模态分布。该模型能学习由人类习惯引起的物体位置时空一致性模式，可用于支持导航等下游任务。
第一作者: Boya Zhang · 方向: 机器人操作 · 来源: cs.RO
软带驱动灵巧操作手内自由度低成本
Abstract:Parallel-jaw grippers are the default manipulator choice in robotics because they are simple, robust, and inexpensive. Their limited in-hand mobility, however, often forces large arm motions and restricts dexterous manipulation in confined workspaces. We present a parallel-gripper upgrade: a double-soft-belt-based finger module that preserves standard opening/closing while adding three in-hand degrees of freedom (DoF): translation, pitch, and roll. The mechanism is deliberately kept simple and engineered for inexpensive manufacturing and straightforward integration, preserving the reliability and precise control of traditional parallel grippers while greatly broadening the range of manipulation capabilities. To demonstrate the utility of the added DoFs, we integrate the gripper in two control pipelines. First, we adapt a model predictive controller for in-hand manipulation of...
论文介绍 传统平行夹爪手内灵活性有限。本文提出Belt-Finger，一种双软带驱动的手指模块，可在保留平行夹爪开合功能的同时，为其增加平移、俯仰和滚转三个手内自由度。该机制设计简单、制造成本低，易于集成，显著扩展了夹持器的操作能力范围。
第一作者: James Fant-Male · 方向: 具身智能 · 来源: cs.RO
装配状态跟踪动作识别人机协作方法比较
Abstract:Human Action Recognition (HAR) is frequently investigated in Human-Robot Collaboration (HRC) research to understand what actions have been performed and hence the state of a collaborative task. Accurately tracking an assembly state from HAR is however not fully investigated, and in realistic scenarios is not a trivial task. This research systematically investigates and compares methods for tracking assembly state using action recognition inputs. Investigations using two diverse datasets and five state tracking approaches, including logic-based, Hidden Markov Model (HMM), and neural network (NN) methods, show that optimal approaches are not uniform across different tasks and that different methods fail under different circumstances. Testing is performed using both simulated inputs with varying noise levels and realistic inputs from a HAR model. Results show NN and HMM methods...
论文介绍 在人机协作中，从人动作识别结果跟踪装配状态面临挑战。本文系统性地研究并比较了逻辑规则、隐马尔可夫模型和神经网络等五种状态跟踪方法。结果表明，最优方法因任务而异，且不同方法在不同情境下会失败；神经网络和HMM方法在噪声输入下通常表现更优。
第一作者: Jianing Guo · 方向: 机器人操作 · 来源: cs.RO
流匹配频率感知动作生成时序一致性
Abstract:Flow matching has emerged as a standard paradigm for robotic manipulation owing to its strong expressive power for modelling complex, multimodal action distributions, alongside similar approaches like diffusion policy. However, existing methods rely on discretized action chunks, making them brittle to demonstrations collected at heterogeneous control frequencies and prone to temporally inconsistent actions that degrade control stability. In this paper, we propose Frequency-Aware Flow Matching (FAFM), which outputs continuous, temporally consistent actions. To handle heterogeneous frequency input, we transform discrete action sequences into the frequency domain with the discrete cosine transform (DCT), perform flow matching over the resulting coefficients, and reconstruct continuous actions via cosine basis expansion. To generate temporally consistent actions, we regularize the...
论文介绍 现有基于流匹配的机器人操作方法依赖离散动作块，对控制频率不一致的演示数据脆弱，且易产生时序不一致的动作。本文提出频率感知流匹配，通过离散余弦变换将动作序列转至频域进行匹配，再重建连续动作，从而能够处理异构频率输入并生成时序一致的连续动作。
第一作者: Hyeonna Choi · 方向: 具身智能 · 来源: cs.RO
协议翻译双智能体机器人实验室交叉验证
Abstract:Biological experiment protocols are written in natural language, whereas automation systems rely on predefined control commands, creating a semantic gap that limits autonomous execution. Microplate-based automatic experiments are particularly challenging due to the need to simultaneously control well mapping, sample-reagent combinations, replicate placement, and parallel dispensing. This study proposes an agent-based protocol translation framework that converts natural-language microplate-based protocols into executable control commands for a robotic laboratory platform. A Parser Agent formalizes the natural-language protocol into a structured representation, and a rule-based mapping engine deterministically incorporates the operational constraints of the robotic laboratory platform to generate device-level control commands. A heterogeneous LLM Validation Agent verifies...
论文介绍 自然语言描述的生物实验协议与机器人控制命令之间存在语义鸿沟。本文提出一个双智能体框架，将基于微孔板的自然语言协议转换为可执行控制命令。解析智能体将协议形式化，规则映射引擎生成控制指令，并由一个异构的大语言模型验证智能体进行交叉验证，确保转换的准确性。
第一作者: Jonghoon Lee · 方向: VLA 通用模型 · 来源: cs.RO
数据增强物体替换多视角物理合理
Abstract:Vision-language-action (VLA) policies have shown strong potential for general-purpose manipulation, yet they often fail on novel, out-of-distribution objects whose appearance or geometry deviates from the training distribution. The standard remedy is to collect multi-view teleoperation data for every failure case, but this scales poorly in both cost and time. We introduce Pose6DAug, a failure-driven data augmentation framework that turns a policy's own successful episodes into targeted demonstrations for its failure modes, without any new data collection. Our key insight is that each successful episode already encodes a physically valid action trajectory together with calibrated multi-view observations. By swapping only the manipulated object while preserving this trajectory, we obtain new and physically grounded demonstrations. However, naive 2D video editing breaks...
论文介绍 视觉-语言-动作策略在面对训练分布外的物体时易失败。本文提出Pose6DAug，一种失败驱动的数据增强框架。它无需新数据采集，通过将策略自身成功轨迹中的操作物体进行物理合理的替换，生成针对其失败模式的新演示，从而提升策略对新物体的泛化能力。
第一作者: Nozomu Masuya · 方向: 模仿学习 · 来源: cs.RO
模仿学习频率外推迭代学习控制可变速度
Abstract:Conventional neural network (NN)-based imitation learning methods for variable-speed motion either restricted their scope to interpolated speeds, or generated unpredictable motions when extrapolating beyond trained velocity ranges. Variable-frequency imitation learning (VFIL) enabled extrapolations of speeds by linking the NN model's sampling frequency to the motion frequency, whereas its open-loop configuration caused frequency errors, especially in the extrapolated high-frequency settings. This study proposes variable-frequency imitation learning with iterative learning control (VFILC) based on a combination of VFIL and iterative learning control (ILC) with both feedforward and feedback parts, the former taking advantage of VFIL and the latter adjusting the frequency errors. The experimental results showed that the proposed method successfully and accurately extrapolated...
论文介绍 传统模仿学习方法在可变速度运动外推时效果不佳。本文提出VFILC方法，将可变频率模仿学习与具有前馈和反馈部分的迭代学习控制相结合。前馈部分利用VFIL生成运动，反馈部分通过ILC修正频率误差，实验表明该方法能准确地将运动频率外推至训练范围之外。
第一作者: Zheyu Zhuang · 方向: 模仿学习 · 来源: cs.RO
镜像反射数据增强模仿学习对称性视觉运动学习
Abstract:Image-based behaviour cloning leverages demonstrations captured from ubiquitous RGB cameras. However, it remains constrained by the cost of collecting diverse demos, especially for generalizing across workspace variations. We propose MirrorDuo, a reflection-based formulation that operates on image, proprioception, and full 6-DoF end-effector action tuples, generating a mirrored counterpart for each original demonstration, effectively achieving "collect one, get one for free". It can be applied as a data augmentation strategy for existing learning pipelines, such as standard behaviour cloning or diffusion policy, or as a structural prior for reflection-equivariant policy networks. By leveraging the overlap between the original and mirrored domains, MirrorDuo achieves significantly improved performance under the same data budget when demonstrations are evenly distributed across...
论文介绍 本文针对基于图像的行为克隆中收集多样化演示数据成本高的问题，提出MirrorDuo框架。该方法利用镜像反射，为每个原始演示自动生成配对数据，实现“收集一次，免费获得一次”。该框架可作为标准行为克隆或扩散策略的数据增强手段，也可用于构建反射等变策略网络，从而在相同数据预算下显著提升性能。
第一作者: Junzhe Xu · 方向: 策略学习 · 来源: cs.RO
神经形态计算强化学习路径规划能效机器人仓储系统
Abstract:Dynamic environmental changes, confined workspaces, and stringent real-time constraints make pathfinding in Robotic Mobile Fulfillment Systems (RMFS) a challenging problem for conventional search- and rule-based methods, which typically suffer from high computational complexity and long decision latency. While reinforcement learning (RL) has emerged as a powerful alternative, deploying learned policies with extreme energy efficiency on resource-constrained hardware remains an open challenge. We present SDQN-RMFS, an end-to-end framework that achieves high-fidelity deployment of an RL-trained policy from a full-precision artificial neural network (ANN) through to a neuromorphic chip. By computing only when triggered by sparse events, this framework unlocks ultra-low-power RMFS pathfinding. Our full-stack pipeline operates as follows: an ANN policy is first efficiently trained...
论文介绍 本文研究机器人移动履约系统中的动态路径寻找问题。传统方法计算复杂度高且实时性差。作者提出SDQN-RMFS框架，将强化学习训练的策略从全精度人工神经网络部署到神经形态芯片上，实现事件驱动的计算。该方法利用稀疏事件触发计算，从而实现超低功耗的RMFS路径规划，为资源受限硬件上的高效策略部署提供了新思路。
第一作者: Jinghan Yang · 方向: VLA 通用模型 · 来源: cs.RO
VLA模型失败检测信息理论可解释性泛化能力
Abstract:Vision-Language-Action (VLA) models are increasingly deployed across diverse tasks, yet they remain black boxes whose physical interactions can cause irreversible harm, making generalizable and interpretable failure detection essential. We observe that successful and failed rollouts carry systematically different information-theoretic signatures. Building on this, we formalize VLA control as a closed-loop information pipeline and derive the Triple Information-theoretic (Tri-Info) signals that capture whether actions remain diverse, temporally consistent, and coupled to state transitions. Across six VLA models and three benchmark environments, Tri-Info matches the strongest baselines in-domain. Moreover, Tri-Info transfers across architectures, environments, and the sim-to-real gap without retraining, reaching 83\% accuracy on real-world tasks where prior detectors collapse to...
论文介绍 视觉-语言-动作模型在物理交互中可能存在风险，因此通用的失败检测至关重要。本文观察到成功与失败运行具有不同的信息论特征，据此将VLA控制形式化为闭环信息管道，并推导出三重信息信号（Tri-Info）。该信号能捕获动作的多样性、时间一致性及其与状态转换的耦合。实验表明，Tri-Info在领域内表现优异，并能跨架构、环境及仿真到现实进行迁移。
第一作者: Xiu Zhang* · 方向: 机器人操作 · 来源: cs.RO
增强现实机器人辅助手术人机交互用户研究经食道超声
Abstract:TransEsophageal Echocardiography (TEE) is essential for diagnosing and guiding Structural Heart Disease (SHD) interventions. However, manual TEE manipulation demands significant operator expertise, is physically demanding, and exposes clinicians to radiation when performed alongside fluoroscopy. Robotic-assisted TEE systems have been introduced to improve probe handling and reduce operator fatigue, yet the design of intuitive and effective user interfaces remains an open challenge. This study presents and evaluates a model-enhanced, Augmented Reality (AR)-based intuitive interface for robot-assisted TEE, designed to improve spatial awareness and control intuitiveness. A robotic TEE platform integrated with electromagnetic tracking and a virtual simulator was used to compare three user interfaces differing in visualization and interaction modalities: 2D jointlevel (2D-JI), 3D...
论文介绍 手动操作经食道超声探头对术者要求高且可能暴露于辐射。本文设计并评估了一种基于增强现实的直觉界面，用于机器人辅助的TEE手术。该界面集成电磁跟踪和虚拟仿真器，旨在提升空间感知与控制直觉性。通过一项用户研究，比较了三种不同的可视化和交互模态，以评估该AR界面在改善操作效率和用户体验方面的效果。
第一作者: Kaixin Lan · 方向: 具身智能 · 来源: cs.RO
对称性等变性世界模型敏捷运动四足机器人
Abstract:While latent world models enable the proactive predictions required for extreme parkour, their purely data-driven nature forces them to redundantly encode left-right symmetric interactions as independent patterns. This inflates the learning burden and hinders the capture of geometric regularities, restricting the latent space's efficiency for downstream policies. To address this, we propose SWAP, an end-to-end equivariant symmetric world model. This framework embeds symmetry directly into both the world model and the actor-critic networks. In real-world tests, the robot leaps across a 2.13 m gap and climbs a 1.63 m platform, breaking records for quadruped parkour. Furthermore, the framework exhibits robust geometric generalization to unseen mirrored terrains and exceptional zero-shot transferability across diverse outdoor environments. These results demonstrate that symmetry...
论文介绍 用于极限跑酷的潜在世界模型常需冗余编码左右对称交互。为解决此问题，本文提出SWAP，一个端到端的等变对称世界模型框架。它将对称性直接嵌入世界模型与演员-评论家网络中。在真实世界测试中，机器人能跨过2.13米间隙并爬上1.63米平台，展示了卓越的敏捷性。该框架还展现出对未见镜像地形的几何泛化能力与跨环境的零样本迁移能力。
第一作者: Hunter Kuperman · 方向: 具身智能 · 来源: cs.RO
深度展开分布式优化多智能体系统自适应超参数ADMM-DDP
Abstract:Distributed optimization is a highly scalable and structurally transparent technique to solve multi-agent robotics problems; however, such methods often suffer from the need for highly-specialized, problem-specific hyperparameter tunings. In this work, we propose Deep Coordinator, a deep-unfolding framework that learns to dynamically adjust the hyperparameters of ADMM-DDP, a popular distributed solver for robotics tasks, at solve-time in response to optimizer performance. Our architecture consists of unrolling a fixed number of ADMM-DDP iterations into a neural network with learnable functions between layers mapping the optimizer state to the next hyperparameters. To the best of our knowledge, Deep Coordinator is the first deep-unfolding framework to adapt the penalty parameters of a non-convex optimizer at solve-time; we show that the mainstream supervised approach can yield...
论文介绍 分布式优化常需为特定问题进行复杂的超参数调整。本文提出Deep Coordinator，一种深度展开框架，用于在求解时自适应调整ADMM-DDP算法的超参数。其架构将固定次数的ADMM-DDP迭代展开为神经网络，通过可学习的层间函数根据优化器状态动态设置下一轮的超参数。这是首个能在求解时调整非凸优化器罚参数的深度展开框架。
第一作者: Xuetao Li · 方向: 多模态具身 · 来源: cs.RO
人机共同创作音乐表演多模态具身智能语义理解实时执行
Abstract:Art has long stood as a pivotal expression of human creativity. Embodied artificial intelligence offers a route for generative models to participate in that creativity through physical action rather than disembodied digital content. In robotic music co-creation, it is challenging to connect semantic musical understanding with real-time and physically executable performance. We present Co-policy, a framework for human-robot musical co-creation that separates semantic intent grounding, constrained musical variation, and visuomotor execution. To ground musical semantics, Co-policy uses pre-inference semantic anchors and a fine-tuned Qwen-vl planner (F-Qwen) to transform speech, live musical seeds, and visual observations into structured co-creation plans. To support low-latency execution, Co-policy introduces a Gaussian-Mixture Visuomotor Policy (GMP), implemented as a...
论文介绍 在机器人音乐共同创作中，连接语义理解与实时物理执行是一大挑战。本文提出Co-policy框架，将语义意图接地、受限音乐变奏与视觉运动执行分离处理。它使用预推理语义锚点和微调的Qwen-vl规划器，将语音、音乐种子和视觉观察转化为结构化共创计划。为实现低延迟执行，引入了高斯混合视觉运动策略，使机器人能与人类进行响应式的音乐表演。
第一作者: Youbin Yao · 方向: 机器人操作 · 来源: cs.RO
双臂操作动作扩展层次化框架大语言模型效率提升
Abstract:Dual-arm manipulation can improve throughput via parallel execution, but collecting bimanual demonstrations for training is costly and difficult. We present ExS2D, a hierarchical action expansion framework that enables dual-arm manipulation from single-arm supervision. ExS2D first generates structured subtasks from textual instructions while explicitly capturing temporal precedence. It then grounds each subtask into executable actions through subtask-guided action mapping in observation. Finally, precedence-aware action allocation and synchronized planning are performed by a multimodal large language model driven coordinator to select collision-free dual-arm executions. Simulation experiments demonstrate that ExS2D reduces the average execution steps by 54.4% while maintaining a comparable success rate to a single-arm baseline. Real-robot experiments on four tasks further...
论文介绍 双臂操作能提升任务吞吐量，但收集双臂演示数据成本高昂。本文提出ExS2D框架，从单臂监督中生成双臂操作。该层次化方法首先从文本指令生成带时间顺序的结构化子任务，然后通过子任务引导将每个子任务映射到可执行动作。最后，由大语言模型驱动的协调器执行无碰撞的双臂同步规划。仿真显示，该方法在保持成功率的同时将平均执行步骤减少了54.4%。
第一作者: Tai Hyoung Rhee · 方向: 具身智能 · 来源: cs.RO
热红外图像去噪小波变换实时性机器人感知
Abstract:Thermal infrared (TIR) imaging has been a popular choice for field robotics due to its robust perception capability under low light visual degradation, but it suffers from severe stochastic and fixed-pattern noise that breaks downstream estimation. This noise is intensified indoors due to low thermal contrast and uniform temperature distributions, contributing to the relative lack of indoor TIR deployments. Existing TIR denoising methods exhibit a poor accuracy-efficiency tradeoff, either too slow for online deployment required in robotics or insufficiently robust to severe degradation, while typically being trained on synthetic noise. Addressing these problems, we propose TIDY, a lightweight wavelet-domain denoiser trained on real clean-noisy TIR data. By reformulating TIR denoising in the wavelet domain, TIDY explicitly disentangles noise from structural content, enabling...
论文介绍 该研究针对室内热红外图像噪声严重、现有去噪方法精度与效率权衡不佳的问题，提出轻量级小波域去噪器 TIDY。其核心是通过在小波域分解，并利用小波域熵和方向条纹指数显式分离噪声与结构内容，从而基于真实数据训练的模型实现高效去噪，有望提升机器人在低光或室内的感知能力。
第一作者: Thien-Loc Ha · 方向: VLA 通用模型 · 来源: cs.RO
视觉语言动作模型等变性机器人操作数据效率泛化
Abstract:Vision-Language-Action (VLA) models have emerged as a powerful paradigm for generalist robot manipulation, yet they lack geometric inductive biases: policies trained at specific orientations require substantially more data to generalize across rotational configurations. We present \textsc{EquiVLA}, the first general framework for end-to-end $\mathrm{SO}(2)$-equivariant VLA models, applicable to any architecture coupling a frozen vision-language backbone with a flow-matching Diffusion Transformer action head. \textsc{EquiVLA} introduces \textsc{EquiPerceptor}, which produces approximately $\mathrm{SO}(2)$-equivariant visual representations from frozen ViT features; and \textsc{EquiActor}, an exactly $\mathrm{SO}(2)$-equivariant flow-matching Diffusion Transformer action head. Together, they establish an approximate $\mathrm{SO}(2)$ equivariance chain from camera observations to...
论文介绍 为解决视觉语言动作模型缺乏几何归纳偏置、数据利用效率低下的问题，本文提出首个通用的端到端 SO(2) 等变 VLA 框架 EquiVLA。该框架通过 EquiPerceptor 生成近似等变的视觉表征，并配合完全等变的 EquiActor 动作头，建立了从观察到动作的等变链条，旨在以更少数据提升机器人操作对旋转配置的泛化能力。
第一作者: Trong-Bao Ho · 方向: 导航与运动 · 来源: cs.RO
异步执行动作分块初始噪声流式策略实时控制
Abstract:Action chunking enables robot policies to produce temporally coherent behavior, but generating multi-step action sequences with flow-based policies incurs latency that is incompatible with real-time control. Under asynchronous execution, the robot continues executing the current chunk while the next one is generated, causing even minor delays to create inconsistencies at chunk boundaries. Existing methods address this problem by steering generation toward the already executed action prefix. We instead show that prefix consistency can be achieved by selecting an appropriate initial noise before generation begins, allowing the unmodified flow ODE to produce a coherent next chunk. This reframes asynchronous inference as a noise selection problem rather than a trajectory steering problem. We introduce \textbf{PAINT}, a training-free method that finds this noise via backward Euler...
论文介绍 在异步执行机器人策略时，生成动作块的延迟会导致边界不一致。本文将此问题重新定义为初始噪声选择问题，并提出无需训练的方法 PAINT。该方法通过后向欧拉法找到合适的初始噪声，使得流 ODE 生成的下一个动作块能与已执行的前缀保持一致，从而提升实时控制的连贯性。
第一作者: Shaoshan Liu · 方向: 多模态具身 · 来源: cs.RO
人形机器人数据标准物理AI具身交互基础设施
Abstract:The scalability of humanoid robots will depend not only on models and hardware, but also on whether physical experience can accumulate across robots, tasks, organizations, and time. Drawing on the authors' work in developing ISO/WD 26264-1, Humanoid robot datasets -- Part 1: General requirements, within ISO/TC 299/WG 16, this article argues that data standards are becoming foundational infrastructure for Physical AI. We develop three insights. First, humanoid robot data is embodied interaction data, not a collection of isolated digital samples; a useful dataset must preserve the relationship among robot body, action, task, scene, execution trace, and outcome. Second, its value depends on physical coherence: multimodal streams are reusable only when timing, coordinate frames, calibration, kinematics, units, and synchronization assumptions remain inspectable. Third, the main...
论文介绍 本文指出，人形机器人的规模化依赖于跨机器人、任务和组织的经验积累，而这需要基础设施支持。基于作者参与制定 ISO 标准的经验，文章论证了数据标准是物理 AI 的基石，强调数据集需保留机器人身体、动作、任务、场景等要素间的关系，并确保多模态数据流在时序、坐标系等方面的物理一致性。
第一作者: Yinsen Jia · 方向: 机器人操作 · 来源: cs.RO
强化学习自模仿学习时间效率机器人操作长时间任务
Abstract:Long-horizon robot manipulation policies trained with reward shaping can still exploit dense rewards through inefficient interaction, while rare efficient behaviors may be forgotten during training. We argue that temporal efficiency itself provides a powerful and underutilized source of self-supervision for reinforcement learning. We introduce Temporal Self-Imitation Learning (TSIL), a reinforcement learning framework that mines temporally efficient successful trajectories generated during learning and converts them into reusable supervision for future policy improvement. TSIL progressively refines learning using configuration-conditioned adaptive temporal targets derived from fast successful trajectories, while preserving and replaying efficient behaviors through efficiency-weighted self-imitation learning. Across 15 distinct long-horizon manipulation tasks, TSIL consistently...
论文介绍 针对长时间跨度机器人操作任务中，奖励塑形可能导致低效交互和遗忘高效行为的问题，本文提出时间自模仿学习框架 TSIL。该框架从学习过程中挖掘出时间上高效的轨迹，并将其转化为自监督信号，通过配置自适应的时序目标和效率加权自模仿，持续优化策略，在15项任务中提升了学习效率。
第一作者: Marcus Hoerger · 方向: 具身智能 · 来源: cs.RO
POMDP在线规划扩散模型不确定性机器人规划
Abstract:Planning under uncertainty is an essential capability for autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides a powerful framework for such a capability. Although POMDP-based planning has advanced significantly, its application to real-world problems is often limited by the difficulty of obtaining faithful POMDP models. We present Vectorized Online planning wIth Learned diffusion model for POMDP Agents (VOiLA), a framework that learns task-agnostic POMDP models for online planning under uncertainty. VOiLA learns transition and observation samplers using conditional diffusion models and learns observation-likelihood models for particle-based belief updates. To enable efficient online planning, the diffusion samplers are distilled into compact feedforward generators and integrated with Vectorized Online POMDP Planner (VOPP), an online POMDP...
论文介绍 为解决部分可观测马尔可夫决策过程中模型获取困难的问题，本文提出 VOiLA 框架。该框架使用条件扩散模型学习任务无关的 POMDP 转移和观测模型，并将扩散采样器蒸馏为紧凑的前馈生成器，与向量化在线 POMDP 规划器 VOPP 集成，从而支持机器人在不确定性下的高效在线规划。
第一作者: Rui Fukushima · 方向: 具身智能 · 来源: cs.RO
运动学习双向互动辅导共同发展行为一致性
Abstract:Infants are well known to develop their motor skills through dense interaction with caregivers. Although such social interaction is crucial for human development, motor-skill learning in robots is often treated as a unidirectional process in which robots passively receive demonstrations from tutors. This overlooks a key property of social interaction: it is inherently bidirectional, with tutor and learner dynamically adapting to each other. In such interactions, the robot's past experiences may function as prior constraints that shape the dynamics of their co-developed trajectories. We hypothesize that bidirectional tutoring allows such constraints to guide the formation of consistent behavioral patterns that preserve behavioral coherence and support generalization, whereas unidirectional interaction lacks such constraints and leads to broader, less consistent behavioral...
论文介绍 借鉴人类发展过程中与看护者的双向互动，本文研究机器人运动技能学习中的双向辅导机制。研究假设双向互动中，机器人的过往经验会作为先验约束，与辅导者共同塑造交互动力学，从而形成稳定、可泛化的行为模式。与单向学习相比，这种共同发展的机制更能保持行为连贯性。
第一作者: Joong-Gil Kim · 方向: 具身智能 · 来源: cs.RO
双足机器人脚趾敏捷性效率冲击吸收
Abstract:Human legs exhibit high efficiency, agility, and impact absorption, with toes playing a crucial role in these capabilities. While many attempts have been made to implement human-like toes in robots, they have not fully replicated human characteristics nor rigorously validated their benefits. We propose a 14-DOF biped robot emulating human toes' lightweight, high-torque, robust nature. To quantitatively analyze the effectiveness of the active toes in terms of agility, efficiency, and impact absorption, we developed a high-fidelity simulation training environment that reflects actual actuators with coupled transmissions and accurate power consumption. To ensure a fair comparison between configurations with and without active toes, we designed a minimal RL reward function and applied an identical training procedure to both. The simulation results indicate that, at 1.33 m/s...
论文介绍 为量化活动脚趾对双足机器人性能的影响，本文设计了一个模拟人类脚趾轻质、高扭矩特性的14自由度双足机器人。研究构建了高保真仿真环境，通过最小化的强化学习奖励函数和统一的训练流程，公平比较了有无活动脚趾配置在敏捷性、能效和冲击吸收方面的表现。
第一作者: Natapat Kirdwichai · 方向: 数据集与评测 · 来源: cs.RO
四足机器人森林环境缠绕检测多模态数据集机器人故障
Abstract:Legged robots are increasingly deployed in forests for ecological surveying and monitoring, yet their autonomy is often interrupted consequent to the challenges posed in traversing forest environments. Forest entrapments, for example, when a robot's legs are ensnared in vines or other vegetation, result in loss of stability and toppling. Such events not only disrupt the mission and require manual intervention, but also risk damage to the robot hardware. To address the absence of a dedicated dataset to investigate these failure modes in forest environments, we present ForEnt, a multi-modal dataset collected with the low-cost Unitree Go2 quadruped across eight forest sites in the Southampton Common Woodlands, UK. For our dataset, over approximately 1.7 km of traversals in 11 sequences were conducted, yielding 69 recorded entrapment events. ForEnt includes time-synchronized RGB-D...
论文介绍 研究问题：四足机器人在森林环境中因植被缠绕导致故障，影响任务执行。核心方法：提出ForEnt多模态数据集，使用Unitree Go2机器人收集时间同步RGB-D等数据，记录69个缠绕事件。应用：可用于开发和评估防缠绕算法，提升机器人在复杂环境中的自主性。
第一作者: Christian Schaible · 方向: 导航与运动 · 来源: cs.RO
Ackermann转向安全导航未映射环境凸优化反馈线性化
Abstract:A control framework is proposed for safe local navigation of mobile robots equipped with Ackermann steering in unmapped environments where a global goal is absent. Based on local obstacle detections, the safest heading angle is determined along the direction of the largest open space ahead of the vehicle. Guided by this direction, bounding lines are constructed on the left and right sides of the vehicle to achieve obstacle separation. These bounding lines are obtained by solving a convex quadratic optimization that maximizes vehicle-to-obstacle clearance. Optionally, conditions are imposed on the bounding lines to preserve parallelism and smooth abrupt changes from prior control steps. A feedback-linearizing controller is then used to regulate the vehicle's distance from one or both bounding lines, effectively enabling tracking of a local reference path that preserves safety...
论文介绍 研究问题：Ackermann转向机器人在未映射环境中缺乏全局目标时的安全导航挑战。核心方法：基于局部障碍检测，通过凸二次优化确定边界线以最大化车辆与障碍物间距，并使用反馈线性化控制器跟踪安全路径。应用：可提高机器人在未知复杂环境中的局部导航安全性。
第一作者: Calvin Luo · 方向: 多模态具身 · 来源: cs.RO
扩散过滤探索样本高效微调生成控制政策多智能体协作机器人决策
Abstract:A natural recipe for intelligent robotic decision-making is initializing from pretrained generative control policies, which have summarized offline experience, and adapting them to self-collected online experience. We present DF-ExpEnse, an exploration technique that improves the quality of online experience collection, thus increasing finetuning sample-efficiency. DF-ExpEnse leverages the multimodal modeling capabilities of the generative control policy to create an expressive and tractably evaluatable candidate set. It then utilizes an ensemble of critics to identify the action that best balances quality with high exploration interest. In fleet settings, DF-ExpEnse further enables cross-agent communication to facilitate collaborative exploration as a group. DF-ExpEnse can be seamlessly integrated with existing strategies that finetune pretrained generative control policies...
论文介绍 研究问题：机器人决策中微调预训练政策时样本效率低。核心方法：提出DF-ExpEnse探索技术，利用生成政策的多模态建模能力创建候选动作集，通过评论家集成选择平衡质量和探索兴趣的动作，并支持多智能体协作。应用：可提升机器人从在线经验中快速适应的能力。
第一作者: Ahmad Farooq · 方向: 策略学习 · 来源: cs.RO
形式化验证多智能体强化学习决策树蒸馏安全保证神经政策
Abstract:Multi-agent reinforcement learning (MARL) enables agents to develop coordination strategies through emergent communication, but neural policies lack the formal safety guarantees required for safety-critical robotic deployment in drone swarms and autonomous vehicle fleets. We present the first end-to-end framework for safety verification of learned multi-agent communication policies through policy abstraction: neural policies are distilled into interpretable decision trees, then formally verified, with empirical validation confirming that verified safety properties transfer to original networks. Our four-stage pipeline consists of domain-specific feature extraction from agent observations, decision tree distillation achieving 97.9% +/- 1.2% fidelity to neural policies, automated translation to PRISM probabilistic model checker specifications with complete...
论文介绍 研究问题：多智能体强化学习中神经策略缺乏形式化安全保证，难以部署于安全关键系统。核心方法：提出端到端框架，将神经政策蒸馏为可解释的决策树，然后进行形式化验证，验证属性可转移至原网络。应用：可增强无人机群或自主车队等系统的安全可靠性。
第一作者: Ameya Salvi · 方向: 具身智能 · 来源: cs.RO
故障检测检索增强生成机器人操作仓库自动化异常事件
Abstract:Industry automation is witnessing an evolution in robotics driven by both technological breakthroughs and societal changes: progress towards generalist robots, embodied and physical artificial intelligence (AI), and increasing labor shortage in this http URL intelligent autonomous robot needs to not only act according to planned motions but also react to any unexpected events. In this study, we focus on such unexpected events in warehouses where robots are used for material handling. Specifically, we refer to any unexpected events as failures and develop methods to detect robot operations related failures. Rule-based detection methods may break since the form of failures could change due to the dynamic nature of both environments and tasks. We propose 'Fail-RAG', a Retrieval Augmented Generation (RAG)-based failure detection framework where failure images and context...
论文介绍 研究问题：仓库机器人操作中意外故障的检测，传统规则方法因环境动态性易失效。核心方法：提出Fail-RAG框架，基于检索增强生成技术，利用故障图像和上下文识别异常事件。应用：可提高仓库机器人在动态任务中的自主性和故障应对能力。
第一作者: Chuer Pan · 方向: 机器人操作 · 来源: cs.RO
视觉运动政策数据增强鱼眼相机高斯喷溅轨迹优化
Abstract:Visuomotor policies for manipulation have demonstrated remarkable potential in modeling complex robotic behaviors, yet minor alterations in the robot's initial configuration and unseen obstacles easily lead to out-of-distribution observations. Without extensive data collection effort, these result in catastrophic execution failures. In this work, we introduce an effective data augmentation framework that generates visually realistic fisheye image sequences and corresponding physically feasible action trajectories from real-world eye-in-hand demonstrations, captured with a portable parallel gripper with a single fisheye camera. We introduce a novel Gaussian Splatting formulation, adapted to wide FoV fisheye cameras, to reconstruct and edit the 3D scene with unseen objects. We utilize trajectory optimization to generate smooth, collision-free, view-rendering-friendly action...
论文介绍 研究问题：视觉运动政策在机器人初始配置变化或未见物体下易产生分布外观察，导致执行失败。核心方法：引入数据增强框架，从鱼眼相机演示生成增强图像序列和动作轨迹，使用高斯喷溅重建3D场景并进行轨迹优化。应用：可减少数据收集需求，提升政策的鲁棒性。
第一作者: Bennett Dogbey · 方向: 导航与运动 · 来源: cs.RO
概率可微分信号时序逻辑随机系统形式化规范轨迹优化鲁棒性
Abstract:Autonomous robots operating in uncertain environments must satisfy complex temporal and safety specifications despite stochastic dynamics and sensing noise. While Signal Temporal Logic (STL) offers robustness measures for gradient-based optimization, existing extensions either lack differentiability or ignore belief-space uncertainty. We introduce pdSTL (probabilistic differentiable Signal Temporal Logic), a framework that unifies probabilistic semantics with differentiable robustness over belief trajectories. pdSTL employs interval-valued probabilistic semantics to compute conservative satisfaction bounds, propagated compositionally through the STL syntax tree. We formulate the temporal robustness evaluation as a recurrent, LSTM-style unfolding of STL operators, enabling linear-time, differentiable monitoring suitable for end-to-end trajectory optimization. We validate pdSTL...
论文介绍 研究问题：自主机器人在随机环境中需满足复杂时序安全规范，现有逻辑扩展缺乏可微性或忽略不确定性。核心方法：提出pdSTL框架，统一概率语义与可微分鲁棒性，通过LSTM风格展开实现线性时间监控。应用：可用于自动驾驶等系统的端到端轨迹规划和验证。
第一作者: Han Zheng · 方向: 导航与运动 · 来源: cs.RO
空间碰撞感知局部规划四足机器人3D占用地图A*搜索
Abstract:Quadruped robots are increasingly expected to navigate through narrow passages, cluttered indoor scenes, and large-scale 3D unstructured environments. Existing local planners commonly approximate the robot using isotropic geometric inflation or rely on planar and elevation-map representations, leading to conservative motion in tight spaces and limited reasoning about overhanging structures. This letter presents SCAN-Planner, a spatial collision-aware local planning framework for long-range quadruped navigation. A yaw-aware twin-cylinder footprint is used to model the elongated robot body, enabling whole-body collision evaluation through sparse queries in an inflated 3D occupancy map. We further introduce a projected A* search that generates collision-free guidance on an interpolated ground-following surface, with z-gradient suppression to avoid obstacles horizontally while...
论文介绍 研究问题：四足机器人在狭窄或非结构化环境中导航时，现有规划器易保守或忽略悬垂结构。核心方法：提出SCAN-Planner框架，使用偏航感知双圆柱足迹建模机器人，通过稀疏查询评估碰撞，并引入投影A*搜索生成无碰撞指导。应用：可增强机器人在复杂地形中的长距离导航能力。
第一作者: Manuel Hernández · 方向: 具身智能 · 来源: cs.RO
范畴论层论自主组件软件组件集成语言形式化方法
Abstract:The proliferation of large-scale, decentralized systems of autonomous agents, such as swarms of robots and networked cyber-physical systems, presents a formidable challenge to traditional formal methods. The Software Component Ensemble Language (SCEL) offers a formal model for such systems, but its operational semantics is not ideal for reasoning about global, structural, and emergent properties. This report proposes a new, multi-layered mathematical model for SCEL using category theory and sheaf theory. We argue that a society of robots described in SCEL can be formally modeled as a sheaf on a topological space, where components are points, ensembles are open sets, and distributed knowledge forms the sheaf's data. In this framework, computational processes like information sharing become equivalent to the sheaf-theoretic operation of "gluing" local data. System failures can...
论文介绍 大规模去中心化自主智能体系统（如机器人集群）对传统形式化方法构成挑战。本文基于软件组件集成语言（SCEL），利用范畴论与层论构建了一个新的多层语义模型。该模型将组件视为拓扑空间中的点，集成系统视为开集，分布式知识构成层数据，信息共享等同于数据「粘合」操作。此框架为推理系统全局、结构性和涌现性提供了新的数学工具。
第一作者: Falak Mandali · 方向: 具身智能 · 来源: cs.RO
人形机器人状态估计不变扩展卡尔曼滤波本体感觉非惯性地面
Abstract:This paper presents an invariant extended Kalman filtering (InEKF) approach for real-time state estimation of humanoid robots operating on non-inertial ground using only onboard proprioceptive sensing. The proposed approach estimates the robot's base position and velocity relative to the moving ground frame without requiring direct measurements of ground motion or externally mounted sensors. By exploiting kinematic constraints at the stance foot through foot-mounted IMUs, the filter accounts for ground-induced nonlinearities in the process and measurement models while remaining fully proprioceptive. The estimator is formulated to admit a right-invariant measurement model, enabling favorable error dynamics under large initial uncertainties. Observability analysis establishes conditions under which the robot's relative base position and velocity are observable with respect to...
论文介绍 本文针对仅依赖本体感觉传感、在非惯性地面（如移动平台）上工作的人形机器人，提出一种不变扩展卡尔曼滤波（InEKF）方法进行实时状态估计。该方法通过足部安装的IMU利用运动学约束，估计机器人基座相对于移动地面的位置和速度，无需外部测量。滤波器采用右不变测量模型，在大初始不确定下具有良好的误差动态特性，并分析了相关状态的可观测性条件。
第一作者: Ryan Walker Brown · 方向: 导航与运动 · 来源: cs.RO
沙地运动阻力力理论物理引擎MuJoCo仿生机器人
Abstract:Recent advancements in Resistive Force Theory (RFT) enable approximation of ground reaction forces for locomotion in sand without the computational expense of modeling interactions with individual grains. However, these tools have been absent in 3D physics engines commonly used for robot simulation. We explore if resistive force approximations are sufficient, when integrated with standard dynamics calculations, to provide a stable substrate for a freely walking robot. To determine this, we implement 3D Granular Resistive Force Theory (3D RFT) in a physics simulation engine, MuJoCo. We verify simulations in multiple scenarios to demonstrate that key trends due to end effector shape, speed, and loading are preserved. Our implementation predicts walking distance and foot sinkage of a 12-Degree of Freedom hexapod robot within 20\% of experiments in sand. While RFT has inherent...
论文介绍 将机器人在沙粒等颗粒介质中的运动模拟整合到标准物理引擎中具有挑战性。本文探索将三维阻力力理论（3D RFT）集成到开源物理引擎MuJoCo中，以近似计算沙地反作用力。通过在多种场景下进行验证，模拟保留了末端执行器形状、速度和载荷等关键影响趋势。对12自由度六足机器人行走距离和足部沉降的模拟预测与实验结果误差在20%以内。
第一作者: Junyi Zhang · 方向: 具身智能 · 来源: cs.RO
游戏式学习具身智能体技能获取代码技能库自我指导探索
Abstract:Current agentic robot systems can write executable Code-as-Policy programs, observe feedback, and revise behavior across multiple attempts, but they remain largely task-driven: reusable skills are acquired only after explicit instructions. We study Playful Agentic Robot Learning, where an embodied coding agent uses self-directed play as a continual skill-learning stage before downstream tasks arrive. We introduce RATs, Robotics Agent Teams designed for play-time skill acquisition. During play, RATs proposes novel yet learnable exploratory tasks, plans and executes robot-code policies, verifies intermediate progress, diagnoses failures, retries with dense, step-level feedback, and distills successful executions into a persistent code skill library. At test time, the agent reuses relevant skills from this frozen library to help solve new tasks. Experiments in LIBERO-PRO and...
论文介绍 本文提出“游戏式具身智能体机器人学习”范式，并引入RATs（机器人智能体团队）系统。在下游任务到来前，RATs通过自我指导的游戏进行持续技能学习：它提出可探索的任务，规划、执行并验证机器人代码策略，在失败时进行诊断与重试，并将成功执行提炼为持久的代码技能库。测试时，智能体可复用此技能库来解决新任务，实验表明该方法有效提升了任务完成能力。
第一作者: Hongkang Cui · 方向: 机器人操作 · 来源: cs.RO
视觉伺服扩散策略生成式框架在线训练机器人操作
Abstract:Visual servoing is a fundamental technique in robotic manipulation and navigation. Regression-based visual servoing frequently experiences trajectory jitter as a result of noise-sensitive single-step mappings and the accumulation of errors during distribution shifts. In contrast, Diffusion Policy maintains temporal consistency by predicting action sequences and improves robustness through implicit data augmentation. This paper presents a novel diffusion-based servoing method. Based on Diffusion Policy, the proposed approach uses normalized image coordinates of observed tag corners as input and generates camera velocity through conditional denoising. To overcome the generalization limitations of models trained on static datasets, an online training paradigm is adopted, continuously expanding the diversity of training data through interactive experience collection. This strategy...
论文介绍 传统基于回归的视觉伺服易受噪声影响导致轨迹抖动。本文提出DiffusionVS，一种基于扩散策略的生成式视觉伺服方法。该方法以观测到的标记点归一化图像坐标为输入，通过条件去噪生成相机速度序列，利用扩散模型维持时序一致性并增强鲁棒性。为克服静态数据集训练的局限，采用在线训练范式，通过交互不断扩充训练数据多样性，提升了模型的泛化能力。
第一作者: Dennis Rotondi · 方向: 机器人操作 · 来源: cs.RO
3D场景图空间AI环境表示机器人综述
Abstract:3D Scene Graphs (3DSGs) have emerged as a powerful representation for spatial AI by combining geometric grounding with semantic and relational abstractions of the environment. Their expressiveness has made them relevant to a broad range of problems in robotics and computer vision, including manipulation, navigation, task planning, scene understanding, and many others. However, the field remains fragmented: different communities adopt distinct formulations, construction pipelines, and evaluation protocols, making it difficult to compare methods, identify common assumptions, and assess remaining challenges for robust real-world deployment. This survey provides a unified and critical review of 3DSGs, with particular emphasis on open challenges and future directions. We first formalize 3DSGs under a common definition and analyze the principal modeling choices that characterize...
论文介绍 三维场景图（3DSGs）通过融合几何信息与语义关系，成为机器人视觉和空间AI的强大环境表示。然而，该领域目前较为分散，不同社区采用不同的定义、构建流程和评估标准。本文对3DSGs进行了统一且批判性的综述，首先提出一个通用的形式化定义，分析主要建模选择，并重点讨论了实现稳健现实世界部署所面临的开放挑战与未来方向。
第一作者: Wenbo Ma · 方向: VLA 通用模型 · 来源: cs.RO
机器人装配基准测试乐高Duplo智能制造符号推理
Abstract:We introduceWorkBenchMark, a LEGO Duplo-based robotic assembly benchmark motivated by the RoboCup Smart Manufacturing League. Robotic assembly couples low-level manipulation with task-level symbolic reasoning under physical constraints, a combination that current end-to-end learning methods do not yet solve reliably. The benchmark provides 400 tasks across four complexity tiers. We provide an open-vocabulary perception, Assembly-by-Disassembly baseline solution. Our planning-based pipeline outperforms a modern vision-language-action approach across all tiers. The benchmark, simulation environment, and baseline implementation will be released openly to support the broader robotic assembly community.
论文介绍 本文受机器人世界杯智能制造联赛启发，引入WorkBenchMark，一个基于乐高Duplo的机器人装配基准测试。它提供400个跨四个复杂度层级的任务，用于研究结合底层操作与任务层符号推理的机器人装配问题。文章提出一个基于“拆解即装配”思路的开放式感知与规划基线方案，其性能在各层级上均优于现代视觉-语言-动作方法。该基准及配套环境将开源发布。
第一作者: Khurram Javed · 方向: 策略学习 · 来源: cs.RO
Physical Atari强化学习机器人学习物理平台Atari游戏
Abstract:We built a robot called the Robotroller that actuates an Atari CX40+ controller and a device called the Atari Devbox that renders the game frame and the reward signal from the Arcade Learning Environment on a screen. The Robotroller and the Atari Devbox, together with an off-the-shelf camera and a desktop computer, constitute a system that can be used to study reinforcement learning algorithms in the physical world. We call the full system Physical Atari. In this paper, we detail the key decisions that make Physical Atari a robust and accessible platform. To make the system robust, we designed the Robotroller so that all movement is done through bearings, which reduces wear. Additionally, we wrote software that monitors the state of the servos at a high frequency and intervenes to limit stress. To make the system accessible, we used affordable off-the-shelf components and...
论文介绍 本文构建了Physical Atari系统，旨在为物理世界中的强化学习算法研究提供一个稳健且易用的平台。该系统包含可操作Atari手柄的Robotroller机器人、能渲染游戏画面与奖励信号的Atari Devbox设备、摄像头和计算机。为提高稳健性，Robotroller采用轴承设计并监控舵机状态；为提高易用性，系统使用廉价现货组件并详细公开了设计关键决策。
第一作者: Yuyang Zhang · 方向: 具身智能 · 来源: cs.RO
世界动作模型图像编辑动作预测机器人控制具身智能
Abstract:World Action Models (WAMs) commonly rely on video generation to bridge visual world modeling and robot control. However, video-based WAMs face three coupled limitations: dense multi-frame future tokens make inference costly, full video prediction spends capacity on action-irrelevant temporal and appearance details, and long-horizon future imagination may introduce errors that mislead action prediction. These issues raise a simple question: Does world action model really need video generation? We propose ImageWAM, a simple WAM framework that repurposes pretrained image editing models for robot action prediction. In contrast to video generation, image editing provides a better-matched prior: it only needs to model a target-frame transformation, focuses on action-relevant current-to-target visual differences, and grounds task instructions to localized visual changes through edit...
论文介绍 本文提出一个核心问题：世界动作模型是否真的需要视频生成？针对视频生成方法存在的推理成本高、能力浪费在无关细节、以及长程想象易引入错误等问题，作者提出了「ImageWAM」框架。该框架利用预训练的图像编辑模型，专注于建模当前帧到目标帧的变换，直接预测机器人动作。这种方法利用了与动作相关的视觉差异先验，为机器人控制提供了一种更高效、更聚焦的替代方案。
第一作者: Ellina Zhang · 方向: 机器人操作 · 来源: cs.RO
3D场景表示物体中心学习自监督学习潜在粒子机器人操作
Abstract:We introduce 3D-DLP, a self-supervised object-centric representation learning model that decomposes scene-level RGB-D or voxel observations into a set of 3D latent particles. Building on the Deep Latent Particles (DLP) framework, each particle encodes disentangled attributes, including 3D keypoint position, bounding box dimensions, and appearance features, and represents a distinct entity in the scene. The model learns interpretable per-particle segmentation maps through an end-to-end self-supervised reconstruction objective. We demonstrate on both simulated and real-world datasets that the learned latent space is interpretable and controllable: by manipulating particle positions and decoding, we can generate novel scene configurations. Furthermore, we show that leveraging these compact 3D latent particles for downstream robotic manipulation improves performance over baselines...
论文介绍 本文介绍了一种名为「3D-DLP」的自监督物体中心表示学习模型。它能将RGB-D或体素观测分解为一组3D潜在粒子，每个粒子编码了3D关键点位置、边界框尺寸和外观特征等解耦属性。该模型通过端到端的自监督重建目标学习可解释的分割。实验表明，学到的潜在空间可解释且可控，通过操控粒子位置可以生成新场景。将这些紧凑的粒子表示用于下游机器人操作，性能优于基线方法。
第一作者: Juncheng Ma · 方向: 具身智能 · 来源: cs.CV
具身预训练第一视角视频数据稀缺性遥操作数据基础模型
Abstract:Embodied foundation models are expected to benefit from data scaling like large language models, but face a much tighter data bottleneck. Teleoperated real-robot trajectories remain the dominant pretraining source due to their precise action supervision and embodiment alignment, yet their scalability is limited by high collection cost, acquisition difficulty, and low behavioral and environmental diversity. These limitations have sparked interest in egocentric human video as a scalable, substantially lower-cost, and more diverse alternative for embodied model pretraining. However, its effectiveness compared to teleoperated real-robot data remains underexplored. To address this question, we conduct a systematic study comparing egocentric human video and teleoperated real-robot trajectories as pretraining data sources for embodied foundation models, under fixed post-training and...
论文介绍 当前具身智能基础模型面临数据瓶颈，昂贵的遥操作机器人轨迹是主要预训练数据源。本文系统研究了第一视角人类视频作为预训练数据源的潜力。研究旨在比较大规模、低成本且多样化的第一视角人类视频，与精确但稀缺的遥操作机器人轨迹在预训练具身基础模型中的效果差异。该研究对于探索突破数据限制、推动具身智能模型发展具有重要意义。
第一作者: Ganlin Yang · 方向: VLA 通用模型 · 来源: cs.CV
长期操作视觉语言动作策略视觉证据记忆关键帧预测具身智能
Abstract:Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-relevant cues become occluded or unobservable over time. While existing memory-augmented methods utilize historical context, they either suffer from severe information bottlenecks, incur high latency via decoupled dual systems, or rely on unselective buffers that accumulate massive visual redundancies. To address these limitations, we introduce EventVLA, an end-to-end framework founded on the concept of sparse visual evidence memory that comprises two core components: foundational visual anchors to retain initial and short-term contexts, and a dynamic Keyframe Evidence Memory (KEM) module. Specifically, KEM directly predicts future keyframe probabilities from the VLA's latent embeddings to autonomously capture and store sparse...
论文介绍 长期机器人操作中，标准视觉语言动作策略易因物体遮挡或信息消失而失败。现有记忆增强方法存在信息瓶颈、延迟高或冗余存储等问题。本文提出「EventVLA」框架，其核心是稀疏视觉证据记忆，包含用于保留初始和短期上下文的基础视觉锚点，以及一个动态关键帧证据记忆模块。该模块直接从策略的潜在嵌入中预测未来关键帧概率，自主捕获和存储关键视觉证据，以提升长期任务性能。
第一作者: Jianing Li · 方向: 多模态具身 · 来源: cs.CV
3D场景理解占用率重建视觉语言模型具身智能RGB图像
Abstract:Recently, vision-language models (VLMs) have made significant progress in 3D scene understanding, driving advances in applications such as embodied intelligence and robotic vision. However, existing approaches typically either rely directly on explicit 3D inputs (e.g., point clouds or RGB-D sequences), or introduce an additional 3D geometry encoder to derive 3D-aware visual tokens from 2D images. Such designs structurally decouple 3D geometric perception from the rich 2D semantics learned via vision-language pre-training, hindering the development of a unified 3D vision-language representation. In this work, we propose Occ-VLM, a novel framework for 3D scene understanding that operates purely on posed RGB images and employs a single 2D vision encoder. Specifically, Occ-VLM reconstructs 3D scene occupancy as an auxiliary geometric prior, which is utilized to spatially associate...
论文介绍 现有3D场景理解的视觉语言模型常依赖显式3D输入或额外的3D编码器，这割裂了3D几何感知与丰富的2D语义。本文提出「Occ-VLM」，一个纯基于位姿RGB图像并使用单一2D视觉编码器的新型框架。其关键思路是重建3D场景占用率作为辅助几何先验，利用该先验将2D视觉语言特征空间化地关联起来，从而构建统一的3D视觉语言表示，用于室内场景理解等任务。
第一作者: Navin Ranjan · 方向: VLA 通用模型 · 来源: cs.CV
模型量化混合精度任务证据感知视觉语言动作模型部署优化
Abstract:We propose Mix-QVLA, a task-evidence-aware mixed-precision PTQ framework for VLA models. Mix-QVLA anchors each quantized variant to the full-precision action-token reference decision and evaluates whether quantization preserves task-relevant evidence across key VLA functional boundaries. It computes normalized gradient-weighted task-evidence maps from boundary activations and compares full-precision and quantized maps using evidence-mass and attribution-distribution distortion, capturing changes in both the strength and allocation of decision-supporting evidence. A soft-bottleneck objective aggregates boundary-level degradation into layer-wise sensitivity scores. Mix-QVLA further models sensitivity throughout task execution, capturing phase-dependent shifts in layer importance rather than assuming a fixed sensitivity profile. The resulting evidence- and time-aware scores guide...
论文介绍 本文针对视觉语言动作模型提出了「Mix-QVLA」，一个任务证据感知的混合精度后训练量化框架。该方法将量化后的模型变体与全精度的动作令牌参考决策对齐，评估量化是否保留了关键VLA功能边界处的任务相关证据。它通过计算归一化的梯度加权任务证据图，并比较全精度与量化图之间的差异，来生成兼顾证据强度和分配的敏感度评分，指导混合精度分配，以实现高效部署。
第一作者: Wenli Xiao · 方向: 机器人操作 · 来源: cs.AI
策略自我改进编码智能体物理反馈循环机器人操作自动化研究
Abstract:Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the pursuit of general physical intelligence. Although emerging coding agents can generate code to automate algorithm search, their successes remain largely confined in digital environments. We conjecture that the missing abstraction to automate robotics research is a repeatable feedback loop for real-world policy improvement: reset the scene, execute a policy, verify the outcome, and refine the next iteration. To bridge this gap, we introduce ENPIRE, a harness framework for coding agents that instantiates this physical feedback routine with four core modules: an Environment module (EN) for automatic reset and verification, a Policy Improvement module (PI) that launches policy refinement, a Rollout module (R) to...
论文介绍 实现灵巧的机器人操作依赖大量人工监督和算法工程，这阻碍了通用物理智能的发展。现有的编码智能体虽能自动生成代码，但多局限于数字环境。本文提出「ENPIRE」框架，旨在建立一个用于策略自我改进的物理反馈循环。该框架为编码智能体提供了一个执行器，使其能在真实世界中重置场景、执行策略、验证结果并优化下一次迭代，从而尝试自动化机器人策略的研究与改进过程。
美股市场技术面呈现分化，主要指数如S&P 500 ETF（SPY）和Nasdaq 100 ETF（QQQ）保持多头排列，RSI14分别在54.1和59.1的正常区间，显示温和上行动量，但个股如微软（MSFT）和特斯拉（TSLA）为空头排列，RSI偏低。加密货币市场情绪极度恐慌，恐慌贪婪指数为23，比特币（BTC-USD）和以太坊（ETH-USD）均处空头趋势，RSI14分别为36和38.4，总市值2.26万亿美元，BTC主导率56.2%。中概股整体承压，阿里巴巴（BABA）RSI14超卖至24.7，拼多多（PDD）和京东（JD）空头排列，显示下行压力。商品外汇领域，黄金期货（GC=F）MACD死叉，原油期货（CL=F）RSI31.2偏弱，美元指数（DXY）则强势上行，RSI14超买70.9。宏观资产中，VIX恐慌指数下降至16.78，美债收益率调整后仍维持多头排列。整体技术面显示风险资产波动加剧，避险情绪升温。
美元指数DXY当前价格100.85，日涨幅0.76%，RSI14为70.9处于超买区间，MACD值为0.3469高于信号线0.2822形成金叉，趋势为多头排列，且接近52周高点。技术指标显示短期动量强劲但超买信号提示回调风险。
10年期美债收益率当前4.45%，日跌0.27%，5日跌1.87%，RSI14为50.8中性，MACD值0.0203略高于信号线0.0289，趋势为多头排列。技术指标显示收益率在调整后仍维持上行倾向。
阿里巴巴BABA价格107.1，日跌0.32%，5日跌幅4.96%，RSI14为24.7进入超卖区域，MACD值为-6.2971低于信号线-4.8371，趋势为空头排列。指标显示下行压力显著，但超卖可能预示技术性反弹。
以太坊ETH-USD价格1706.5，日跌2.37%，5日涨1.56%，RSI14为38.4中性偏弱，MACD值-83.7967高于信号线-106.7316形成金叉，但趋势为空头排列。金叉信号与空头趋势矛盾，表明可能处于整理阶段。
VIX 恐慌指数
10Y 美债收益率 (%)
美元指数 DXY
S&P 500 ETF
Nasdaq 100 ETF
Apple
Microsoft
Nvidia
Alphabet
Tesla
Meta
Bitcoin
Ethereum
Solana
阿里巴巴 (BABA)
拼多多 (PDD)
京东 (JD)
腾讯控股 (0700.HK)
黄金期货
WTI 原油期货
美元 / 人民币
本报告基于公开行情数据计算的技术指标，过去走势不代表未来表现，仅供技术指标解读参考，不构成任何投资建议。投资者应自行评估风险并结合其他信息决策。
At least one person was killed and dozens of others were injured in the crash near Bedford, England, the authorities said.
中文摘要 英国贝德福德附近发生火车相撞事故，当局称至少1人死亡，数十人受伤。
Iranian deputy foreign minister says Iran 'ready to move forward' on diplomacy with US, but war must end on all fronts.
中文摘要 伊朗副外长表示，伊朗准备与美国推进外交，但强调美国必须确保以色列停止攻击黎巴嫩，战争需在所有战线结束。
The minister for agriculture, Julie Collins, confirms case of H5N1 bird flu in Western Australia, with another suspected The deadly H5N1 bird flu strain has arrived on the Australian mainland with test results confirming a bird found on the Western Australian coast was positive for the disease. The
中文摘要 澳大利亚农业部长朱莉·柯林斯证实，西澳大利亚州发现首例大陆H5N1禽流感病例，另有一例疑似病例。
The fighting between Israel and Hezbollah in Lebanon had delayed the next stage of talks to end the U.S.-Iranian war. Hezbollah did not immediately comment.
中文摘要 以色列大使称，以色列承诺在黎巴嫩实施新停火，但部队将留守。以色列与真主党的战斗延迟了美伊战争谈判，真主党暂无回应。
More than eight million South Africans are living with HIV – the highest number of any country in the world.
中文摘要 美国宣布将停止资助南非的HIV项目。南非有超过800万HIV感染者，为全球最多。
Biden, a former Democratic president, argued that releasing the recordings would violate his right to privacy.
中文摘要 美国法官驳回前总统乔·拜登的诉讼，拜登要求扣留回忆录录音，理由是发布将侵犯其隐私权。
The conflict between Israel and Hezbollah, once seen as a secondary front to the American-Israeli war on Iran, has become one of the main obstacles to ending it.
中文摘要 黎巴嫩在美伊结束战争协议中成为关键薄弱环节。以色列与真主党的冲突，原被视为次要战线，现成为主要障碍之一。
At least 30 people have died since May in the Kigonze displacement camp in the Democratic Republic of Congo.
中文摘要 刚果民主共和国Kigonze流离失所者营地自5月以来至少30人死亡，埃博拉威胁日益加剧。
Ukraine has denounced the move, calling it a "strategic mistake" and "disrespectful".
中文摘要 波兰因二战部队名称剥夺乌克兰总统泽连斯基的最高荣誉，乌克兰谴责此举为“战略错误”和“不尊重”。
中文摘要 标题为“最新消息”，但无具体内容，无法生成摘要。
A 2015 law requiring congressional approval for any Iran nuclear deal is in the spotlight after this week's memo.
中文摘要 2015年法律规定任何伊朗核协议需国会批准，本周伊朗备忘录引发关注，特朗普是否必须提交国会成为疑问。
Talks come as Hezbollah, Israel say new ceasefire has been reached in wake of US-Iran memorandum to end war.
中文摘要 美国宣布下周在华盛顿举行新一轮以色列-黎巴嫩谈判。真主党和以色列称已达成新停火，此为美伊备忘录结束战争的一部分。
Italian Prime Minister says she didn't ‘beg’ Trump for G7 photograph.
中文摘要 意大利总理表示，她没有“乞求”特朗普拍摄G7照片，否认相关报道。
'No ceasefire can be considered meaningful while children continue to be killed' says UNICEF.
中文摘要 联合国称，尽管有停火协议，以色列在加沙平均每天导致一名儿童死亡。联合国儿童基金会强调，儿童持续被杀则停火无意义。
"Italy and I do not beg," Meloni said in a video rebuke posted on social media Friday. Italy's top diplomat, meanwhile, said he was cancelling a visit to the U.S because of the alleged remarks.
中文摘要 意大利总理梅洛尼否认特朗普编造的关于她的故事，并表示“意大利和我不会乞求”。意大利外长因相关言论取消访美行程。
Low-cost, long-range weapons could be deployed as soon as this year in war against Russia
中文摘要 英国公布为乌克兰研发的原型导弹，其组件不含美国部分。这款低成本、远程武器最快可在年内用于对抗俄罗斯。
Collision on the Midland Main Line is the first fatal rail incident in nearly two years
中文摘要 英国米德兰干线发生火车相撞事故，造成1人死亡，89人受伤。这是近两年来该国首次发生的致命铁路事故。
The $400mn gift has raised charges of conflicts between personal interests and official duties
中文摘要 特朗普接受卡塔尔赠送的价值4亿美元的飞机作为新「空军一号」，此举引发个人利益与公职冲突的质疑。
Barry sits down with Munger disciple Seth Klarman, CEO of Baupost Group, a Boston-based investment manager with a multi-strategy approach. They discuss Seth's start as a 25 year-old and journey to CEO. They also discuss his approach to risk, IPOs, and sectors along with his sports passions including
中文摘要 投资界传奇人物、Baupost集团CEO塞思·卡拉曼接受访谈，探讨其作为查理·芒格门徒的起点、风险管控、新股投资及所关注行业。
国際政治もマーケットも新たな局面へ踏み出した1週間。五つのニュースを厳選して振り返ります。
中文摘要 彭博一周精选新闻：美国与伊朗达成和平协议，日本央行加息至1%，东京证交所收盘指数首次突破7万点，标志着国际政经格局进入新阶段。
Starbucks Corp. laid off corporate workers in the London and Hong Kong hubs that oversee parts of its international business, as the coffee chain gives third-party licensees greater latitude to run its stores outside of North America.
中文摘要 星巴克进行架构重组，裁减其位于伦敦和香港的办公室职员，以将北美以外门店的运营更多地授权给第三方特许经营商。
Forecast by Department for Transport is a tenth of level predicted by the airport
中文摘要 英国政府研究发现，希思罗机场第三条跑道对英国GDP的贡献仅为0.05%，这一预测值仅为该机场此前预测的十分之一。
Canada applied a 10% import tax on imports of canned vegetables to protect domestic growers and food processors, the Department of Finance said in a statement Friday.
中文摘要 加拿大宣布对进口罐装蔬菜临时征收10%的关税，旨在保护国内种植者和食品加工商。
BaFin’s move comes as country’s oldest lender reports possible breaches of corporate governance
中文摘要 德国金融监管机构BaFin免去了贝伦贝格银行三位高管的职务，此举发生之际，这家德国最古老的银行报告可能存在违反公司治理的行为。
Brookfield Asset Management Ltd. is emerging as the frontrunner to acquire a controlling stake in telecom tycoon Patrick Drahi’s French fiber optic company XpFibre, according to people with knowledge of the matter.
中文摘要 据知情人士透露，布鲁克菲尔德资产管理公司有望领先竞购电信大亨帕特里克·德拉希旗下法国光纤公司XpFibre的控股权。
Ex-employees of Hattons of London took confidential customer data amid a booming market for bullion
中文摘要 法院认定，伦敦金币销售公司「Hattons of London」的前员工策划阴谋陷害竞争对手，在黄金市场繁荣期间窃取了公司机密客户数据。
Transaction expenses pushed the group into a pre-tax loss
中文摘要 爱尔兰食品集团Greencore的非执行主席看准低价机会进行交易，该公司因交易费用导致税前亏损。
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本帖使用社区公益推广，符合推广要求。我申明并遵循社区要求的以下内容： 我的项目是免费使用的，无收费（变相收费、赞助）部分： 是 我的帖子已经打上 公益推广 标签： 是 我的项目属于个人项目，与公司或商业机构无关： 是 我的项目不存在QQ、TG等群组引流： 是 我的项目不存在非运营必要的网站引流： 是 我的项目不存在为他人推广、AFF： 是 我的项目无关联的商业项目： 是 我的站点存在登录，并已接入 LINUX DO Connect： 是 我帖子内的项目介绍，AI生成、润色内容部分已截图发出： 是 以上选择我承诺是永久有效的，接受社区和佬友监督： 是 以下为项目介绍正文内容，AI生成、润色内容已
本帖使用社区公益推广，符合推广要求。我申明并遵循社区要求的以下内容： 我的项目是免费使用的，无收费（变相收费、赞助）部分： 是 我的帖子已经打上 公益推广 标签： 是 我的项目属于个人项目，与公司或商业机构无关： 是 我的项目不存在QQ、TG等群组引流： 是 我的项目不存在非运营必要的网站引流： 是 我的项目不存在为他人推广、AFF： 是 我的项目无关联的商业项目： 是 我的站点存在登录，并已接入 LINUX DO Connect： 是 我帖子内的项目介绍，AI生成、润色内容部分已截图发出： 是 以上选择我承诺是永久有效的，接受社区和佬友监督： 是 以下为项目介绍正文内容，AI生成、润色内容已
Emily Chang (主持人)： 你在百度的所见所闻，是否塑造了你对中国的看法？ Dario Amodei (Anthropic CEO)： 其实并没有。我在那里工作了一年。我想我学到更多的可能是关于语音、语音识别以及诸如此类的技术… Inside the Mind of Anthropic CEO Dario Amodei | The Circuit | Extended Interview 23 个帖子 - 20 位参与者 阅读完整话题
很抱歉昨天起床晚了，中午14:00号池榨干拉闸一段时间 这位国际友人的扫码次数已经被我榨干了 夜猫福利，今天签到88.88刀额度最后15分钟（1:30关闭签到） @jiven @FoundZiGu 最近提供的帮助 公益推广申明 状态 我的项目是免费使用的，无收费（变相收费、赞助）部分 是 我的帖子已经打上 公益推广 标签 是 我的项目属于个人项目，与公司或商业机构无关 是 我的项目不存在 QQ、TG 等群组引流 是 我的项目不存在非运营必要的网站引流 是 我的项目不存在为他人推广、AFF 是 我的项目无关联的商业项目 是 我的站点存在登录，并已接入 LINUX DO Connect 是 我帖子
地址：https://img2.design 可直接使用linuxDO登录，以 令牌桶 方式限流不限额，后续更高并发我以CDK形式发放兑换码吧 目前实现： AI提示词优化 原图编辑 图片智能增强（在不改变主题的情况下进行图片效果优化增强） 图片反推提示词 多图上传合并 SVG像素生成 API 同/异 调用 高并发出图 预设多组比例格式/多种预设风格 免费 gpt号池，没有高质量图。 下面是高并发令牌桶兑换码 （点击了解更多详细信息） 上面的码如果用完了，就CDK领吧，20LDC cdk.linux.do LINUX DO CDK Linux Do 社区 CDK 快速分享平台 - 让分享变得更简
想了很久还是发出来，昨晚吧，一件事情彻底的颠覆了我的三观，虽然我本身已经很渣了，可以说是扎到骨子里的那种，我端午节随机约见了一位在我眼里能打的上8分的女生（满分10分），一起去吃饭、买盲盒、去极地海洋公园啥的，晚上一起去了酒吧，然后自然而然的最后就去了维也纳，该发生的也都发生了，离谱的事情来了，那啥完她去洗澡了，迷迷糊糊的，有一个电话打过来，我以为是我的手机响了，我就直接接了，结果是一个男生，我还懵了，当时脑子没转过来，我直接朝着浴室喊了一句XX你的电话，然后那个男生就开始崩溃了应该是，我本以为他会说很多难听的话啥的，结果离谱的是还在求，最后我才知道那个男生应该是个舔狗，舔了半年了，差不多每次
先放个链接，去领300的券，已经用来买服务器的佬别着急，还能退的（没带aff不能杀我吧 university.aliyun.com 云工开物_阿里云高校用云支持计划，支持高校AI人才培养和科研创新-阿里云 “云工开物”是由阿里云发起的高校用云支持计划，支持AI时代高校人才培养和科研创新。与高校合作共建人工智能通识课，为大学生送免费算力资源。 通过验证变成立即使用就可以了，然后创建一个apikey bailian.console.aliyun.com 大模型服务平台百炼控制台 百炼控制台是阿里云大模型服务平台，提供AI模型训练、部署、推理一站式服务，支持多种大模型框架，助力企业快速构建AI应用。
之前几天降到96了，直到今天白天域名还能正常访问的时候也是96。估计现在蹬的人少了，不过估计很快Host大法就会传播开，到时候不知道Juice值还能不能维持768 56 个帖子 - 36 位参与者 阅读完整话题
我这个臭本科还是民办的肯定比不上站里各位92，还是在家里县城上找了一个小工作，大富大贵不会有，自己一人肯定够活了。接下来 8 月就要迈入牛马生活了，还有人生最后一个暑假过！ 33 个帖子 - 32 位参与者 阅读完整话题
众所周知clash是支持dns覆写的, 所以我们只需要配置一下any域名和ip的host覆写即可 27 个帖子 - 15 位参与者 阅读完整话题