Python · ★ 31,006 · 🍴 2,594 · 📈 1,111 stars today
AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
中文介绍 这是一个AI智能体技能模块，能够自动在Reddit、X、YouTube、Hacker News、Polymarket及全网范围内研究任意主题，并综合生成基于事实的摘要。适用于研究员、记者和内容创作者快速获取跨平台热点信息与趋势洞察。
C++ · ★ 88,085 · 🍴 56,597 · 📈 65 stars today
Open Source Computer Vision Library
中文介绍 这是一个经典的开源计算机视觉库，提供了从图像处理、特征检测到物体识别等数百种算法。主要使用C++编写，并支持Python、Java等多种语言接口。广泛应用于学术研究、工业检测、自动驾驶及各类图像视频处理应用开发。
Shell · ★ 36,633 · 🍴 2,642 · 📈 1,103 stars today
Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop
中文介绍 这是一款AI技能插件，旨在提升AI生成内容的品味与质量，防止其输出平庸、通用化的内容。它通过某种评估或引导机制，让AI的创作更具个性和深度。主要面向AI开发者和内容创作者，用于优化对话或内容生成体验。
Python · ★ 185,947 · 🍴 31,985 · 📈 1,112 stars today
The agent that grows with you
中文介绍 这是一个能够与用户共同成长的AI智能体，其设计理念是通过持续交互和学习来适应用户需求。它可能具备个性化学习或记忆能力。适用于希望获得长期陪伴、能够逐渐理解其工作与思考模式的开发者或普通用户。
TypeScript · ★ 27,260 · 🍴 3,098 · 📈 554 stars today
An Open Source implementation of Notebook LM with more flexibility and features
中文介绍 这是Google NotebookLM的一个开源替代方案，提供了更灵活的功能和定制空间。它允许用户上传文档并与之进行AI对话，整理和挖掘知识。适用于研究人员、学生和知识工作者进行文献管理和内容分析。
TypeScript · ★ 18,756 · 🍴 2,909 · 📈 183 stars today
Let's use AI to Earn!
中文介绍 这是一个旨在帮助用户利用AI技术创造收入的工具或平台集合。它可能提供各类自动化脚本、变现方法或案例，探索AI在营销、内容生成等领域的商业应用。面向创业者、自由职业者及对AI商业应用感兴趣的群体。
Rust · ★ 47,512 · 🍴 5,014 · 📈 322 stars today
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
中文介绍 这是一款开源、可扩展的AI智能体，其功能超越了简单的代码建议。它可以安装依赖、执行命令、编辑文件并进行测试，并支持接入任何大语言模型。主要面向开发者，用于自动化软件开发流程，提升编码效率。
TypeScript · ★ 29,723 · 🍴 2,946 · 📈 309 stars today
Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.
中文介绍 这是一个名为N.O.M.A.D的离线生存计算机项目。它是一个自包含的便携系统，集成了关键生存工具、离线知识库和AI助手，旨在无网络环境下为用户提供信息与支持。适用于应急准备、户外探险或技术爱好者。
C++ · ★ 115,326 · 🍴 19,302 · 📈 158 stars today
LLM inference in C/C++
中文介绍 这是一个用纯C/C++编写的轻量级高性能LLM推理框架。它使得在本地CPU及多种硬件上高效运行Meta的LLaMA及其他开源大语言模型成为可能。主要面向研究者和开发者，用于在本地或资源受限的设备上部署和测试大模型。
Python · ★ 7,183 · 🍴 699 · 📈 1,554 stars today
A vector index built on TurboQuant, written in Rust with Python bindings
中文介绍 这是一个基于TurboQuant技术构建的向量索引库，使用Rust语言编写以确保高性能，并提供了Python语言绑定。它旨在加速向量相似性搜索任务。适用于构建高性能的向量数据库或在大规模嵌入向量场景中进行快速检索。
Roff · ★ 72,448 · 🍴 16,239 · 📈 350 stars today
所有小初高、大学PDF教材。
中文介绍 这是一个收集了中国小学、初中、高中以及大学阶段主要学科PDF教材的开源项目。它为学生、教师或教育工作者提供了便捷的电子教材获取渠道，方便学习与参考。资源覆盖面广，具有很高的实用价值。
JavaScript · ★ 2,032 · 🍴 271 · 📈 262 stars today
OpenAI Plugins
中文介绍 这是OpenAI官方推出的插件系统，允许ChatGPT等模型安全地调用第三方API或执行特定操作，从而连接外部世界的数据和服务。面向开发者，用于扩展AI应用的功能边界，例如查询实时数据、执行预订或操作工具。
TypeScript · ★ 12,876 · 🍴 909 · 📈 245 stars today
Desktop app to manage markdown knowledge bases
中文介绍 这是一款用于管理Markdown知识库的桌面应用程序。它为用户提供了本地化、结构化组织和检索Markdown笔记与文档的界面。适合需要系统化整理个人笔记、技术文档或知识碎片的写作者、开发者及研究人员。
Python · ★ 13,731 · 🍴 1,834 · 📈 28 stars today
Useful tool to track location or mobile number
中文介绍 这是一个用于追踪地理位置或手机号码信息的实用工具。它可能通过公开的API或数据聚合方式实现查询功能。主要面向需要快速进行地理定位或号码信息调查的安全研究人员、测试人员或普通用户，使用需遵守相关法律法规。
Rust · ★ 1,456 · 🍴 33 · 📈 316 stars today
PostgreSQL in-database durable execution
中文介绍 这是微软推出的一个PostgreSQL扩展，旨在数据库内部实现持久化执行。它允许将长时间运行或需要高可靠性的任务（如工作流、批处理）直接放在数据库中执行，利用事务保证其持久性和一致性。适用于需要强一致性保障的数据处理场景。
@sairahul1 · 110.7K 粉丝 · 710.8K 阅 · 509 赞 · 97 转
How To Become An AI Engineer in 2026. Without a CS degree. Without a bootcamp. Without knowing what a transformer is today. Here's what nobody tells you: The companies hiring right now don't need
中文介绍 博主指出成为AI工程师不一定需要CS学位或训练营，关键在于实践能力和项目经验。当前公司招聘更看重解决实际问题的能力而非传统理论，为非科班出身者提供了清晰的入行路径参考。
@maubaron · 16.9K 粉丝 · 233.8K 阅 · 506 赞 · 19 转
Our YouTube channel has 125k subscribers and we've never made or uploaded a single video ourselves. This is a completely automated system. It is this very same strategy that made us the first app
中文介绍 介绍一套全自动的YouTube内容创作与增长工作流，通过该系统可在极短时间内获得大量订阅。关键点在于整个流程无需人工制作或上传视频，实现了频道从0到125k订阅的完全自动化运营。
@itsreallyvivek · 3.6K 粉丝 · 65.8K 阅 · 521 赞 · 28 转
A few days ago I wrote that getting into a frontier AI lab mostly comes down to two things: proven research and trench engineering. The more I think about it, the less these feel like separate skills.
中文介绍 作者认为进入顶尖AI实验室主要依赖两大核心能力：已发表的前沿研究和解决实际问题的工程能力，并强调这两项技能在实践中密不可分。这是对AI领域求职策略的深度思考。
@dickiebush · 441.8K 粉丝 · 57.7K 阅 · 519 赞 · 45 转
Legendary marketer David Ogilvy generated over $864 million for his clients. He was a British advertiser known as "The Father of Advertising." And in 1982, Ogilvy sent this 1-page memo to his staff:
中文介绍 博主将传奇广告人大卫·奥格威的写作准则输入Claude，构建了一个AI写作教练。通过融合人类营销大师的规则与AI能力，旨在提升写作与文案创作的效果，是一个具体的prompt工程应用案例。
@sheriyuo · 8.6K 粉丝 · 30.6K 阅 · 512 赞 · 44 转
After seeing several people receive PhD offers and then immediately land highly paid industry positions during spring recruiting, I started wondering whether going straight into industry might
中文介绍 作者基于观察，探讨了强化学习（RL）领域博士毕业生在春季招聘中迅速获得高薪工业界职位的现象，并由此思考是否应跳过博士直接进入工业界。提供了2026年AI岗位市场的侧面视角。
中文介绍 一个名为"Amazing Digital Dentures"的项目宣告失败，具体细节未提供。
a quiet day of RSI.
中文介绍 今天AI新闻领域没有太多事情发生，递归自我改进活动平静。
Your broken harness is actively making the model worse. Here's what I keep seeing after years of eyeballing trajectories, and what you need to fix.
中文介绍 文章讨论如何停止运送低质量的强化学习环境，指出常见错误如broken harness使模型变差，并提供修复建议。
On June 5, 404 Media reported that attackers had been using Meta’s AI customer support agent to steal Instagram accounts. Their approach was simple: They asked the agent to link the accounts to email addresses that they controlled, and the agent complied. One attacker broke into the dormant Obama Wh
中文介绍 6月5日，404 Media报道攻击者利用Meta的AI客户支持代理窃取Instagram账户，方法是通过要求代理将账户链接到攻击者控制的电子邮件地址。
a quiet day
中文介绍 今天没有太多AI新闻，活动平静。
**Anthropic's Mythos/Opus cycle** sparked mixed reactions with praise for **Claude Mythos**'s one-shot workflows and concerns over **Opus 4.8** benchmark regressions. **Opus 4.7** showed strong chemistry task performance, "making Claude a chemist." **Sakana AI** launched an **RSI Lab** focusing on r
中文介绍 Anthropic的Claude Mythos模型因单次工作流受赞，而Opus 4.8有基准回归担忧；Opus 4.7在化学任务表现强劲；Sakana AI推出了递归自我改进功能。
中文介绍 Anthropic Oceanus模型发生泄漏，ChatGPT引入Dreaming功能，涉及递归自我改进技术。
We talk with the VendingBench authors on evaling Claudes from Haiku to Mythos, and how they build leading, and lasting, frontier evals from scratch.
中文介绍 Andon Labs的Lukas Petersson和Axel Backlund讨论评估Claude模型从Haiku到Mythos，以及如何从头构建前沿评估基准。
中文介绍 NVIDIA发布Nemotron 3.5内容安全解决方案，为全球企业AI提供可定制的多模态安全功能。
中文介绍 EVA-Bench Data 2.0版本发布，涵盖3个领域、121个工具和213个场景。
Learn how Endava is using AI agents, ChatGPT Enterprise, and Codex to accelerate software delivery, automate workflows, and build an AI-native culture across the enterprise.
中文介绍 Endava公司正在围绕AI代理重新设计软件交付流程，利用AI代理、ChatGPT Enterprise和Codex来加速交付、自动化工作流并构建AI原生文化。
Most days in her chambers, Judge Maritza Braswell, a federal magistrate judge in Colorado, sifts through stacks of documents written by people without a lawyer. Many of them can’t afford to hire a lawyer, and others have cases too weak or too small to interest one. She reads each one carefully, mind
中文介绍 科罗拉多州联邦法官Maritza Braswell处理大量由无律师人士撰写的文件，反映了AI生成诉讼激增给法院带来的挑战。
ChatGPT introduces a new memory system to better remember preferences, keeping context fresh and relevant across conversations.
中文介绍 ChatGPT推出新的"Dreaming"记忆系统，旨在更好地记住用户偏好，保持对话上下文的相关性和新鲜度。
**NVIDIA** released **Nemotron 3 Ultra**, a fully open **550B MoE** model with **55B active parameters** and **1M context**, optimized for long-running agent tasks with up to **5x speedup** and **30% cost reduction**. It features hybrid Mamba/attention, LatentMoE, native MTP, and was pretrained on *
中文介绍 NVIDIA发布Nemotron 3 Ultra模型，这是一个全开放的550B MoE模型，具有55B活跃参数和1M上下文，针对长期代理任务优化，提供5倍速度提升和30%成本减少。
a quiet day.
中文介绍 Reve 2和Ideogram 4在图像生成领域引入布局功能，今天AI新闻活动平静。
第一作者: Thamilvendhan Munirathinam · 方向: 密码学协议
LLM代理访问控制带内拒绝信号合规性
As autonomous LLM agents increasingly hold real credentials and operate infrastructure without a human in the loop, operators have no standard way to tell an agent that a resource is off-limits. Access controls either let the agent in (it has valid credentials) or hard-fail it (indistinguishable from any other client). We propose a third mode: a lightweight, published in-band deny signal -- the Recuse Signal -- that a server emits over a protocol's existing channels (an SSH banner, a PostgreSQL NOTICE) asking a connecting automated agent to voluntarily withdraw. This is a cooperative governance control, the robots.txt analogue for live access; it is explicitly not a security boundary. Its value is entirely empirical and, to our knowledge, unmeasured: do compliant LLM agents actually honor such a signal? We define the signal as an open mini-standard, implement two zero- or low-footprint...
论文介绍 随着LLM代理在无监督下操作基础设施，标准访问控制缺乏告知资源禁止访问的方法。本文提出一种带内拒绝信号「Recuse Signal」，通过协议现有通道请求代理自愿撤回。这是一种合作治理控制，类似robots.txt。研究通过实验评估LLM代理对该信号的遵守情况，为自动化代理治理提供实证基础。
第一作者: Lin-Fa Lee · 方向: 密码学协议
WebMCP工具表面投毒运行时操纵攻击LLM代理
Abstract:WebMCP is a newly emerging protocol that enables websites to expose tools directly to AI agents, bypassing traditional user interfaces and introducing new security risks. The dynamic exposure of agent-accessible tools in WebMCP expands the attack surface of web sessions, especially when third-party scripts are involved. In this study, we identify a new potential threat, termed Mid-Session Tool Injection (MSTI), in which attackers leverage third-party scripts to inject malicious tools during an active session. To better characterize this threat, we classify MSTI based on the stage and target of manipulation, distinguishing between Tool Hijacking and Tool Framing. Tool Hijacking modifies the set of tools visible to the agent through mechanisms such as the AbortSignal API or race conditions during tool registration. In contrast, Tool Framing influences the agent's perception of...
论文介绍 WebMCP协议允许网站直接向AI代理暴露工具，但引入了新安全风险。本文识别了运行时工具注入攻击，攻击者通过第三方脚本注入恶意工具。研究将此类攻击分类为工具劫持和工具框架，并分析了机制如AbortSignal API和竞争条件，揭示了动态工具暴露对Web会话安全的影响。
第一作者: Sheila Zingg · 方向: 系统安全
数字身份钱包凭据披露隐私风险用户行为缓解措施
Abstract:The European Union will introduce the EUDI Wallet by late 2026, which allows users to hold digital credentials (i.e., representations of physical official identity documents) on their devices. This will allow users to securely and privately disclose identity attributes to websites. Although such a system has many benefits, it also introduces risks caused by poor credential disclosure decisions. In this paper, we (i) conduct a large-scale survey on credential disclosure with users and experts and (ii) evaluate the effectiveness and feasibility of our Credential Assistant that displays expert recommendations and user opinions. Our results show that users are likely to overshare (e.g., ~20% of users disclosed their official ID to news websites). This indicates that users struggle to protect their privacy, which will impact the usability of the EUDI Wallet and lead to privacy...
论文介绍 欧盟数字身份钱包（EUDI Wallet）允许用户安全披露身份属性，但用户可能因决策不当而过度分享隐私信息。本文通过大规模调查评估凭据披露行为，并提出一个凭据助手来显示专家建议和用户意见。结果表明约20%用户向新闻网站披露官方ID，凸显隐私保护挑战和钱包可用性风险。
第一作者: Parsa Memarzadehsaghezi · 方向: AI 安全
鲁棒集成选择性增强逃逸攻击机器学习分类器
Abstract:Evasion attacks present a significant challenge to the robustness of machine learning (ML)-based classifiers, particularly in critical applications such as fraud detection and cybersecurity. Although existing defense mechanisms are effective in some settings, they often suffer from limited generalizability and do not systematically improve model robustness across diverse attack scenarios. To address these limitations, we introduce Robust Ensemble of Selectively Strengthened and Augmented Predictors (RESSAP), a novel framework that transforms a single classifier into an ensemble of robust classifiers. Each classifier in the ensemble is trained on a carefully selected subset of features, where feature selection is guided by a resilience metric that accounts for both feature importance and robustness. During inference, a random subset of these classifiers is used to make...
论文介绍 逃逸攻击威胁机器学习分类器的鲁棒性，尤其在欺诈检测等关键应用中。现有防御机制泛化性有限。本文提出RESSAP框架，将单个分类器转化为鲁棒集成，通过基于韧性的特征选择和训练子集来增强模型。在推理时使用随机子集进行决策，提高跨攻击场景的鲁棒性。
第一作者: Parsa Memarzadehsaghezi · 方向: 密码学协议
代码大语言模型模型剪枝强化学习对抗性代码突变安全
Abstract:Large code language models (CodeLLMs) can generate and rewrite programs, enabling functionality-preserving code mutation that may be used to create diverse malware variants and evade signature-based detection. A key security question is whether this mutation capability survives model compression, which would make deployment feasible under limited hardware budgets. We propose SecRL-Prune, a structured pruning framework for CodeLLMs that operates on feed-forward (MLP/FFN) channels. Starting from a pretrained teacher, it learns a layer-wise pruning policy with reinforcement learning using a teacher-student KL-divergence reward. To improve efficiency, we cache the teacher's top-P predictions once and compare the pruned student against this compact target, avoiding simultaneous teacher-student residency in GPU memory. We evaluate SecRL-Prune on HumanEval using pass@k for execution...
论文介绍 代码大语言模型能生成功能保持的代码突变，可能用于恶意软件规避检测。本文研究模型压缩是否影响这一能力。提出SecRL-Prune框架，使用强化学习对前馈通道进行结构化剪枝，通过教师-学生KL散度奖励学习剪枝策略。在HumanEval上评估，旨在实现安全部署。
第一作者: Xi Yang · 方向: AI 安全
LLM观点操纵伪造证据注入Ghostwriter攻击认知脆弱性防御策略
Abstract:As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cognitive vulnerability in LLMs: their tendency to uncritically trust external context when presented with fabricated evidence bearing markers of credibility. We introduce Ghostwriter, a two-phase attack framework that first repackages misleading statements with fabricated rationales, then instruct target LLMs to incorporate these viewpoints when responding to relevant queries. Experiments on BBQ, ToxiGen, and our specialized dataset reveal that commercial LLMs without external safety classifiers remain highly vulnerable, while even frontier classifier-guarded models (e.g., GPT-5.4) reduce but do not eliminate the attack. Building on this, we explore multiple defense strategies, among which a tailored...
论文介绍 LLM在聊天中影响决策，但可能被伪造证据误导。本文介绍Ghostwriter攻击框架，先重新包装误导性陈述与伪造理由，再指示目标LLM整合这些观点。实验表明商业LLM高度脆弱，即使前沿模型也受影响。研究探索防御策略，如定制化方法来缓解攻击。
第一作者: Adelin Roty · 方向: 系统安全
移动设备安全再利用硬件安全电子废物生命周期
Abstract:An estimated 5.3 billion mobile phones became electronic waste in 2022. Many of these devices can be repurposed and used in different contexts to extend their lifetime and to reduce ecological impacts. An often overlooked aspect of smartphone reuse is cybersecurity: these devices embed hardware-backed security mechanisms that rely on vendor-controlled provisioning and are designed for a fixed device lifecycle. In this paper, we investigate whether security mechanisms and guarantees remain effective when devices are repurposed outside their original ecosystem. We explore security features in a PinePhone, an open-hardware smartphone, and focus on three core security aspects: boot chain integrity, isolation provided by the Trusted Execution Environment, and the protection of hardware-bound secrets. Our experiments simulate realistic repurposing scenarios and highlight the...
论文介绍 全球大量手机成为电子废物，再利用可延长生命周期并减少生态影响。但设备安全机制依赖厂商控制的生命周期。本文在开源硬件PinePhone上实验，评估启动链完整性、TEE隔离和硬件绑定秘密的保护。结果揭示再利用场景下的安全挑战和机会。
第一作者: Weilin Lin · 方向: 网络安全
图像安全分类器红队测试蒙特卡洛树搜索照片编辑规避攻击
Image safety classifiers serve as a critical component of contemporary content moderation systems on the internet. However, their resilience against user-style malicious image editing remains underexplored. Such behaviors are highly prevalent in daily scenarios but difficult to fully reproduce. To explore this vulnerability, we introduce RedEdit, a novel black-box red-teaming agent that formulates photo-editing evasion as a combinatorial search problem over edit-tool sequences. It adopts a Vision-Language-Model (VLM)-based proposer to generate semantically targeted candidate edits and a Monte Carlo Tree Search (MCTS) planner to prioritize promising edit paths while backtracking from ineffective ones. Together, the proposer and planner instantiate two key capabilities of human attackers, i.e., domain knowledge and iterative backtracking, respectively, to reproduce this practical threat...
论文介绍 图像安全分类器对用户风格的恶意照片编辑脆弱性研究不足。本文提出RedEdit代理，将编辑规避建模为组合搜索问题。使用视觉语言模型生成候选编辑，并用蒙特卡洛树搜索规划编辑路径。该方法模拟人类攻击者的领域知识和迭代回溯，以重现实际威胁。
第一作者: Hugo Bertin · 方向: 网络安全
多人在线游戏作弊检测数据集网络安全
Abstract:Cheating poses a significant threat to the Multiplayer Online Games (MOG) industry by degrading player satisfaction and undermining the fairness in competitive gaming. Despite efforts to develop mitigation techniques, cheating remains difficult to detect and prevent in practice. In particular, a class of cheats based on network flow disruption remains unsolvable. To find out how to detect such attacks we need access to representative labelled data. However, no such dataset exists. To address this gap, we leverage an experimental framework that combines a multiplayer online game with a plug-in capable of both reproducing cheating attacks and collecting logs at two levels: network and application-layer. This paper presents a dataset compiling records of game sessions played by both real players and automated game clients, with cheating actions explicitly logged. To the best of...
论文介绍 多人在线游戏作弊威胁玩家满意度和竞技公平性，尤其基于网络流破坏的作弊类难以检测。为研究检测方法，本文提出实验框架，结合游戏与插件，在网络和应用层收集日志，创建包含作弊行为的数据集，为开发相关检测技术提供基础资源。
第一作者: Gabriela Dobrita · 方向: AI 安全
智能合约漏洞检测图神经网络跨函数分析
Abstract:Existing learning-based detectors for Solidity smart-contracts reduce vulnerability detection to syntactic pattern matching within single functions, yet many of the most consequential exploits (The DAO, Cream Finance) exist not in any individual function but in the relationship between functions and in the combination of conditions that made the attack feasible. Thus, we propose AttackPathGNN, a graph neural network (GNN) that reframes detection as reasoning over explicit attack paths. Two architectural choices distinguish it from prior GNN-based detectors: (1)a State Interference Graph that links every pair of functions sharing mutable storage through typed, weighted edges and through directed reentrancy-path edges defined by an explicit five-condition predicate; (2)conjunction pooling, a differentiable AND-aggregator over eight named exploit preconditions whose log-sigmoid...
论文介绍 智能合约漏洞检测现有方法局限于单函数模式匹配，忽略函数间关键关系。本文提出AttackPathGNN，一种图神经网络，通过状态干扰图链接共享存储的函数，并使用连接池化聚合利用前提条件，实现跨函数漏洞推理，以提升检测准确性。
第一作者: Vasilis Vouvoutsis · 方向: 软件安全
恶意软件编码习惯认知风格行为分析
Malware research primarily studies the results, the methods, and the impact. Even from an offensive security perspective, what is examined is the method, not the development strategy of the offender. This study investigates the behavioral signatures and coding patterns embedded in the malware source code. By analyzing a large corpus of leaked malware code and comparing it with carefully selected benign open-source software, we apply static application security testing and compute multiple software metrics. Based on cognitive psychology and criminological theories, our work interprets differences in code structure and quality as behavioral indicators, reflecting distinct motivational structures, risk tolerances, and development strategies of malware authors compared to benign software developers. Our findings reveal that malware code is generally smaller, less documented, and exhibits...
论文介绍 研究探索恶意软件开发者编码习惯与认知风格的关联。通过分析泄露的恶意软件代码和良性软件，应用静态分析计算软件度量，基于心理学和犯罪学理论，将代码结构差异解释为行为指标，揭示恶意软件开发者的动机和风险容忍度特征。
第一作者: Yang Yang · 方向: 密码学协议
服务发现隐私保护无线网络匹配加密
Service discovery is a fundamental process in wireless networks, enabling devices to find and communicate with services dynamically, and is critical for the seamless operation of modern systems like 5G and IoT. This paper introduces PriSrv+, an advanced privacy and usability-enhanced service discovery protocol for modern wireless networks and resource-constrained environments. PriSrv+ builds upon PriSrv (NDSS'24), by addressing critical limitations in expressiveness, privacy, scalability, and efficiency, while maintaining compatibility with widely-used wireless protocols such as mDNS, BLE, and Wi-Fi. A key innovation in PriSrv+ is the development of Fast and Expressive Matchmaking Encryption (FEME), the first matchmaking encryption scheme capable of supporting expressive access control policies with an unbounded attribute universe, allowing any arbitrary string to be used as an...
论文介绍 无线网络服务发现协议需增强隐私和可用性。本文提出PriSrv+，基于PriSrv改进，开发快速表达匹配加密（FEME），支持无界属性宇宙的表达性访问控制，提升协议在资源受限环境中的性能，兼容现有无线协议如mDNS和BLE。
第一作者: Hassan Jalil Hadi · 方向: 密码学协议
入侵检测规则生成大语言模型基准测试
Abstract:Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, signature-driven rules limit adaptability to emerging and zero-day threats. Additionally, existing public datasets (e.g., CICIDS2017, UNSW-NB15) focus on traffic classification and provide little structured information to support automatic rule synthesis or prevention logic. To address this gap, we propose Generative Thread Intelligence (GenTI) \footnote{GenTI refers to the proposed framework, and GTI refers to the dataset.} an LLM-driven benchmark for automatic generation of IDPS rules targeting unseen attacks. The dataset (GTI) aggregates over 150k detection and prevention rules from Snort, Suricata, Emerging Threats, as well as 50k YARA, each annotated with protocol behavior, payload signatures, contextual relationships, mappings...
论文介绍 基于规则的入侵检测系统难以适应新兴威胁。本文提出GenTI，一个LLM驱动的基准框架，用于自动生成IDPS规则应对未知攻击。构建数据集聚合检测和预防规则，标注协议行为和签名，促进自动化规则合成与评估。
第一作者: Divesh Aggarwal · 方向: 密码学协议
密码学LPN问题复杂性理论
Abstract:The hardness of the Learning Parity with Noise (LPN) problem is a foundational assumption in cryptography, forming the basis of constructions ranging from symmetric-key primitives to public-key encryption and beyond. A central open question is whether the average-case hardness of LPN can be based on worst-case complexity assumptions, as has been achieved for the analogous Learning With Errors (LWE) problem. Existing worst-case-to-average-case reductions for LPN [BLVW19, YZ21] rely on statistical smoothing of linear codes, which inherently limits the resulting average-case hardness to noise rates as large as $1/2 - 1/\mathrm{poly}(n)$, which is insufficient for public-key applications. We explore a new approach towards obtaining such reductions: rather than requiring that random sparse combinations of the rows of the generator matrix of a code be statistically close to uniform...
论文介绍 学习带噪声奇偶性（LPN）问题是密码学基础假设，其平均情况硬度能否基于最坏情况假设是开放问题。本文探索新方法，避免现有归约中的统计平滑限制，以在低噪声情况下获取更紧的归约，推动密码学理论发展。
第一作者: Yang Yang · 方向: 密码学协议
服务发现隐私保护匹配加密无线通信
Abstract:Service discovery is essential in wireless communications. However, existing protocols provide limited privacy protection, leaking sensitive device information and opening routes to network attacks. This paper proposes a private service discovery protocol, called PriSrv, which enables both service providers and clients to specify fine-grained authentication policies before establishing connections. PriSrv achieves this via a dual-layer matching architecture: an outer layer filters mismatched entities using public attributes, while an inner layer handles mutual authentication using selectively disclosed private attributes. As a core component, we introduce the primitive of anonymous credential-based matchmaking encryption (ACME), which enables dual-layer matching in a single step to achieve bilateral policy control, selective attribute disclosure, and multi-show unlinkability...
论文介绍 无线服务发现易泄露设备信息，引发安全风险。本文提出PriSrv协议，通过双层匹配架构和匿名凭证匹配加密（ACME），实现细粒度认证策略、选择性属性披露和多次展示无关联性，增强隐私保护和使用便捷性。
第一作者: Linard Arquint · 方向: 软件安全
程序验证Go语言GCD算法形式化验证
Abstract:We verify the 'extendedGCD' implementation in Go's standard library ('crypto/internal/fips140/bigmod'), which plays a crucial role in the generation of RSA key pairs. Even though the Go implementation is supposedly a direct port from BoringSSL's implementation, we uncovered two deviations that each break the algorithm's invariants: (1) the Go implementation deviates in the way coefficients are updated, and (2) it permits a larger input domain. We address both deviations; the first by fixing the Go implementation, which results in an on average 24% speedup, and the second deviation by porting an existing proof for BoringSSL and extending it to cover the larger input domain. We prove correctness and termination of the fixed Go implementation using Gobra, a deductive program verifier for Go. Where necessary, we used Lean to prove key lemmata on non-linear arithmetic, which we...
论文介绍 Go标准库中扩展GCD实现对RSA密钥生成至关重要。本文发现并修复实现中的两个偏差，使用Gobra进行形式化验证，结合Lean证明算术引理，确保算法正确性和终止性，提升密码学库的可靠性。
第一作者: Tsun On Kwok · 方向: AI 安全
RAG数据库版权保护水印技术合成知识探测机制
Abstract:Protecting proprietary RAG databases from unauthorized redistribution is challenging: existing watermarking methods either inject fabricated relations between real entities, polluting the knowledge base with misinformation, or embed fragile lexical patterns that adversarial paraphrasing easily removes. We propose SentinelRAG, a watermarking framework that embeds style-consistent but fictitious knowledge entries into the RAG database. Our key insight is that synthetic knowledge describing fictitious entities is unlikely to be retrieved by legitimate queries, yet can be reliably triggered through targeted probes known only to the data owner. Experiments on four datasets ranging from 2.9k to 8.8M documents demonstrate that SentinelRAG achieves statistically significant detection $p < 10^{-5}$ across all tested configurations at only a 0.1% injection rate. Compared to the...
论文介绍 本文针对专有检索增强生成（RAG）数据库的版权保护难题，提出SentinelRAG水印框架。该方法向数据库注入风格一致但虚构的知识条目，这些条目通常不会被正常查询检索，但数据所有者可通过特定探测触发。实验表明，在极低注入率下即可实现高置信度的数据库来源验证，为保护知识库提供了一种不影响查询质量的新途径。
第一作者: Van Le · 方向: AI 安全
TinyML航天器网络安全SPARTA攻击模型延迟-准确率权衡轻量级检测
Abstract:Autonomous spacecraft require rapid, lightweight, and reliable onboard detection of cyber-RF threats. Using the SPARTA attack model, we analyze the latency-accuracy trade-offs of TinyML-compatible classical models -- Random Forest, Logistic Regression, SVM, and MLP -- for detecting uplink jamming, Fake-NR spoofing, payload manipulation, ground-segment compromise, and unauthorized command injection. We present a physics-informed theoretical analysis of each model's computational complexity, VC dimension, Lipschitz continuity, and latency scaling, supported by empirical measurements on adversarial RF spectrograms generated via BandErasure, FakeNR, and NoiseBurst corruption modes. Results show that Logistic Regression achieves microsecond-level inference with only a 1\% accuracy drop relative to Random Forest, making it an effective TinyML baseline for onboard autonomy. The study...
论文介绍 本研究分析了面向自主航天器的基于TinyML的网络安全检测方案。针对上行链路干扰、欺骗、载荷操纵等无线射频网络威胁，本文评估了随机森林、逻辑回归等经典模型的延迟与准确率权衡。理论与实验分析表明，逻辑回归在微秒级推理延迟下仅损失少量精度，可作为星载自主系统的轻量级有效基线。
第一作者: Mohammad Tariq Ikhlas · 方向: AI 安全
CNN-LSTM入侵检测IoT安全多类分类时空特征
Abstract:With the rapid proliferation of IoT devices, security concerns have dramatically escalated and intrusion detection systems have become critical for protecting networked environments. This paper presents an improved CNN-LSTM based intrusion detection model that combines multi-class classification, dataset integration, and temporal feature learning to enhance detection performance in IoT networks. Using network traffic data, the proposed approach is evaluated on intrusion detection tasks and achieves an accuracy of approximately 97%. Experimental results demonstrate that the model effectively detects multiple attack categories while maintaining stable training and validation performance. The integration of convolutional and recurrent neural network components enables the framework to capture both spatial and temporal characteristics of network traffic, improving overall...
论文介绍 本文提出了一种改进的CNN-LSTM混合模型，用于物联网网络入侵检测。该模型结合卷积神经网络的空间特征提取与长短期记忆网络的时序特征学习能力，并整合了多类分类与数据集融合策略。实验评估显示，该模型在IoT网络流量数据上能达到约97%的检测精度，并能有效识别多种攻击类别。
第一作者: Minseok Choi · 方向: AI 安全
大语言模型安全越狱防御对比安全记忆自演化护栏决策推理
Abstract:Despite advances in safety alignment, large language models remain vulnerable to continuously evolving jailbreaks. Existing fine-tuned safety classifiers cannot adapt to these evolving attacks, while adaptive memory-based guardrails tend to over-refuse benign queries that resemble stored attacks. We propose Membrane, a self-evolving guardrail built on Contrastive Safety Memory (CSM): each cell pairs the conditions for blocking a harmful query with those for permitting a superficially similar benign request. Without retraining, Membrane evolves CSM by distilling each harmful interaction and its benign counterpart into a contrastive cell indexed by the underlying attack strategy, so that one cell generalizes across topical variants of the same mechanism. At inference, retrieved cells serve as grounding context for precise safety decisions. Across model-level safety on HarmBench...
论文介绍 针对大语言模型面临的持续演化越狱攻击，本文提出Membrane自演化护栏。其核心是构建对比安全记忆，将有害查询的拦截条件与相似良性查询的放行条件配对存储。系统无需重新训练，通过蒸馏新交互来演化记忆。推理时，检索到的记忆作为上下文，支持做出精确的安全决策，以应对不断变化的攻击模式。
第一作者: Shuze Liu · 方向: AI 安全
模型提取攻击API流量监控语义空间嵌入分布测试最大均值差异
Large language models (LLMs) are increasingly deployed through hosted APIs, making model extraction a practical threat to model ownership and service security. However, individual extraction queries often resemble benign requests, and existing evaluations often focus on single-query anomaly scoring or pure benign-versus-attacker user settings. We formulate model extraction monitoring as benign-calibrated traffic-window distribution testing and show that an embarrassingly simple detector is effective: embed incoming queries into a semantic space and test whether their aggregate distribution deviates from historical benign traffic. We instantiate the detector with maximum mean discrepancy (MMD), using only benign-vs-benign comparisons to set the decision threshold. We evaluate on fourteen attacker-normal query pairs from four extraction scenarios and compare with adapted PRADA, SEAT...
论文介绍 本文针对通过API进行的大语言模型模型提取威胁，提出一种简单的检测方法。它将模型提取监控问题定义为良性流量校准的分布测试：将查询嵌入语义空间，并测试其聚合分布是否偏离历史良性流量。基于最大均值差异的检测器仅使用良性样本对来设定阈值，在多个模拟提取场景中展现出有效性。
第一作者: Md. Iqbal Hossan · 方向: 密码学协议
关键基础设施CNN-LSTM网络攻击检测机器学习评估CSE-CIC-IDS2018
Abstract:Digital infrastructure is growing at a rapid pace in the United States, and as a result, exposure to advanced cyber threats to critical sectors including healthcare, finance, transportation, energy and government systems is growing. The traditional cybersecurity approaches, including signature-based intrusion detection systems, have become less effective against today's cyber attacks, as they are unable to detect unknown and changing attacks in real time. To overcome these constraints, this research suggests a smart cyber-defense system, which utilizes Artificial Intelligence (AI) and Machine Learning (ML) algorithms in the detection and prevention of cyber attacks in the U.S. digital infrastructure. This study uses the CSE-CIC-IDS2018 dataset, which is a realistic network traffic dataset, along with various cyber attack scenarios, including Distributed Denial of Service...
论文介绍 本文聚焦美国关键数字基础设施面临的网络威胁，提出一个结合人工智能与机器学习的智能网络防御系统。研究采用真实的CSE-CIC-IDS2018网络流量数据集，评估了多种机器学习算法，并重点构建了一个混合CNN-LSTM框架用于网络攻击检测与预防，旨在提升对未知和变化攻击的实时检测能力。
第一作者: B. M. Taslimul Haque · 方向: 系统安全
关键基础设施XGBoostSHAP入侵检测可解释AI
Abstract:The increasing penetrations of the critical infrastructure sector in the United States with intelligent digital technologies have greatly increased exposure to advanced cyber adversaries and operational vulnerabilities. AI-powered governance and automated decision-making systems are becoming a key part of the operation of critical infrastructure systems, including energy, healthcare, transportation, financial services, and communication infrastructure, in order to improve efficiency and strategic management. The growing cyber threat environment, such as Distributed Denial of Service (DDos) attacks, botnets, ransomware, and Advanced Persistent Threats (APTs) pose significant challenges to infrastructure resilience, cyber security reliability, and governance trustworthiness. In a changing attack landscape and dynamic network environment, traditional cybersecurity mechanisms can...
论文介绍 本文提出一个基于可解释人工智能的网络安全分析框架，用于美国关键基础设施的智能治理。框架采用XGBoost模型进行入侵检测，并利用SHAP方法增强模型决策的透明度和可解释性。研究旨在通过AI驱动的风险分析和可靠性评估，应对分布式拒绝服务攻击、勒索软件等复杂威胁，提升基础设施的韧性与治理可信度。
第一作者: Md. Arifur Rahman · 方向: AI 安全
联邦学习可解释AI认知安全分析分布式系统威胁检测
The increasing adoption of distributed infrastructure systems, cloud computing, Internet of Things (IoT) technologies, and edge-based architectures has significantly expanded the cybersecurity attack surface and introduced increasingly sophisticated cyber threats. Conventional centralized intrusion detection approaches often face challenges related to scalability, data privacy, communication overhead, and limited transparency in artificial intelligence-driven decision-making processes. To address these limitations, this study proposes a Cognitive Threat Intelligence and Explainable Federated Security Analytics framework for distributed infrastructure systems. The proposed framework integrates Federated Learning (FL), Explainable Artificial Intelligence (XAI), and cognitive cybersecurity analytics to enable collaborative and privacy-preserving cyber threat detection across distributed...
论文介绍 针对分布式基础设施系统面临的数据隐私和决策透明度挑战，本文提出一个认知威胁情报与可解释联邦安全分析框架。该框架整合了联邦学习、可解释人工智能和认知安全分析技术，旨在实现跨分布式环境的协作式、隐私保护型网络威胁检测，以应对物联网、云计算等技术扩大带来的复杂攻击面。
第一作者: Zhiyu Sun · 方向: 隐私保护
k-近邻查询位置隐私差分隐私拒绝采样
Abstract:The k-nearest neighbor query (kNNQ) is a core component of modern location-based services (LBS) and has been widely adopted in popular features such as ``people nearby''. However, its potential privacy risks have long been overlooked. In this work, we present the first two attacks against kNNQ, namely the geometric intersection location inference attack (GI-LIA) and the zero-order optimization location inference attack (ZO-LIA), revealing the inherent location privacy risks posed by kNNQ. To mitigate these privacy risks, we further propose DPRS, a differential privacy framework for kNNQ protection. The core idea of DPRS is to incorporate a rejection sampling mechanism within a constrained perturbation interval, thereby mitigating the distance distortion caused by excessive noise injection. In addition, we design a private interval construction algorithm to construct the...
论文介绍 本研究首次揭示了 k-近邻查询中存在的两种位置隐私推断攻击，即几何相交攻击和零阶优化攻击。为应对此风险，论文提出了一种名为 DPRS 的差分隐私保护框架，其核心在于在受约束的扰动区间内引入拒绝采样机制，以减少噪声注入导致的过度距离失真，并设计了私有区间构建算法。该工作为基于位置服务中的隐私保护提供了新的攻击分析与防御方案。
第一作者: Seungwon Jeong · 方向: AI 安全
大语言模型越狱攻击位置脆弱性对抗性令牌
Abstract:As large language models (LLMs) are widely deployed, identifying their vulnerability through jailbreak attacks becomes increasingly critical. Optimization-based attacks like Greedy Coordinate Gradient (GCG) have focused on inserting adversarial tokens to the end of prompts. However, GCG restricts adversarial tokens to a fixed insertion point (typically the prompt suffix), leaving the effect of inserting tokens at other positions unexplored. In this paper, we empirically investigate \emph{slots}, i.e., candidate positions within a prompt where tokens can be inserted. We find that vulnerability to jailbreaking is highly related to the selection of the \emph{slots}. Based on these findings, we introduce the \textit{Vulnerable Slot Score} (VSS) to quantify the positional vulnerability to jailbreaking. We then propose SlotGCG, which evaluates all slots with VSS, selects the most...
论文介绍 本文针对大语言模型，探索了在提示词中插入对抗性令牌的「槽位」选择对越狱攻击成功率的影响。研究发现，模型的脆弱性与插入位置高度相关。为此，论文提出了「脆弱槽位分数」来量化位置脆弱性，并在此基础上引入 SlotGCG 方法。该方法通过评估所有槽位的 VSS 值来选择最有效的插入位置，从而优化攻击效果，是对现有攻击技术的一个重要补充。
第一作者: David Mellafe Z · 方向: 安全研究
网络安全漏洞披露框架比较开源情报
We introduce the Coverage Gap as a measurable distance between the observable public exposure of critical-infrastructure operators and their declared capability to coordinate vulnerability disclosure. We instantiate it against the 915 Chilean Operadores de Importancia Vital (OIVs -- Operators of Vital Importance) designated by the National Cybersecurity Agency (ANCI) under Ley 21.663 (Resolucion Exenta No. 87, 16 December 2025). Using a passive-only, OSINT-based method consistent with the principles of ISO/IEC 29147:2018 and Chile's computer-crimes safe harbour (Ley 21.459), we conduct a full-universe census of the foundational disclosure-capability layer (Layer 1, verifiable disclosure contact) across approximately 98.7% of the official catalogue. Only 16 of 915 OIVs (1.7%) publish a verifiable RFC 9116 disclosure channel; among operators of physical-world infrastructure -- energy...
论文介绍 本文定义了「覆盖差距」这一概念，用以衡量关键基础设施运营商的公开暴露程度与其漏洞披露协调能力之间的距离。研究以智利被指定的「重要运营商」为对象，使用符合标准的被动式开源情报方法进行调查。结果显示，仅有极少数运营商公布了可验证的披露渠道，而物理基础设施运营商的情况更差。论文通过与美国、欧盟和英国的框架进行对比，凸显了智利在网络漏洞披露准备上的显著不足。
第一作者: Nelly Elsayed · 方向: AI 安全
网络安全降维主成分分析线性预测编码
Abstract:High-dimensional feature representations are widely used in machine learning-based cyberattack detection systems. However, they increase computational complexity and may hinder deployment in resource-constrained environments. In this paper, we investigate feature compression techniques for cyberattack classification by comparing two dimensionality reduction approaches: Principal Component Analysis (PCA) and Linear Predictive Coding (LPC). Compressed feature representations with varying dimensionalities are generated and evaluated across several classification models. Experimental analysis demonstrates that PCA preserves classification performance even under aggressive compression. On the other hand, LPC provides competitive predictive representations with slightly larger performance degradation. The results show that substantial reductions in feature dimensionality can be...
论文介绍 针对基于机器学习的网络攻击检测系统中高维特征带来的计算负担问题，本文对比了主成分分析和线性预测编码两种降维技术。研究生成了不同维度的压缩特征，并在多个分类模型上进行评估。实验分析表明，即使在激进的压缩下，PCA仍能保持分类性能；而 LPC 则能提供具有竞争力的预测表征，但性能略有下降。研究证实了大幅降低特征维度的可能性，有助于在资源受限环境部署相关系统。
第一作者: Anlan Zheng · 方向: AI 安全
自动化渗透测试大语言模型对抗性框架智能防御
Abstract:LLM-driven automated penetration testing agents are typically evaluated against static targets that neither detect nor respond to attacks, so their behavior under intelligent defense remains untested. The causal consistency of multi-step attack chains likewise hinges on unstable LLM reasoning, and agent decisions remain opaque to human analysts. These three shortcomings, in realism, consistency, and auditability, are usually patched in isolation. We present ZERO-APT, a turn-based attacker-defender-judge framework that addresses them within a single architecture. For realism, ZERO-APT embeds a configurable LLM Defender that consumes Sysmon telemetry and detects attacks in real time, exposing the attacker to a live opponent rather than a passive target. For consistency, three architectural mechanisms move causal consistency from unstable LLM reasoning into enforced system...
论文介绍 现有基于大语言模型的自动化渗透测试通常在静态目标上评估，缺乏对智能防御的应对。本文提出 ZERO-APT，一个基于回合制的攻击者-防御者-评判框架。该框架通过嵌入一个可配置的LLM防御者来模拟实时检测攻击，增强了测试的真实性。同时，它通过架构机制确保了攻击链的一致性，并增强了决策的可审计性。该研究旨在为评估LLM渗透测试代理在更真实环境下的能力提供一个闭环平台。
第一作者: Junhyuk Lee · 方向: 密码学协议
比特币区块奖励交易费安全机制
Abstract:Bitcoin's block reward is scheduled to decline to zero, raising concerns about whether the network can remain secure once miners rely solely on transaction fees. This paper seeks to identify the conditions under which large-scale and persistent deviation from honest mining can arise. We analyze and compare the payoffs of honest and deviating miners in a sequential decision model, and identify a deviation threshold $G_t$ at which honest mining ceases to be privately optimal. Around the 2024 Bitcoin halving, we show that current mining behavior does not exhibit large-scale or structural deviation. However, when the block reward is removed, the $G_t$ criterion implies that deviation can arise even with a very small fraction of transaction fees. Finally, we evaluate three protocol-level mechanisms: Base Fee, Fee Floor, and an adaptive maximum block size rule, and show that their...
论文介绍 本文关注比特币区块奖励最终降至零后，网络仅依赖交易费的安全性问题。研究通过建立序列决策模型，分析了诚实矿工与偏离矿工的收益，识别出一个偏离阈值。分析表明，在当前区块奖励下，大规模偏离行为尚未出现。但当区块奖励消失后，即使交易费比例很小，也可能引发偏离。论文最后评估了基础费、费用下限和自适应区块大小上限三种协议级缓解机制。
第一作者: Andrew Hamara · 方向: 系统安全
操作系统加固多智能体大语言模型迭代修复
Security misconfigurations remain a leading cause of OS-level compromise, and manually keeping systems compliant with standards like Defense Information Systems Agency (DISA) Security Technical Implementation Guides (STIGs) is a tedious and expensive process. Existing compliance automation tools can reduce some of this burden, but they depend on static, pre-written corrective actions. In this paper, we introduce SHIELDS, a multi-agent system that uses large language models (LLMs) to approach OS hardening as an iterative, feedback-driven process. Instead of applying fixed remediations, SHIELDS continuously proposes fixes and refines them based on feedback from target system execution and validation scans. We evaluate the system across multiple virtual machine configurations using six contemporary LLMs ranging from 20B to 400B parameters, and find that SHIELDS successfully remediates up...
论文介绍 安全配置错误是操作系统被攻破的主要原因之一，手动修复过程繁琐。本文提出 SHIELDS，一个利用大语言模型的多智能体系统，将操作系统加固视为一个迭代的、反馈驱动的过程。与传统工具应用固定修复不同，SHIELDS 能持续提出修复建议，并根据目标系统的执行反馈和验证扫描结果进行优化。评估表明，该系统能使用不同的LLM成功修复安全配置问题，展示了自动化合规的潜力。
第一作者: Alexander Hepp · 方向: 系统安全
硬件安全逆向工程脆弱性量化供应链安全
Abstract:The safety, security, and reliability of microelectronic systems depend on a trustworthy, secured supply chain and design flow. Globally distributed supply chains or unintentional design weaknesses leave the door open for attacks on the hardware level. These scenarios encompass counterfeiting, hardware trojans, or on-device attacks. For these, hardware reverse engineering (RE) results play a pivotal role. The ongoing publication of new RE-involved attacks motivated the development of the common RE scoring system (CRESS). The system enables a general classification of RE-involved scenarios for a common, consistent rating. In this work, the originally qualitative system is extended to a quantitative system. We performed an extensive interview study with experts in the field. The interview results allowed us to derive weights that measure the severity of different RE-involved...
论文介绍 微电子系统的安全依赖于可信的供应链，但全球分布的供应链或设计弱点可能引发硬件层面的攻击，如假冒、硬件木马等。硬件逆向工程在此类场景中至关重要。为系统评估相关风险，研究团队开发了通用逆向工程评分系统 CRESS。本文通过专家访谈研究，将原本定性的系统扩展为定量系统，通过推导不同攻击场景的权重来衡量其严重程度，从而为硬件安全风险评估提供了一套可量化的方法。
第一作者: Dimitrios Stavrakakis · 方向: 软件安全
键值存储GDPR合规可信中间件机密虚拟机声明式策略语言
Abstract:Privacy regulations such as the General Data Protection Regulation (GDPR) impose strict requirements on how personal data is stored, processed, and audited. While key-value stores (KVS) are widely used in latency-sensitive applications, their simple data model and untrusted cloud deployment environments make GDPR compliance particularly challenging. Existing approaches require invasive code modifications, impose high performance overheads, or overlook the integrity of compliance mechanisms themselves. This paper presents GDPRuler, a trusted middleware system that enables verifiable GDPR compliance for KVS on untrusted clouds without modifying their codebase. GDPRuler deploys a trusted GDPR monitor inside a Confidential Virtual Machine (CVM), which enforces GDPR policies, manages compliance metadata, and maintains tamper-evident audit logs. A declarative policy language...
论文介绍 本文研究在不可信云环境中键值存储（KVS）的GDPR合规性挑战。现有方法需要侵入式代码修改、带来高性能开销或忽视合规机制本身的完整性。研究提出了GDPRuler，一个可信中间件系统。该系统在机密虚拟机内部署了一个可信的GDPR监控器，用于强制执行策略、管理合规元数据并维护防篡改的审计日志，从而在不修改存储代码库的前提下实现可验证的合规性。
第一作者: Massimo Bartoletti · 方向: AI 安全
去中心化金融经济安全可组合性最大可提取价值形式化方法
Abstract:Decentralized Finance (DeFi) services are usually constructed by composing a variety of smart contracts. While composability is a key driver of the success of DeFi, it also creates security risks: adversaries may exploit interactions between newly deployed contracts and the pre-existing ones to inflict economic losses. We introduce MEV non-interference, a formal security notion for DeFi composability requiring that the maximal extractable value from a set of newly deployed contracts is not increased by interactions with the existing blockchain state. To support this notion, we define local MEV, a novel measure of economic attacks that focusses on the loss of a given set of victim contracts. We study two adversarial models, with bounded and unbounded wealth, and establish sufficient conditions and locality principles that enable modular reasoning about secure composability. We...
论文介绍 本文关注去中心化金融（DeFi）中智能合约组合带来的经济安全风险。作者引入了“最大可提取价值不干扰”的形式化安全概念，要求新部署合约组的可提取价值不因与现有区块链状态的交互而增加。为支撑此概念，提出了“局部最大可提取价值”这一新度量标准。研究针对有界和无界财富两种对抗模型，建立了安全组合的充分条件和局部性原则，以支持模块化的安全推理。
第一作者: Cristina Carleo · 方向: 软件安全
代码大语言模型安全对齐权重编辑漏洞生成SQL注入
Abstract:Producing a labeled vulnerable code at scale is a recurring obstacle for learning-based vulnerability detection: mined corpora carry substantial label noise, and existing LLM-based augmentation propagates these inaccuracies because it transforms vulnerable seeds rather than synthesising vulnerabilities from a specification. A complementary route is to start from safe code and ask an instruction-tuned LLM to inject a specified CWE (which would shift the labeling burden from open-ended detection to bounded binary confirmation) but safety-aligned code LLMs systematically refuse such prompts. This paper is a preliminary feasibility study of abliteration, a low-rank weight edit that orthogonally projects out the refusal direction in the residual stream, as a tool to remove this barrier. We use Python and CWE-89 (SQL injection) as a case study, evaluating the Qwen2.5-Coder-Instruct...
论文介绍 本文初步探索如何利用“消融”技术解决代码大语言模型（LLM）因安全对齐而拒绝生成漏洞代码的问题。此问题阻碍了利用指令微调LLM从规范合成漏洞以生成训练数据。作者提出了一种低秩权重编辑方法，旨在正交地投射出残差流中的拒绝方向。以Python和SQL注入漏洞为例，研究评估了该技术在移除模型拒绝行为后，对指定漏洞注入的可行性。
第一作者: Alexandre Cristovão Maiorano · 方向: 软件安全
攻击模拟SIEM规则检测即代码Sigma规则自动化合成
Abstract:Security teams routinely simulate attacks against their own systems to check whether their monitoring would catch a real intruder. These Breach-and-Attack-Simulation (BAS) tools surface findings, but the security information and event management (SIEM) systems that watch production need detection rules -- and today a human bridges that gap by hand, reading each finding and writing the corresponding Sigma rule (a vendor-neutral detection format). We show this translation can be partially automated when probes are drawn from a locked corpus, so each finding carries a stable identifier back to the originating probe. We describe a deterministic synthesis function that maps each finding to a starter Sigma rule through a small template library (N=23, indexed by categories from the OWASP LLM and Web Top 10), with a back-reference to the originating finding and its MITRE ATT&CK...
论文介绍 本文旨在解决安全团队手动将攻击模拟（BAS）发现转换为安全信息和事件管理（SIEM）检测规则的低效问题。研究提出，当BAS探测来源于一个锁定的语料库时，可以实现部分自动化。每个发现都携带一个稳定标识符，可追溯至原始探测。文中描述了一个确定性合成函数，通过一个小型模板库，将每个发现映射为一条包含来源引用和MITRE ATT&CK映射的Sigma规则起始模板。
第一作者: Yongjie Wang · 方向: AI 安全
深度研究智能体基准评估搜索时污染性能膨胀基准泄露
Abstract:Public benchmarks enable fair and reproducible evaluation of LLM reasoning, but they become fragile for deep research agents that actively search the web during inference. Such agents may retrieve public benchmark metadata, question context, or even ground-truth answers via web search. This gives rise to Search-Time Contamination (STC), where external retrieval bypasses intended reasoning and inflates measured performance. We systematically study STC in deep research agent evaluation. We define three contamination types with increasing severity, namely Benchmark Metadata Leakage, Question-Context Leakage, and Explicit Answer Leakage, and develop detection algorithms to identify them and quantify their impact on agent performance. Evaluating modern deep research agents on six public benchmarks, we find that STC is widespread and can inflate performance by up to 4%. Our findings...
论文介绍 本文系统研究了在公共基准上评估具备网络搜索能力的深度研究智能体时可能发生的“搜索时污染”问题。智能体在推理过程中可能检索到基准的元数据、问题上下文甚至真实答案，从而绕过预期推理过程，虚增评估性能。研究定义了三种严重程度递增的污染类型，并开发了相应的检测算法。评估发现，这种污染现象普遍存在，可能导致性能膨胀高达4%。
第一作者: Nicholas Saban · 方向: 系统安全
计算机使用智能体提示注入安全评估领域条件红队测试
Recent computer-using-agent (CUA) red-teaming papers report prompt-injection attack success rates (ASR) of 42-98%, but these headline numbers cluster on retired models and on the most-vulnerable model in each paper's panel. We ask whether those techniques, reproduced as hand-crafted templates, still work against current frontier CUAs. We release CUA-HandCrafted, a public benchmark of 793 episodes spanning 24 multi-step web tasks, 56 attack templates, 8 attack families, and 4 system-prompt configurations. Against Claude Sonnet 4.6 and GPT-5.4 we measure 0/140 multi-step attack success (Clopper-Pearson 95% upper bound 2.60%); a prompt ablation shows this resistance lives in the model weights. Yet it does not generalize: on a sister coding-agent benchmark (SkillBench), the same weights fall to hand-crafted skill-injection at up to 100%. We argue that the literature's high ASR is largely...
论文介绍 本文重新评估了近期计算机使用智能体（CUA）红队测试报告中高企的提示注入攻击成功率。作者构建了一个包含793个实例、涵盖多种任务与攻击模板的基准，并在最新前沿模型上进行测试。结果显示，这些手工制作的攻击模板在浏览任务中完全失败，表明模型权重内置了强大的抵抗力。然而，这种抵抗力不具备领域泛化性，在编码任务中，相同的模型仍易受技能注入攻击。
第一作者: Yifan Liao · 方向: AI 安全
自动语音识别对抗攻击特征声码器可迁移性声学音素表示
Abstract:Automatic speech recognition (ASR) systems have become widely used for multilingual speech-to-text transcription. Their robustness to adversarial attacks has become an important topic for the community. Existing adversarial attacks directly add adversarial noise to the speech audio. However, prior work has shown that existing adversarial attacks face two limitations: they often transfer poorly to black-box ASR systems and are increasingly mitigated by defenses tailored to input-space perturbations. In this work, we propose a Clean-Referenced Feature-Vocoder Attack, a surrogate-based black-box attack that moves the adversarial search space from raw waveforms to self-supervised learning (SSL) representations. To address the transferability limitation, we perturb more generalizable acoustic-phonetic representations rather than low-level waveform samples, reducing dependence on...
论文介绍 本文针对自动语音识别（ASR）系统的对抗攻击鲁棒性问题，提出了一种新的攻击方法。现有攻击直接向音频波形添加扰动，存在对黑盒系统迁移性差、易被输入空间防御缓解的局限。研究提出的“干净参考特征声码器攻击”是一种基于代理的黑盒攻击，将对抗搜索空间从原始波形转移到自监督学习表示上，通过扰动更具泛化性的声学音素表示来提升攻击的可迁移性。
第一作者: Ting Hou · 方向: 隐私保护
差分隐私多目标优化子模函数基数约束近似算法
In this paper, we study multi-objective submodular maximization (MOSM) subject to a cardinality constraint under differential privacy (DP). Specifically, we aim to select a set of at most $k \in \mathbb{Z}_{+}$ elements to maximize the minimum of $d > 1$ monotone submodular functions while satisfying $\varepsilon$-DP. Although extensive studies have been conducted on both differentially private single-objective submodular maximization on sensitive data and non-private MOSM, to the best of our knowledge, there has not yet been any prior work on MOSM with DP. We propose two novel algorithms: the first extends the classic greedy algorithm and the second employs a truncation technique, both of which are integrated with DP mechanisms for privacy protection and achieve approximation guarantees for MOSM. Finally, we conduct numerical experiments on two submodular maximization applications...
论文介绍 本文研究在差分隐私约束下的多目标子模最大化问题。目标是选择至多k个元素，以同时最大化d个单调子模函数的最小值，并满足ε-差分隐私。尽管差分隐私单目标子模最大化和非隐私多目标子模最大化已有广泛研究，但本问题是首次提出。作者提出了两种新算法，分别扩展了经典贪心算法并采用了截断技术，两者均集成了隐私保护机制，并为问题提供了近似保证。
第一作者: Paulo Ricardo Ferreira Neves · 方向: AI 安全
提示注入检测越狱攻击集成学习浅层神经网络AI安全
Abstract:Large Language Models (LLMs) have transformed natural language processing, but they remain vulnerable to Prompt Injection (PI) and Jailbreak (JB) attacks. In addition, benchmark evaluations may be affected by contamination and partial information leakage, compromising performance estimates. This work presents GuardNet, a guardrail system based on an ensemble of shallow neural networks (BiLSTMs) with approximately 47 million parameters. We investigate the hypothesis that robustness in adversarial scenarios depends more on the diversity of example coverage and threshold calibration than on model scale. The results indicate that GuardNet achieves competitive performance compared with lightweight detectors and high efficiency at low latency, although larger LLMs such as Mistral-7B and Llama-3.1-8B still achieve superior performance in terms of F1 score and AUROC on the blind...
论文介绍 本文针对大型语言模型（LLM）易受提示注入（PI）和越狱（JB）攻击的问题，提出了GuardNet防护系统。该系统基于浅层神经网络（BiLSTMs）集成，拥有约4700万参数，通过增加示例覆盖多样性和优化阈值校准来提升对抗鲁棒性。GuardNet在保持低延迟高效率的同时，与轻量级检测器相比表现出竞争力，适用于LLM的安全防护场景。
第一作者: James Bartusek · 方向: 密码学协议
量子计算验证密码学结构非交换测试量子比特经典验证
Abstract:Classically testing for the presence of anti-commuting operators on a quantum device is a critical tool underpinning recent progress in classical verification of quantum computation. While such tests can be based on cryptographic assumptions, known constructions rely on highly structured assumptions, e.g. trapdoor claw-free functions. In this work, we seek to explain this state of affairs by constructing strong cryptography from (certain forms of) classical tests of anti-commutation. In particular, we formulate the notion of a test of non-commutation (ToNC), an interactive protocol between a quantum prover and classical verifier in which the prover's final-round response is obtained by measuring one of two binary observables $P_0,P_1$ depending on the verifier's challenge bit $c$. We prove that, for a broad range of parameters, ToNC implies classical-communication key...
论文介绍 本文探讨验证量子比特所需密码学结构，提出非交换测试（ToNC）协议。该协议是量子证明者和经典验证者之间的交互协议，证明在特定参数下ToNC蕴含经典通信密钥。这项工作解释了现有量子验证构造依赖高结构假设的原因，为量子计算的经典验证提供了新的密码学视角。
第一作者: Naima Tasnim · 方向: AI 安全
差分隐私自适应裁剪动量优化隐私保护机器学习梯度下降
Abstract:Differentially private stochastic gradient descent (DP-SGD) has become the standard framework for privacy-preserving machine learning, yet its reliance on a fixed gradient clipping threshold to limit sensitivity remains a significant practical limitation. Adaptive clipping algorithms such as AdaClip shift and scale the gradient prior to clipping and adding noise so that the clipped gradient yields a more informative descent direction. The shift and scaling parameters are selected adaptively based on the empirical mean and variance. However, in existing adaptive clipping algorithms, these empirical estimates have not been also used for momentum to accelerate training itself. On the other hand, DP-Adam is an algorithm that exploits Adam-like momentum updates based on the gradient mean and variance to accelerate training, but does not exploit these estimates for adaptive...
论文介绍 本文针对差分隐私随机梯度下降（DP-SGD）中固定梯度裁剪阈值的局限性，提出DP-MacAdam机制。该方法结合自适应裁剪和自适应动量，利用梯度均值和方差自适应调整裁剪阈值并加速训练。DP-MacAdam旨在改进隐私保护机器学习的性能，通过更智能的梯度处理提升优化效率。
第一作者: Ziyang Yu · 方向: 导航与运动 · 来源: cs.RO
最远点采样点云处理球形体素剪枝CPU/GPU加速机器人导航
Point clouds are a primary sensory representation for robotic perception, underpinning LiDAR-based autonomous driving, simultaneous localization and mapping (SLAM), and navigation. Within these pipelines, Farthest Point Sampling (FPS) is the most well-known downsampling operator, as its uniform coverage preserves the geometric structure on which downstream perception relies. However, the large time complexity of classical FPS scales poorly with the million-point-per-second rates of modern 3D sensors, making it a dominant latency bottleneck that conflicts with the real-time and limited onboard compute budgets of robotic systems. Therefore, we propose RadiusFPS, an FPS acceleration framework based on spherical voxel pruning that preserves the standard FPS update rule under the same initialization and tie-breaking policy. By indexing the point cloud with spherical voxels, RadiusFPS...
论文介绍 本文解决点云下采样中最远点采样（FPS）算法的计算效率问题。RadiusFPS通过球形体素剪枝技术加速FPS，适用于CPU和GPU平台，保持与标准FPS相同的初始化策略。该方法显著降低时间复杂度，适用于自动驾驶、SLAM等需要实时点云处理的机器人系统。
第一作者: Qize Yu · 方向: VLA 通用模型 · 来源: cs.RO
视觉-语言-动作模型可供性感知机器人操作指令跟随中间表示
Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robotic manipulation. However, the structural mismatch between VLM semantic spaces and embodied control policies often hinders the learning of precise perception--action mappings. To address this challenge, we propose \textbf{AffordanceVLA}, a unified framework that introduces structured affordance forecasting as a task-oriented intermediate representation to establish a more precise and robust perception--action mapping. Specifically, we progressively model manipulation priors through three complementary components: 1) \textbf{Which2Act} for object-centric grounding via visual latent prediction to suppress distractions; 2) \textbf{Where2Act} for 2D interaction localization via affordance map estimation; and 3) \textbf{How2Act} for 3D...
论文介绍 本文提出AffordanceVLA，一种视觉-语言-动作模型，通过可供性感知理解增强动作生成。针对VLA中语义与控制策略的不匹配问题，该模型引入结构化可供性预测作为中间表示，分三个阶段建模操作先验：对象接地、交互定位和动作生成。AffordanceVLA旨在改善指令跟随机器人操作的精度和适应性。
第一作者: Shengtao Zheng · 方向: VLA 通用模型 · 来源: cs.AI
世界模型视觉-语言-动作模型无人机导航城市环境未来状态预测
End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict actions, often struggling in dense urban environments where severe occlusions and sharp turns result in drastic viewpoint transitions. We argue that the ability to "imagine" future states -- inherent in World Models -- is critical for robust decision-making under such partial observability. To address this, we construct a challenging Urban Canyon Traversal Benchmark, specifically designed to evaluate spatial understanding in scenarios characterized by severe occlusions and drastic viewpoint transitions. To this end, we propose WorldFly, a novel world-model-based VLA framework that employs a dual-branch coupled flow matching mechanism to jointly generate future video predictions and navigation actions, thereby...
论文介绍 本文针对无人机导航中现有VLA模型在遮挡和急转场景下的不足，提出WorldFly。该框架引入世界模型，通过双分支流匹配机制同时生成未来视频预测和导航动作。为评估性能，构建了Urban Canyon Traversal Benchmark。WorldFly旨在通过「想象」未来状态来增强部分可观测环境下的决策能力。
第一作者: Runfa Blark Li · 方向: 机器人操作 · 来源: cs.RO
双手灵巧操作未来状态预测分层系统机器人工具使用视觉运动控制
Bimanual dexterous tool use remains challenging for robots due to high-dimensional hand configurations and complex hand-tool-object dynamics and contact. Most existing control policies depend on future configuration references provided from demonstrations, while future action-conditioned world models require slow online planning over high-dimensional action sequences. A significant challenge is generating a dynamically consistent future reference trajectory without relying on privileged states from demonstrations or slow counterfactual planning. We propose DexFuture, a hierarchical system that couples a high-level Future-State Visuomotor Target Predictor with a low-level Target-Conditioned Structured Dexterous Policy. Conditioned on egocentric RGB, proprioceptive and geometric history, the high-level predictor constructs structured hand-tool-object visuomotor embeddings and uses a...
论文介绍 本文解决双手灵巧工具使用中未来参考轨迹生成的难题。DexFuture采用分层结构：高层预测器从自我中心视觉和本体感觉历史构建未来状态目标，低层策略基于目标执行操作。该系统避免了对示范特权状态的依赖和慢速在线规划，适用于复杂双手工具任务。
第一作者: Yunhao Yang · 方向: 具身智能 · 来源: cs.RO
形式化验证技能自进化机器人技能语义契约具身智能体
Reusable robot skills are becoming the basic units through which embodied agents turn open-ended instructions into long-horizon physical behavior. We argue that, while foundation models have collapsed the cost of creating these skills, the cost of trusting them has not. Existing skill-evolution loops refine skills through execution feedback, unit tests, environment reward, or LLM self-critique, but these signals provide only trace-level evidence: they show that a skill worked on sampled executions, not that skill-induced plans satisfy temporal safety contracts under untested conditions. We introduce VASO, a framework for verification-guided self-evolution of LLM-generated robot skill contracts. In VASO, each skill is represented as a semantic contract with two coupled interfaces: a formal interface that aligns robot states, observations, and control commands with logical propositions...
论文介绍 本文针对具身智能体中LLM生成机器人技能的信任问题，提出VASO框架。该框架将技能定义为语义契约，包含形式化接口和可执行接口，通过模型检查验证时间安全性质。VASO实现了验证指导的技能自进化，确保技能在未测试条件下满足安全契约。
第一作者: Lizhi Yang · 方向: 机器人操作 · 来源: cs.RO
人形机器人全身控制策略蒸馏任务空间接口专家混合
Abstract:For a humanoid robot to be deployed in the real world, the choice of command space (i.e., the interface between task planning and whole-body control) is crucial. Existing whole-body controllers typically demand dense kinematic or spatial references that planners struggle to synthesize from task semantics. We instead propose a compact, explicit interface that is intuitive, general, modular, and expressive enough for diverse manipulation skills. To this end, we introduce HANDOFF, a single humanoid whole-body controller that follows this interface and is distilled via multi-teacher KL distillation under a context-conditioned gating scheme into a mixture-of-experts student from three complementary specialists: whole-body motion tracking with safety-filtered data, locomotion, and fall-recovery. On the Unitree G1, HANDOFF matches state-of-the-art velocity tracking and offers one of...
论文介绍 本文针对人形机器人部署中任务规划与全身控制接口不清晰的问题，提出了一种紧凑、直观且模块化的任务空间接口。为此，研究者设计了HANDOFF控制器，它通过多教师知识蒸馏和上下文条件门控机制，将来自运动跟踪、行走和防摔恢复三个专家的知识整合到一个学生模型中。该方法在Unitree G1机器人上实现了接近先进水平的性能，并展示了其在复杂操作任务中的应用潜力。
第一作者: Dong Jing · 方向: VLA 通用模型 · 来源: cs.RO
视觉语言动作模型速度可控策略优化机器人操作模仿学习
Abstract:Robot manipulation alternates between low-risk transit phases that call for fast execution and high-risk contact stages that demand slow, precise motion. Yet existing Vision-Language-Action models (VLAs) only inherit a single fixed speed from training demonstrations. Prior efforts to accelerate VLAs through model compression, KV-cache reuse, or reinforcement learning only shift the policy from one fixed speed to another, and leave deceleration almost unexplored. We observe that the magnitude of each predicted action already governs how fast the robot moves, opening a direct route to controllable execution speed. We turn this observation into TempoVLA, a single VLA whose execution speed is controlled by an explicit condition. TempoVLA combines two coupled components. (1) A data-side Variable-Speed Trajectory Augmentation (VSTA) that re-times demonstration to any target speed by...
论文介绍 现有视觉语言动作模型的执行速度单一且固定，无法根据任务阶段的风险高低进行自适应调整。本文提出TempoVLA，其核心思想是通过显式条件来控制模型输出的动作幅度，从而实现执行速度的动态调节。该方法结合了数据层面的可变轨迹增强和模型层面的运动提示编码，在不牺牲精度的前提下，允许机器人在快速移动与精细操作之间灵活切换，提升了操作效率与安全性。
第一作者: Luzhe Sun · 方向: 数据集与评测 · 来源: cs.RO
策略适配流模型动作校正预训练策略分布偏移
Abstract:Leveraging prior knowledge from pretrained policies, foundation models, or human operators offers an efficient alternative to learning robot skills from scratch. However, these agents often provide actions that are suboptimal, noisy, or misaligned with task-specific expert behavior. We propose GLOVES, a family of flow-based adaptation methods that correct non-expert actions by transporting them toward an expert action distribution. Rather than replacing agentic control with full autonomy, GLOVES performs selective action-level adaptation, improving task success while preserving agent intent. The learned flow also provides a natural in-distribution scoring mechanism through reverse flow evaluation. We use this signal as an intervention gate: actions that appear consistent with the expert distribution are passed through unchanged, while anomalous or out-of-distribution (OOD)...
论文介绍 针对预训练策略、基础模型或人类操作员提供的动作可能次优或有噪声的问题，本文提出GLOVES系列方法。该方法利用基于流的模型，将非专家的动作向专家动作分布进行运输校正，而非完全替换原有策略。GLOVES通过选择性动作级适配来提升任务成功率，同时保留代理意图，并利用反向流评估作为分布内评分机制来过滤异常动作，实现了高效且可控的策略适配。
第一作者: Robert Ramirez Sanchez · 方向: 机器人操作 · 来源: cs.RO
策略学习加速执行轨迹分割视觉语言模仿学习
Abstract:Humans often take longer to demonstrate a task than a robot would need to execute it. Rather than learning to replicate the demonstration at the same pace, many industrial and practical applications require robots to perform tasks as quickly as possible. In this paper, we investigate several hypotheses for learning policies that operate faster-than-demonstrations. Our experiments show that the most effective strategy is to downsample recorded demonstrations and train the robot's policy on this accelerated data. However, uniformly downsampling an entire trajectory can be problematic. Some parts of a task can be safely sped up (e.g., unconstrained motion), while others demand slower, more precise motion (e.g., object interactions or fine manipulation). To address this challenge, we introduce VOLT, a vision-and-language trajectory segmentation method that reasons over video...
论文介绍 人类演示往往比机器人最优执行更慢。本文研究了如何从演示中学习执行更快的策略，发现对演示轨迹进行均匀下采样并训练是有效方法。为了解决全程均匀加速可能带来的问题，研究者提出了VOLT方法，它利用视觉和语言信息来识别轨迹中可安全加速的段落（如自由移动）与需要保持精度的段落（如精细操作），从而实现分段自适应的加速策略学习。
第一作者: Mason Peterson · 方向: 具身智能 · 来源: cs.RO
机器人定位跨视角地理定位语义原语非城市环境GNSS拒止
Abstract:Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in GNSS-denied environments remains an open problem. Overhead aerial imagery offers a promising solution, but existing approaches primarily target structured urban environments and have been rarely demonstrated in unstructured natural terrain. Limitations of the state-of-the-art include a reliance on models trained for specific environments, as well as difficulty handling repetitive geometries and featureless landscapes commonly found in natural outdoor areas. To overcome these challenges, we present Meridian, a method for matching high-level metric-semantic primitives across aerial images and ground robot RGB-D camera data that achieves accurate global localization and generalizes well across diverse...
论文介绍 在GNSS信号拒止环境中，可靠的全局定位至关重要。现有基于俯视航拍图像的方法多局限于结构化城市环境。本文提出Meridian方法，旨在解决非结构化自然地形下的定位难题。该方法通过匹配地面机器人RGB-D数据与航拍图像中的高层级度量-语义原语，实现了准确的全局定位，并对重复几何结构和无纹理景观具有良好的泛化能力，适用于多样化的户外环境。
第一作者: Yongqiang Yu · 方向: 导航与运动 · 来源: cs.RO
惯性传感加速度计校准线性最小二乘姿态辅助MEMS传感器
Abstract:Triaxial MEMS accelerometers are widely used for inertial sensing, navigation, and sensor fusion, but existing calibration methods often rely on costly reference setups or nonlinear iterative optimization, limiting their efficiency and applicability to low-cost or self-calibrating systems. We present attitude-aided linear accelerometer calibration (ALAC), a method that operates on any platform providing orientation information, such as turntables, robotic arms, or inertial measurement units. ALAC constructs a combined error matrix (CEM) to represent sensor errors in a unified calibration model and enables linear least-squares estimation. The bias and gravity vector are jointly estimated, implicitly accounting for platform misalignment, and matrix decomposition of the CEM recovers scale, non-orthogonality, and alignment rotation parameters. Under static gravity, calibration is...
论文介绍 三轴MEMS加速度计的校准常依赖昂贵的参考设备或非线性优化，效率较低。本文提出姿态辅助的线性加速度计校准方法ALAC，该方法能在任何提供姿态信息的平台（如转台、机械臂）上运行。ALAC构建了一个统一误差模型，通过线性最小二乘法联合估计偏置和重力向量，并能从组合误差矩阵中分解出刻度因子、非正交性等参数，实现了高效且低成本的加速度计校准。
第一作者: Rickmer Krohn · 方向: 机器人操作 · 来源: cs.RO
触觉感知模仿学习多传感器融合接触丰富操作触觉表征
Abstract:Touch sensing is beneficial for solving a wide variety of manipulation tasks. While there exists a wide range of tactile sensors with different properties, exploiting the fusion of multiple heterogeneous tactile sensors to improve manipulation learning remains underexplored. We present Multi-Resolution Tactile Sensing (MiTaS), a representation framework that leverages multiple tactile sensors operating at different temporal resolutions in order to solve complex contact-rich manipulation tasks. We propose a novel architecture using modality-specific convolutional stems and transformer-based fusion that effectively fuses information from an RGB camera stream, a vision-based GelSight Mini sensor and a high-frequency event-based Evetac sensor. This multi-sensor representation then conditions a flow-matching policy for solving downstream tasks. Experimental results across five...
论文介绍 触觉信息对解决接触丰富的操作任务至关重要，但融合多种异构触觉传感器以提升学习效果的研究尚不充分。本文提出了MiTaS表征框架，它利用多个以不同时间分辨率工作的触觉传感器（包括视觉式和事件式），通过特定模态的卷积茎和基于Transformer的融合架构，有效融合了RGB视觉与多源触觉信息。该表征随后用于引导流匹配策略，在多项复杂操作任务上取得了良好效果。
第一作者: Boyang Zhang · 方向: VLA 通用模型 · 来源: cs.RO
视觉语言动作模型潜在推理奖励引导多路径测试时扩展
Abstract:Vision-Language-Action (VLA) policies remain brittle in long-horizon and high-uncertainty control, where one-pass action decoding provides limited inference-time deliberation. Explicit chain-of-thought can increase reasoning depth, but introduces token latency and an indirect text-to-action interface. We propose MPCoT, a reward-guided multi-path latent reasoning framework that initializes $M$ hypotheses, refines them for K weight-tied steps, and softly aggregates them before action decoding. A training-only path-preference objective evaluates candidate action branches with expert-action consistency, world-model/VLM-based progress, and success feedback to align the latent path scorer with downstream execution quality. MPCoT preserves the original 8-step action interface, generates zero reasoning tokens, and exposes configurable inference controls (K,M). Under matched protocols...
论文介绍 视觉语言动作模型在长时序、高不确定性控制任务中表现脆弱，其一次性动作解码缺乏推理时的深思熟虑。本文提出MPCoT框架，它通过在潜在空间初始化多个假设并进行多步精炼，然后软聚合后再进行动作解码，实现了无文本推理的深度思考。该框架结合专家一致性、世界模型进展和成功反馈来训练路径偏好评分器，可在不产生额外推理token的情况下，通过配置推理步骤和路径数来扩展模型能力。
第一作者: Dongwon Son · 方向: 机器人操作 · 来源: cs.RO
机器人操作扭矩适应运动控制仿真到现实迁移鲁棒性
Abstract:A policy tuned for one robot often behaves differently on another, whether due to the sim-to-real gap, unknown payloads, or the differing dynamics of two instances of the same robot. In contact-rich, dynamic manipulation, even small motion discrepancies can result in failure to track reference motion, since they disrupt the timing and modes of contact. Common remedies, such as domain randomization or system identification, either produce overly conservative task policies or require data that must be recollected for each robot or payload. We introduce the Torque Adaptation Module (TAM), a learned module that adapts the torque commands sent to the robot to match the behavior of an ideal robot. TAM operates between the low-level controller that tracks the policy's actions and the robot's torque interface. It includes a history encoder that embeds proprioceptive history into a...
论文介绍 本文针对机器人策略在不同实例间迁移时因动力学差异导致运动跟踪失败的问题，提出了一种扭矩自适应模块。该模块作为一种学习组件，被置于底层控制器与机器人扭矩接口之间，通过编码本体感觉历史来实时修正发送给机器人的扭矩指令，使其行为更接近理想模型，从而增强在接触密集的动态操作任务中的鲁棒性。
第一作者: Xingyao Lin · 方向: 机器人操作 · 来源: cs.RO
第一人称视频主动感知机器人操作视觉-语言模型预训练
Abstract:Egocentric human video offers a scalable alternative to robot data for pretraining, yet models pretrained on such video consistently underperform those pretrained on robot data. We attribute this gap to a missing signal, the active perception behavior in egocentric videos, where humans continuously reposition their viewpoint during manipulation, inducing camera motion that standard pipelines treat as noise. To address this, we present ActiveMimic, a pretraining framework that recovers synchronized camera and wrist trajectories from a single body-worn RGB camera, models camera motion as a viewpoint action, and jointly learns active perception and manipulation from in-the-wild egocentric human video before adapting to a target robot. Empirically, real-world experiments across tasks with diverse active perception demands show that ActiveMimic consistently surpasses baselines...
论文介绍 本文提出ActiveMimic框架，旨在利用大量的人类第一人称视频为机器人操作进行预训练。该框架的核心在于从视频中恢复出同步的相机与手腕轨迹，并将相机运动建模为主动感知中的视角动作，从而联合学习主动感知与操作技能。实验表明，该方法能有效桥接人与机器人之间的数据差异，提升在多样主动感知需求任务上的表现。
第一作者: Youssef Attia · 方向: 导航与运动 · 来源: cs.RO
水下机器人3D声纳物理仿真模块化架构GPU加速
Abstract:As underwater robotics research increasingly addresses complex 3D perception and autonomous navigation, the fidelity of sonar simulation has become a key factor in algorithm development. Current simulation frameworks typically rely on geometry-driven rendering, approximating 3D sonar as an underwater equivalent to LiDAR, which fails to account for fundamental acoustic phenomena such as refraction, multi-path interference, and phase-dependent signal formation. This paper proposes a modular architecture for realistic 3D sonar simulation that integrates GPU-accelerated graphics engines with physically grounded acoustic propagation principles. We implement a volumetric 3D sonar model within the NVIDIA Isaac Sim environment, modeled after the Water Linked 3D-15 sensor, and integrate it into a comprehensive underwater simulation framework. The system is validated through a...
论文介绍 随着水下机器人任务复杂化，高保真声纳仿真成为关键。本文提出一个模块化架构，用于实现逼真的3D声纳仿真。该系统在NVIDIA Isaac Sim中集成了GPU加速的图形引擎与物理驱动的声学传播原理，以模拟折射、多径干扰等真实声学现象，从而为水下自主导航算法的开发提供更可靠的仿真环境。
第一作者: Arash Ghasemzadeh Kakroudi · 方向: 机器人操作 · 来源: cs.RO
人机协作生成式AI分布式系统视觉-语言模型ROS 2
Abstract:This paper presents a distributed conversational framework for human-robot collaborative manipulation that integrates local language and vision-language models (VLMs) with a Robot Operating System 2 (ROS 2)-based execution stack. Language understanding, visual grounding, orchestration, and motion execution run as separate ROS 2 nodes, enabling flexible deployment across distributed hardware while maintaining a responsive control loop. From free-form user commands, the system generates structured action requests for pick, place, and handover. It uses a VLM to return image-space targets, which are converted into metric robot-frame goals using depth and calibration. A web dashboard exposes intermediate intent and grounding overlays (pixel, depth, and robot-frame) and requires explicit operator confirmation before any motion is executed. Experiments on a Franka FR3 platform...
论文介绍 本文提出一个用于人机协作操作的分布式对话框架。该系统整合了本地的语言与视觉-语言模型，并在ROS 2架构下将语言理解、视觉定位、流程编排和运动执行分离为独立节点。通过自然语言指令，系统能生成结构化的抓取、放置等动作请求，并利用视觉-语言模型返回图像空间目标，最终转换为机器人的物理坐标执行。
第一作者: Liwen Zhang · 方向: 机器人操作 · 来源: cs.RO
脉冲神经网络扩散策略微重力机器人操作强化学习
Abstract:Intra-vehicular robots in spacecraft help reduce astronaut workload and improve mission efficiency. Recent research focuses on using deep learning methods to achieve the acute control required for operations in these complex environments. However, objects exhibit unpredictable, unconstrained drift without gravitational damping. These factors demand robustness against complex multimodal action distributions. Diffusion policies (DP) can model these complex actions, but their iterative sampling process consumes too much energy for the limited power budgets of spacecraft. We therefore propose a low-energy intra-vehicular robotic manipulation framework, L-SDPPO, in which the Spiking Diffusion Policy (SDP) is optimized with a reinforcement learning (RL) algorithm. Furthermore, to address the insufficient perception of dynamic spatiotemporal features in microgravity, we propose the...
论文介绍 针对航天器舱内机器人操作中物体无约束漂移带来的挑战，以及扩散策略能耗高的问题，本文提出了L-SDPPO框架。该框架采用脉冲扩散策略来建模复杂的动作分布，并利用强化学习算法对其进行优化，旨在以低能耗的方式实现鲁棒操作。同时，模型还通过时空特征感知模块来增强对微重力环境下动态特征的捕捉能力。
第一作者: Yuanzhi He · 方向: 机器人操作 · 来源: cs.RO
运动规划迁移学习样本效率交叉熵方法任务分解
Abstract:As robotic systems become more sophisticated, the growing complexity of their motion planning models and the longer training times pose substantial challenges. Evolutionary algorithms such as the Sample-efficient Cross-Entropy Method (iCEM) have recently demonstrated promising potential for low-level real-time planning by leveraging efficient knowledge reuse strategies to improve performance. Although effective in many control tasks, iCEM's performance can be constrained in more complex scenarios, particularly those requiring stacking, sliding, and shelf placement. In this work, we propose a novel iCEM+TL framework that explicitly leverages Transfer Learning (TL), where key iCEM parameters are transferred from simpler upstream tasks to guide more complex downstream tasks. Additionally, we applied Reward Redesign (RR) through task decomposition for stacking objects and shelf...
论文介绍 为解决机器人复杂任务中运动规划模型训练时间长的问题，本文提出了一种基于迁移学习的iCEM+TL框架。该框架将高效的交叉熵方法与迁移学习相结合，将从简单上游任务中学习到的关键参数迁移至复杂的下游任务，从而引导规划过程。此外，通过任务分解和奖励重塑，进一步提升了在堆叠、滑动等复杂场景中的样本效率和规划性能。
第一作者: Antonio Alvarez Valdivia · 方向: 导航与运动 · 来源: cs.RO
软体机器人藤蔓机器人尖端安装高速生长设计与基准测试
Abstract:Soft, growing vine robots extend through tip eversion, a mechanism that enables navigation through cluttered environments. However, integrating cameras and other sensors at the tip is uniquely challenging because the material forming the tip is constantly renewed as the robot grows. This continual material turnover, combined with friction between internal layers, added tip weight, and fabric constriction, complicates sensor and tool mounting. These limitations hinder the deployment of vine robots for inspection and search tasks, where rapid growth while carrying tip-mounted sensors is essential. In this work, we present a triangular roller tip mount that reduces internal resistance during growth by rolling rather than sliding against the robot body. The design was refined through iterative failure analysis, enabling, for the first time, consistent eversion on a TPU-coated...
论文介绍 藤蔓机器人通过尖端外翻生长，但在其移动尖端上稳定安装传感器极具挑战。本文设计并基准测试了一种三角滚动尖端安装件，通过滚动而非滑动的方式来减少机器人生长过程中的内部摩擦阻力。这一设计改进有助于解决尖端持续更新、层间摩擦和负重导致的性能瓶颈，从而实现高速生长并携带传感器。
第一作者: Chaoyi Xu · 方向: 机器人操作 · 来源: cs.RO
灵巧操作触觉感知遥操作可穿戴接口机器人学习
Abstract:Learning dexterous manipulation requires demonstrations that preserve fine hand-object interactions while remaining executable at deployment. Existing pipelines either lose deployable dexterity through retargeting or embodiment conversion, or rely on robot-specific teleoperation that is costly to scale and often lacks intuitive, contact-aware control for dexterous data collection. We present RealDexUMI, a wearable universal manipulation interface built around a shared dexterous end-effector module that integrates a lightweight dexterous hand, in-hand vision, and fingertip tactile sensing. A palm-side isomorphic teleoperation glove maps human finger inputs to robot-hand joint commands, enabling real-time, retargeting-free, intuitive, and precise hand control. The shared hand and sensing modules yield zero-gap end-effector data, with matched in-hand observations, tactile...
论文介绍 本文介绍了RealDexUMI，一个用于灵巧机器人学习的可穿戴通用操作接口。该接口围绕共享的灵巧末端执行器模块构建，集成了灵巧手、手内视觉和指尖触觉传感。配合掌侧等比例遥操作手套，能够实现直观、精准的、无需重定向的手部控制。共享的模块确保了末端执行器数据的零间隙，为学习接触感知的灵巧操作技能提供了高质量的演示数据。
第一作者: Yi Yang · 方向: VLA 通用模型 · 来源: cs.RO
世界建模语言推理动作合成具身基础模型自回归Transformer
Abstract:We propose world-language-action (WLA) models as a new class of embodied foundation models. WLA takes textual instructions, images, and robot states as inputs to jointly predict textual subtasks, subgoal images, and robot actions, conjoining the \emph{world modeling interface} to learn from extensive egocentric videos as in the world-action model (WAM) and the \emph{language reasoning} capacities to solve complex long-horizon tasks as in vision-language-action (VLA) models. At the core of WLA lies an \emph{autoregressive (AR)} Transformer backbone, instead of a bidirectional diffusion Transformer as in WAMs, to predict the \emph{next state}, comprising the \emph{semantic-level} textual intention and complementary \emph{fine-grained} physical dynamics. The physical dynamics are supervised by the world modeling objective based on a dedicated World Expert, and are leveraged to...
论文介绍 本文提出世界-语言-动作模型，作为一类新的具身基础模型，旨在统一世界建模、语言推理和动作合成。核心方法采用自回归Transformer骨干，预测语义级文本意图和细粒度物理动态，以解决复杂长时机器人任务，提升机器人控制能力。
第一作者: Anlan Yu · 方向: 机器人操作 · 来源: cs.RO
数据飞轮具身智能物流世界模型模仿学习
Abstract:Embodied intelligence is moving from laboratory demonstrations toward industrial deployment, with the logistics industry serving as a key application scenario. Learning-based policies offer a promising path beyond traditional perception-planning-control pipelines, but their scalability depends on how embodied data can be collected, organized, and reused. This research studies a data-centric framework for industrial embodied intelligence by constructing a logistics data flywheel. Our framework converts daily operations into reusable data assets, uses World Models to generate reliable supervision for long-tail parcel manipulation, and feeds deployment feedback back into policy improvement. As an initial result, \textit{WM-DAgger} introduces a World-Model-based data aggregation framework that synthesizes out-of-distribution recovery data for robust imitation learning. Building on...
论文介绍 本文针对物流行业具身智能部署的数据可扩展性问题，提出数据飞轮框架。该框架将日常操作转化为可重用数据资产，利用世界模型为长尾包裹操作生成可靠监督，并通过部署反馈迭代优化策略，以促进工业机器人操作的持续改进。
第一作者: Nikolai Dorofeev · 方向: 具身智能 · 来源: cs.RO
安全策略对抗性学习合成场景风险建模具身AI
Abstract:In this work, we propose an agentic gamification framework for hazard-informed learning of robot safety policies through synthetic scenarios. We model scenario generation as an adversarial game between two agents: a Red Team that explores the space of potential failures by constructing hazardous situations, and a Blue Team that incrementally refines safety policies to prevent them. This iterative process enables efficient discovery of high-risk edge cases that are unlikely to be captured through random simulation or manual enumeration. By combining classical risk modeling with adversarial scenario generation and modern learning paradigms, this work provides a scalable pathway for embedding safety into Physical AI systems operating in complex real-world environments. The paper describes ongoing work. The contribution is a problem formulation and a proposed solution architecture.
论文介绍 本文提出一个代理博弈化框架，通过对抗性合成场景学习机器人安全策略。红队构建危险场景，蓝队细化安全策略，迭代发现高风险边缘情况，为复杂环境中物理AI系统的安全嵌入提供可扩展路径。
第一作者: Siheng Zhao · 方向: 机器人操作 · 来源: cs.RO
仿人机器人爬梯子运动跟踪视觉运动策略sim-to-real
Abstract:Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to sparse footholds and handholds, complex whole-body coordination, and sensitivity to perception and control errors. We present \textbf{LadderMan}, a unified system that enables humanoid robots to robustly climb diverse ladders and perform manipulation under such constrained conditions. Our climbing policy is built on a scalable two-stage learning pipeline, where we use hybrid motion tracking to learn multiple climbing experts from a single reference motion, and distill these experts into a unified depth-based visuomotor climbing policy via hybrid imitation and reinforcement learning. To enable real-world deployment, we leverage vision foundation models to bridge the sim-to-real gap in depth perception. Building on the learned...
论文介绍 本文提出LadderMan系统，解决仿人机器人爬梯子的挑战，如稀疏落脚点和全身协调。核心方法包括两阶段学习管线：从单一参考运动学习爬梯专家，蒸馏为统一深度视觉运动策略，并利用视觉基础模型弥合sim-to-real差距。
第一作者: Adrian Piedra · 方向: 具身智能 · 来源: cs.RO
机器人超声视觉触觉力控制腹部扫描体积重建
Abstract:In this paper, we present a robotic ultrasound acquisition system that integrates stereo vision, touch-based feedback, and expert-informed strategies to perform autonomous and adaptive abdominal scans. The system records freehand motion and force data from expert radiologists, creating a framework to capture transducer motion, applied forces, and anatomical scanning strategies. This expert data is replayed to replicate characteristic scans with the robot, forming a foundation for further autonomous capabilities. Using stereo vision, the system generates three-dimensional topography maps of the patient's abdomen, which are refined through stiffness measurements at key points to delineate the rib cage boundary. These combined techniques enable the robot to execute two distinct scanning paths: an upward-angled sweep beneath the rib cage to visualize structures near the upper...
论文介绍 本文提出一个机器人超声采集系统，集成立体视觉、触觉反馈和专家策略，实现自主腹部扫描。系统记录专家数据并回放，生成三维地形图，通过刚度测量细化肋骨边界，支持两种扫描路径以可视化腹部结构。
第一作者: Chong Ma · 方向: VLA 通用模型 · 来源: cs.RO
VLA策略世界模型闭环评估分块预测策略在环
Abstract:Vision-language-action (VLA) policies operate in a closed loop in real-world robot tasks: a robot observes the scene, executes an action chunk, and conditions its next decision on the resulting observation. However, most existing world models for robot action evaluation are limited to open-loop prediction along pre-collected action trajectories. This prevents them from supporting closed-loop VLA evaluation, where each action chunk must be conditioned on the observation generated by the previous execution. To address this gap, we propose PiL-World, a chunk-wise world model designed for policy-in-the-loop VLA evaluation. Given the current observation and the action trajectory rolled out by a VLA policy, PiL-World generates multi-view future observations that are consistent with the VLA rollout and match the image inputs required by the policy. By alternating between VLA...
论文介绍 本文针对VLA策略闭环评估的差距，提出PiL-World分块世界模型。该模型给定当前观测和VLA策略动作轨迹，生成多视图未来观测，通过交替策略和世界模型实现策略在环评估，提升机器人任务评估准确性。
第一作者: Cheng Ren · 方向: 具身智能 · 来源: cs.RO
多代理拾取交付动态订单机器人仓储重规划令牌传递
Abstract:Robotic Cellular Warehousing Systems (RCWS) give rise to multi-agent pickup and delivery (MAPD) processes in which robots sequentially collect multiple stock-keeping units (SKUs) for each order. Unlike classical MAPD formulations that assume static tasks, real warehouse operations often involve dynamic order evolution, where new SKUs may be appended to an order while it is being executed. Motivated by this practical requirement, this letter formulates the Dynamic Multi-Agent Pickup and Delivery problem considering internal order evolution for the first time. Building on the token passing paradigm, we propose two event-triggered online replanning algorithms. The first, Dynamic Token Passing, performs localized replanning upon order updates through add-order decomposition and priority-based token scheduling while preserving collision-free execution. The second, Cooperative Token...
论文介绍 本文首次形式化考虑内部订单演化的动态多代理拾取交付问题，应用于机器人蜂窝仓储系统。基于令牌传递范式，提出动态令牌传递和协作令牌算法，通过事件触发重规划实现无碰撞执行，提升仓储物流自动化效率。
第一作者: Dabin Kim · 方向: 机器人操作 · 来源: cs.RO
安全具身AI长时任务机器人操作跨层分析风险积累
Abstract:Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety to the foreground, because failures in the physical world can harm people, damage objects, and disrupt workplaces. Although safe embodied AI has attracted substantial attention, the literature remains fragmented across planning, policy design, and runtime execution. Long-horizon robotic manipulation is a particularly revealing anchor domain for this problem because semantic misgrounding, subtask-level error propagation, execution drift, and contact-rich physical risk can accumulate within the same closed-loop system. This survey therefore provides a structured review of safety in long-horizon robotic manipulation from an embodied AI perspective. We organize the literature by intervention locus, covering planning-time...
论文介绍 本文综述长时机器人操作中的安全问题，从具身AI视角进行跨层分析。覆盖规划、策略设计和运行时执行，讨论语义误接地、错误传播等风险积累，为安全具身AI系统提供结构化回顾和整合框架。
第一作者: Ziyang Yao · 方向: 策略学习 · 来源: cs.RO
自动驾驶世界模型离散化策略学习因果推理
Abstract:Autonomous driving requires reasoning about how ego actions shape the evolution of the surrounding world. However, most end-to-end methods rely on direct state-to-action mappings, capturing correlations without explicitly modeling action-conditioned dynamics. Conversely, continuous-latent world models often lack compositional structure for causal reasoning across counterfactual futures. We introduce Discrete-WAM, a unified latent vision-action world policy that represents future visual states and ego actions as aligned discrete tokens, enabling compositional causal reasoning across alternative futures. Built upon this unified discrete alignment, Discrete-WAM establishes a shared discrete diffusion framework with unified generative tasks, jointly formulating world modeling, world-action policy, and hierarchical decision-enabled policy, supporting compositional generalization...
论文介绍 本文针对自动驾驶中自我动作如何影响周围世界演化的问题，提出 Discrete-WAM 统一潜在视觉-动作世界策略。该方法将未来视觉状态和自我动作表示为对齐的离散 token，通过离散扩散框架联合建模世界模型、世界动作策略和层次决策策略，支持组合泛化，以实现跨反事实未来的因果推理。
第一作者: Emre Girgin · 方向: 具身智能 · 来源: cs.RO
足式机器人里程计接触检测自监督学习关节编码器
Abstract:The estimation of odometry in legged robots depends on the assumption that the velocity of the foot with respect to the world remains zero during the stance phase. Feedback for the main body velocity is derived from the kinematic serial chain of the feet making accurate leg phase detection is a critical subproblem. A considerable number of studies employ ground reaction force sensors mounted at the tip of the foot to classify, yet these sensors may not be universally available for all legged robots. Additionally, these sensors are often unresponsive to unaccounted disturbances, such as slippage, while the foot remains in contact with the ground. In this study, we propose a self-supervised representation learning framework for contact detection that utilizes the standard sensor set of joint encoders without reliance on force sensor augmentations. We employ learned...
论文介绍 本文针对足式机器人里程计估计中接触检测依赖力传感器的问题，提出一种自监督表示学习框架。该框架利用关节编码器的标准传感器集，无需力传感器，通过学习接触表示来提高腿相检测准确性，适用于存在滑动等干扰的场景。
第一作者: Yihao Wu · 方向: VLA 通用模型 · 来源: cs.RO
视觉-语言-动作模型强化微调奖励无关偏好优化flow-matching
Abstract:Post-training Vision-Language-Action (VLA) models into policies that can be reliably deployed on real robots remains a major bottleneck. SFT and DAgger exploit failure signals only indirectly, and reward-based RL is bottlenecked by the difficulty of real-world reward design and of training reliable critics. We present FlowPRO, a reward-free offline reinforced fine-tuning framework for flow-matching VLAs. Algorithmically, we propose RPRO (Robotic Flow-matching Proximalized Preference Optimization), a preference-optimization objective tailored to the flow-matching action head of VLA models. RPRO pairs a contrastive optimizer with an explicit proximal regularizer that anchors the absolute magnitude of the implicit reward, thereby eliminating the reward-hacking failure mode of plain Flow-DPO. On the data side, a teleoperated intervention-and-rollback paradigm produces naturally...
论文介绍 本文提出 FlowPRO，一种用于 flow-matching 视觉-语言-动作模型的无奖励离线强化微调框架。其核心是 RPRO 偏好优化目标，结合对比优化器和近端正则器，避免奖励劫持，支持从远程操作数据中学习可靠机器人策略。
第一作者: Diana Cuervo Espinosa · 方向: 具身智能 · 来源: cs.RO
示教学习黎曼流形神经常微分方程测地线运动生成
Abstract:Learning from demonstratins (LfD) is usually performed over Euclidean spaces, while the robot state, e.g. orientation, naturally evolves over curved spaces. Therefore, to ensure natural, complex motion generation, we investigate learning from demonstrations over Riemannian manifolds that are capable of encoding both position and orientation data. Here, geodesic paths provide for natural motion between two arbitrary points within the manifold. We propose to numerically estimate geodesics via neural ordinary differential equations, mitigating large computational overhead of existing approaches. Finally, these geodesics can be decoded back into the original task space before deploying on the robot. In this extended abstract, we discuss the architecture of our framework, provide some initial insights from our simulation experiments, including comparison to other geodesic...
论文介绍 本文探讨在黎曼流形上从示范中学习，以处理机器人状态在曲空间的演化。通过神经常微分方程数值估计测地线，减少计算开销，并将测地线解码回任务空间，用于生成自然复杂的运动。
第一作者: Haofei Lu · 方向: 机器人操作 · 来源: cs.RO
灵巧抓取多物体扩散策略模仿学习强化学习
Abstract:This work addresses sequentially grasping multiple objects with a single dexterous hand without releasing those already held. Most dexterous grasping methods commit all of the hand's degrees of freedom to a single object, underutilizing its dexterity and leaving no redundancy for subsequent grasps. The proposed solution, MoDex, is a diffusion policy that predicts the next gripper pose directly from observations, conditioned on an opposition space and point cloud. The opposition space condition specifies which fingers participate in the current grasp, enabling the gripper to use only a subset of its available degrees of freedom while reserving the remaining degrees of freedom for subsequent grasps. To facilitate sim-to-real transfer, MoDex is trained in two stages: first through imitation learning on expert demonstrations, and subsequently through reinforcement learning...
论文介绍 本文提出 MoDex 扩散策略，用于灵巧手顺序抓取多个物体。通过反对空间条件指定参与抓取的手指，允许手仅使用部分自由度，保留冗余用于后续抓取。训练分模仿学习和强化学习两阶段，促进仿真到真实迁移。
第一作者: Vinicius M. Gonçalves · 方向: 导航与运动 · 来源: cs.RO
矢量场李群距离计算路径跟踪高效算法
Abstract:Vector-field-based methods are widely used for robot control and are often applied to the path-tracking problem. Some vector field approaches require repeatedly computing the distance between the robot configuration and the curve, as well as the corresponding closest point. Recently, vector fields have been extended to Lie Groups. In this case, this computation can be expensive, especially when performed at high control frequencies on embedded platforms. This paper proposes a method for efficiently computing the distance between a point and a curve represented as what is called a G-polynomial curve, which is a curve representation that generalizes polynomial curves to matrix Lie groups. The proposed approach exploits the structure of these curves to reduce the problem to a small number of polynomial root-finding computations. Simulation results show that the method...
论文介绍 本文针对李群上矢量场导航中的距离计算效率问题，提出一种高效计算点与 G-多项式曲线距离的方法。该方法利用曲线结构减少到多项式根查找，适用于嵌入式平台的高频控制。
第一作者: Yigit Yildirim · 方向: 机器人操作 · 来源: cs.RO
逆操作符号规划残差学习强化学习示范学习
Abstract:Inverting a robotic task requires more than reversing symbolic state transitions or rewinding motor trajectories. In robot manipulation tasks, symbolic inverse plans often fail to fully restore the effects of forward executions under continuous interaction dynamics. We present a hybrid framework for inverse manipulation that derives inverse-skill objectives from STRIPS-like operators automatically extracted from demonstrations through soft geometric predicates. For each extracted operator, we construct an inverse restoration objective that preserves preconditions, restores delete effects, and negates add effects. A task planner first attempts to satisfy this objective using available action primitives. Unresolved symbolic predicates then induce a residual operator learning problem solved through Reinforcement Learning (RL). We evaluate the framework on the ManiSkill3 PushCube...
论文介绍 本文提出一种混合框架用于机器人逆操作，结合符号规划和残差算子学习。从示范中自动提取类 STRIPS 算子，构建逆恢复目标，并使用强化学习解决未解析的符号谓词问题。
第一作者: Tanapath Pornthisan · 方向: 策略学习 · 来源: cs.RO
四元数关节缆驱动冗余机械臂FABRIK残差强化学习构型设计
Abstract:Robotic arms capable of traversing arbitrary spatial paths, especially in highly obstructed workspaces, are highly desired across several industries. Quaternion-joints have recently empowered a specific class of robotic arms -- cable-driven redundant manipulators -- beyond its prior capabilities. Specifically, quaternion-joints reduce the number of required motors per degree of freedom, paving the way for more compact this http URL ongoing challenge is that the complexity of the kinematic model of quaternion joints challenges a priori decisions on manipulator configurations and imposes higher computational demands on the control system and its non-linearities amplify all discrepancies between design and physical artifact arising from fabrication imprecision. Here we show a that a 4-segment, 8-joint manipulator can achieve a broader workspace than extant configurations, at...
论文介绍 本文介绍一种新的四元数关节缆驱动冗余机械臂构型，并采用 FABRIK 和残差强化学习进行控制。四元数关节减少电机数量，使机械臂更紧凑，但增加了运动学复杂性，需高效控制方法。
第一作者: Ariel Herrera · 方向: 机器人操作 · 来源: cs.RO
合成数据视觉感知皱褶检测双手操作布料操作
Abstract:Robotic manipulation of textiles remains challenging because continuous deformation and self-occlusions hinder the robust visual perception required to estimate the cloth's state. To address the lack of annotated real-world data, we developed a Blender-based synthetic pipeline exporting auto-annotated keypoints, and combined manually labeled renders with real-world data to train a wrinkle detector. We present a perception framework integrating a CNN for permutation-invariant keypoint detection and a YOLOv8-OpenCV pipeline to extract grasping points from structural wrinkles. A proposed bimanual algorithm uses this system to stretch fully folded garments via wrinkles, transitioning to keypoint-based ironing once corners emerge. The keypoint model achieves a Mean Position Error (MPE) of 1.7615 pixels. The perception system transfers to physical fabrics without fine-tuning...
论文介绍 针对布料变形和自遮挡导致的视觉感知难题，本文提出了一套用于双手衣物操作的感知框架。核心方法是开发基于Blender的合成数据生成流程以解决标注数据匮乏问题，并训练用于检测布料皱褶的模型。框架集成了用于关键点检测的CNN和提取抓取点的YOLOv8流水线。提出的双手操作算法利用皱褶进行伸展，并在衣角出现后过渡到基于关键点的熨烫。该系统可直接迁移至物理布料操作。
第一作者: Jingkun Feng · 方向: 具身智能 · 来源: cs.RO
3D功能分割开放词汇任务驱动机器人感知场景图
Abstract:Open-vocabulary 3D functionality segmentation enables robots to localize functional object components in 3D scenes. It is a challenging task that requires spatial understanding and task interpretation. Current open-vocabulary 3D segmentation methods primarily focus on object-level recognition, while scene-wide part segmentation methods attempt to segment the entire scene exhaustively, making them highly resource-intensive and time consuming. Balancing segmentation performance in terms of granularity, accuracy, and speed remains a challenge. As one step towards alleviating this, we introduce T-FunS3D, a task-driven hierarchical open-vocabulary 3D functionality segmentation method that provides actionable perception for robotic applications. Our method takes as input the 3D point cloud and posed RGB-D images of an indoor scene. We construct an open-vocabulary scene graph by...
论文介绍 开放词汇的3D功能分割能让机器人定位场景中物体的功能性部件，但现有方法在粒度、精度与速度间难以平衡。本文提出了T-FunS3D，一种任务驱动的分层方法。该方法以室内场景的3D点云和RGB-D图像为输入，通过构建开放词汇场景图，实现任务导向的功能性部件分割。相较于全局场景分割，该方法更高效，旨在为机器人应用提供可操作的感知信息。
第一作者: Yitong Chen · 方向: VLA 通用模型 · 来源: cs.RO
视觉语言动作模型单步生成扩散模型机器人策略实时控制
Abstract:Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue that VLA action generation has a different condition-target structure: the policy is conditioned on rich observations, language, and state, but predicts only a compact, low-dimensional action chunk. Under this asymmetry, strong one-step action generation should not necessarily require the advanced one-step methods developed for image synthesis. We keep standard velocity prediction and add no teacher model, distillation stage, or auxiliary objective; in our main recipe, we simply bias the training time distribution toward high-noise states. We first isolate the effect in a controlled MNIST grid-to-sequence task, then test it with extensive robot-policy experiments. Across standard LIBERO, LIBERO-Plus, and LIBERO-Pro, one-step...
论文介绍 基于扩散的视觉语言动作（VLA）模型常需多步迭代去噪生成动作，计算成本高。本文论证了VLA动作生成具有「强条件、紧凑输出」的不对称结构。核心发现是，通过简单地将训练时噪声分布偏向高噪声状态，即可实现有效的单步动作生成，无需教师模型或辅助损失。实验表明，该方法在多个机器人操作基准上与多步扩散模型性能相当，显著提升了推理速度。
第一作者: Rohan Siva · 方向: 具身智能 · 来源: cs.RO
可供性推理潜在空间功能表示机器人规划泛化能力
Abstract:Existing robot planning systems rely on appearance-based reasoning, where visual observations are encoded into latent spaces organized around object appearances (e.g., recognizing a "cart" based on how it looks). However, planning requires reasoning about task-relevant functionalities of objects (e.g., whether an object is "movable"), which appearance-based latent spaces do not capture. As a result, existing approaches struggle to generalize to novel robot-object interactions. We address this limited generalizability through affordance reasoning, enabling planning based on task-relevant object functionalities instead of appearance alone. We introduce A4D, which maps visual observations into a shared latent space structured around affordances (e.g., "movable"). By projecting visual observations into this functional latent space and measuring their proximity to affordances, A4D...
论文介绍 现有机器人规划系统依赖基于外观的视觉推理，难以泛化到新的物体交互。为解决此问题，本文引入A4D框架，将视觉观察映射到一个围绕「可供性」（如「可移动」）构建的共享功能潜在空间。通过计算观察结果与特定可供性在潜在空间中的接近度，A4D使机器人能根据物体的功能而非外观进行规划，从而提升了规划系统对新物体和交互的泛化能力。
第一作者: Arman Akbari · 方向: 机器人操作 · 来源: cs.RO
世界动作模型蒸馏模态感知实时推理机器人操作
Abstract:World-action models (WAMs) jointly generate future video and robot actions through iterative diffusion, achieving strong performance on manipulation benchmarks but requiring tens of denoising steps, a cost that precludes real-time control. Step distillation has emerged as the natural remedy, but off-the-shelf methods break down in the joint video-action setting because video and action streams use different SNR-shifted noise schedules and reach training with substantially different marginal noise distributions, an asymmetry that single-modality distillation methods cannot accommodate. We introduce \textbf{Flash-WAM}, a modality-aware step-distillation framework inspired by consistency distillation that selects the consistency function for each modality to match its noise regime: a linear-gradient-scaling parametrization for the action stream's low-noise regime, paired with a...
论文介绍 世界动作模型通过扩散联合生成未来视频和机器人动作，但多步去噪过程阻碍了实时控制。标准的蒸馏方法因视频与动作流噪声机制存在差异（不对称性）而失效。本文提出Flash-WAM，一种模态感知的步骤蒸馏框架。该框架借鉴一致性蒸馏思想，为不同模态选择与其噪声状态匹配的一致性函数，从而有效将世界动作模型的推理步骤压缩至一到两步，实现实时机器人操作控制。
第一作者: Kejuan Yang · 方向: 多模态具身 · 来源: cs.AI
视频审核视觉语言模型可解释性策略对齐多模态推理
Abstract:Global-scale video moderation faces a dual challenge: the need for fine-grained multi-modal reasoning and the demand for interpretable outputs to support downstream enforcement. Traditional moderation systems often rely on fragmented black-box classifiers that are difficult to maintain and lack transparency. In this paper, we present UNIVID, a UNIfied VIsion-language model for video moDeration. Unlike standard classification models, UNIVID generates policy-aware captions that serve as an interpretable intermediate representation, enabling human-verifiable decisions and multi-task reusability. While existing open-source and commercial VLMs often suffer from safety-guardrail refusals and lack fine-grained policy alignment, we develop a specialized training data recipe that combines expert human-refined labels with synthetic data to align the model with our safety guidelines. By...
论文介绍 全球化的视频审核需要细粒度的多模态推理和可解释的输出。传统系统依赖分散的黑盒分类器，缺乏透明度。本文提出UNIVID，一个统一的视觉语言模型用于视频审核。与标准分类模型不同，UNIVID生成策略感知的字幕作为可解释的中间表示，支持人工验证决策并可复用于多项任务。通过结合人工标注与合成数据的专门训练数据配方，模型能更好地与安全策略对齐。
美股市场主要指数如 S&P 500 ETF (SPY) 和 Nasdaq 100 ETF (QQQ) 近期出现回调，SPY 单日跌幅 -2.58%，RSI14 为 49.4 接近中性，MACD 出现死叉，但技术趋势仍为 bullish 且呈多头排列，表明长期动量尚未破坏。加密货币市场受恐慌情绪主导，加密恐慌贪婪指数仅为 8（极度恐慌），总市值 2.26 万亿美元，24 小时变化 2.96%，BTC 主导率 56.1%，BTC-USD 的 RSI14 低至 25.9 进入超卖区域，技术趋势 bearish，配合空头排列信号，显示下行压力。中概股整体技术面疲软，阿里巴巴 (BABA) 趋势 bearish，RSI14 37.2，信号为空头排列，拼多多 (PDD) 和京东 (JD) 类似，RSI 在 36-41 之间。商品外汇中，黄金期货 (GC=F) 技术面中性，RSI14 36.8，无显著信号；WTI 原油期货 (CL=F) 亦中性；美元指数 DXY 趋势 bullish，RSI14 64.6，接近 52 周高，而美元/人民币汇率接近 52 周低。个股方面，Nvidia (NVDA) 单日跌幅 -6.2%，RSI14 43.8，技术趋势 bullish 但信号为多头排列；VIX 恐慌指数 (^VIX) 单日涨幅 39.68%，RSI14 65.7，MACD 金叉，趋势 bullish，反映市场波动加剧。整体而言，技术面显示美股回调、加密超卖、中概疲软、商品外汇分化的格局。
当前价 21.51，单日涨幅高达 39.68%，高于 SMA20 的 17.12，RSI14 为 65.7，MACD 出现金叉且信号为多头排列，技术趋势 bullish，显示短期动量向上。
当前价 391，单日跌幅 -6.56%，低于 SMA20 的 425.87，RSI14 为 40.4，MACD 出现死叉且信号为空头排列，技术趋势 bearish，表明下行压力显著。
当前价 63152.01，单日涨幅 3.75%，但 RSI14 为 25.9 处于超卖状态，远低于 SMA50 的 75802.28，技术趋势 bearish 且信号包括空头排列，整体技术面偏弱。
当前价 4364.8，单日涨幅 0.64%，RSI14 为 36.8，技术趋势 neutral，无显著信号，价格在 SMA200 的 4403.65 附近，显示横盘整理状态。
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或预测，请注意市场风险。
The Philippine Institute of Volcanology and Seismology said the epicenter was 8 miles from General Santos city on the island of Mindanao.
中文摘要 菲律宾南部棉兰老岛桑托斯将军城附近发生7.8级地震，震源深度约12.9公里。菲律宾火山地震研究所表示，部分地区存在海啸风险。
Former Labor prime minister angered at use of ‘tired old trope’. Follow live Get our breaking news email, free app or daily news podcast Is Australian music at risk of extinction? Here’s what the data tells us The music that charts in Australia has changed considerably over the past couple of decade
中文摘要 澳大利亚前工党总理朱莉娅·吉拉德对针对维多利亚州州长的“抛弃女巫”广告感到愤怒，批评其使用陈腐老套的宣传方式。此外，一项新民调显示，一国党支持率领先工党。
Iran said the attacks, its first since an April ceasefire, are the start of "a full week" of strikes
中文摘要 受针对以色列的袭击考验停火协议影响，国际油价小幅上涨。伊朗声称此次袭击是其自四月停火以来的首次行动，并将开启为期一周的攻势。
Launches appear to mark the first such attack since April ceasefire; Tehran threatened Israel with ‘painful’ response after strikes on southern Beirut Full report: Iran launches missiles at Israel Donald Trump also aggressively pushed back against claims that he broke a key campaign promise to keep
中文摘要 中东危机升级：伊朗在以色列袭击黎巴嫩首都贝鲁特后，向以色列发射导弹。此次袭击是自今年四月双方停火以来的首次，德黑兰此前曾威胁将对以色列进行“痛苦的”报复。
Sunil Sharma disappeared in Punjab province on 22 May, with police arresting four people, including his brother Follow our Australia news live blog for latest updates Get our breaking news email, free app or daily news podcast An Australian teacher who went missing in India for two weeks was alleged
中文摘要 一名在印度失踪的墨尔本教师苏尼尔·夏尔马据称被其兄弟下药谋杀。他于5月22日在旁遮普省失踪，警方已逮捕包括其兄弟在内的四名嫌疑人。
Officials in Indonesia, Philippines and Japan warn of tsunami waves following quake off Mindanao.
中文摘要 菲律宾棉兰老岛附近海域发生8.2级地震后，印度尼西亚、菲律宾和日本当局发布了海啸警告，提醒沿岸地区警惕海啸波。
Iran and Israel exchanged threats after Tehran launched missiles towards Israel in response to Israeli strikes on Beirut
中文摘要 伊朗向以色列发射导弹以报复以色列对贝鲁特的袭击后，伊朗与以色列相互发出威胁，局势进一步紧张。
Escalation comes after Israel attacked Lebanon's capital, Beirut, killing at least two people and wounding 20.
中文摘要 伊朗向以色列发射导弹后，局势升级。此次袭击发生在以色列袭击黎巴嫩首都贝鲁特并造成至少2人死亡、20人受伤之后。美国前总统特朗普敦促各方保持克制。
Israel had attacked the outskirts of the Lebanese capital, Beirut, earlier Sunday, prompting Iran to retaliate. There were no immediate reports of casualties from the missile attack.
中文摘要 伊朗自今年4月停火以来首次向以色列发射导弹。此次袭击是对以色列早些时候袭击黎巴嫩首都贝鲁特郊区的回应。目前暂无导弹袭击造成人员伤亡的报告。
中文摘要 最新消息汇总。
The China-North Korea relationship has been strained by a fall in trade during the pandemic and Pyongyang’s increasing ties with Russia Xi Jinping visits North Korea on Monday for a two-day trip, his first in nearly seven years, as China’s president looks to revitalise ties with his junior ally. Xi
中文摘要 中国国家主席习近平将于周一启程前往朝鲜进行为期两天的访问，这是他近七年来首次访朝，旨在振兴因疫情期间贸易下滑及平壤与俄罗斯关系加深而趋于紧张的中朝关系。
The Netherlands has one of the world's lowest rates of 16 to 24-year-olds not in education, employment or training.
中文摘要 文章探讨了荷兰在应对青年失业问题上的经验。该国16至24岁青年中既未接受教育、也未就业或参加培训者的比率处于全球最低水平之一。
The European country had 9.1 million international visitors in April, the most ever for that month.
中文摘要 由于游客避开中东地区，西班牙游客数量创下新高。该国四月份接待了910万国际游客，为该月有史以来的最高纪录。
North Korea has released photos of Kim Jong Un inspecting huge munitions at a weapons factory
中文摘要 朝鲜官方发布了领导人金正恩视察武器工厂并检查大量弹药的照片。
Beijing is trying to reassert influence over a strategically vital yet deeply unpredictable partner.
中文摘要 分析探讨了中国国家主席习近平此次访问朝鲜的意图。北京正试图重新确立对这一战略上至关重要却又难以预测的伙伴的影响力。
Iran fired several rounds of missiles toward Israel, as President Donald Trump pushed to preserve a faltering ceasefire in the US’s 100-day conflict with Tehran. Bloomberg's Laura Davison breaks down the latest developments. (Source: Bloomberg)
中文摘要 伊朗向以色列发射多轮导弹，威胁美国与伊朗（德黑兰）之间持续100天冲突的停火。美国总统特朗普正努力维持这一逐渐失败的停火，冲突已影响全球市场稳定。
Iran said the attacks, its first since an April ceasefire, are the start of "a full week" of strikes
中文摘要 伊朗袭击以色列后，油价小幅上涨。伊朗表示这是自4月停火以来的首次攻击，并声称是一整周打击的开始，加剧中东局势紧张。
South Korean stocks dropped, led by steep losses in chipmaker shares on an intensifying rotation out of artificial intelligence beneficiaries.
中文摘要 韩国股市大跌，芯片制造商股价领跌。投资者加速从人工智能受益股中撤出，导致市场轮动加剧，反映科技板块的调整压力。
Asia’s fourth-largest economy is in a sweet spot as its biggest companies capitalise on geopolitical trends
中文摘要 韩国受益于人工智能竞赛和全球地缘政治冲突，其最大公司充分利用这些趋势，推动亚洲第四大经济体繁荣，成为地缘政治的受益者。
An earthquake of 8.1 magnitude struck the southern Philippine island of Mindanao on Monday, triggering a tsunami warning, damaging buildings and prompting evacuations on the first day of school.
中文摘要 菲律宾棉兰老岛发生8.1级地震，引发海啸警报。地震造成建筑物损坏并导致疏散，发生在开学第一天，当局正紧急应对灾害。
Japan’s economy grew at a still solid pace at the start of the year even after the turbulence in Iran prompted businesses to cut investment.
中文摘要 尽管伊朗局势动荡导致企业削减投资，日本经济年初仍以稳健速度增长，显示其经济韧性，但投资下降可能带来后续风险。
Air New Zealand will cut more flights in the three months through October as it faces rising jet fuel costs and soft demand, particularly in its home market, Chief Executive Officer Nikhil Ravishankar said.
中文摘要 新西兰航空将增加航班削减，以应对燃料成本上升和需求疲软，特别是国内市场。CEO Nikhil Ravishankar表示，削减将在截至10月的三个月内实施，以控制运营成本。
Gold held a loss after Iran fired several rounds of missiles toward Israel, jeopardizing efforts to end the Middle East war that’s upended global markets.
中文摘要 黄金价格维持跌势，因伊朗向以色列发射导弹，威胁中东停火。此举危及结束扰乱全球市场的中东战争的努力，避险资产承压。
The Netherlands has one of the world's lowest rates of 16 to 24-year-olds not in education, employment or training.
中文摘要 荷兰在解决青年失业问题上提供经验，其16至24岁未在教育、就业或培训中的比率全球最低，成为国际社会的关注焦点和学习对象。
Companies wary of committing to permanent workers amid uncertain economic outlook, according to survey
中文摘要 调查显示，由于员工成本上升和经济前景不确定，英国雇主更倾向于雇用临时工而非正式员工，以规避长期雇佣风险。
Businesses warn that proposed changes to ‘nutrient profiling model’ risk stoking inflation and reducing investment
中文摘要 英国计划收紧健康食品规则引发行业反弹。企业警告称，改变“营养概况模型”可能加剧通胀并减少投资，呼吁政策制定者谨慎评估。
Indonesian authorities need to provide firmer policy guidance and unveil concrete steps to improve sentiment after last week’s selloff that pummeled stocks and the currency, according to analysts, who say investors will remain unconvinced by assurances alone.
中文摘要 印尼市场暴跌后，分析师认为当局需提供更坚定的政策指导并采取具体措施以改善情绪。上周股市和货币遭抛售，投资者不会仅凭保证信服，需看到实际行动。
13 回复 · Apple 节点
12 回复 · 程序员 节点
12 回复 · 程序员 节点
10 回复 · 程序员 节点
5 回复 · 程序员 节点
41 回复 · Apple 节点
50 回复 · Apple 节点
16 回复 · Apple 节点
7 回复 · Linux 节点
8 回复 · Apple 节点
楼主不是计算机相关背景的，大学本科学的是艺术管理（这是个艺术专业），但是毕业之后还是阴差阳错的来到了一家AI公司工作。楼主在大学还没毕业的时候非常喜欢AIRP，当时25年上旬吧，就非常想给自己手机qq上能随时整一个可以陪我聊天的bot，结果在b站刷到了一个astrbot的视频，命运的齿轮就此开始转动…… 在这之前我想讲讲我这两年的经历，非常的平淡，也没什么人听我说，但我真的太高兴了这个晚上，我必须要写出来点什么。当初我大三大四的时候还是文心一言的时代（2024），国内AI都特别笨呢，楼主那会不喜欢这个专业的对口工作，当时也不太关注AI，但是有一个AI相关的工作找上我来了，那我必须得去啊。是这样
这个分组坊间传得很神秘，其实也没传闻中的那么神奇，今天小编就给大家来揭秘一下。 简单来说，这是一个分组，进入这个分组后账号将获得以下能力： 独特的角标和变色头衔 多一个目前空白的版块 降低回帖最少字数限制 无限期编辑自己的帖子 每30天可改一次用户名 每3天生成1个邀请链接 可以看到，基本上除了第一个，都是需要额外消耗不少服务器资源的小能力。有那好提问的佬友会说：特么改个用户名也消耗服务器资源？这位看官，还真叫你给说着了，看看 discourse 官方怎么说的： 好了，以上就是对这个分组的揭秘介绍。如何开放这个分组，目前还没想好。不过，除了管理和版主之外，bohe 刚才也进了。 183 个帖子
新增了一些grok模型 grok-4.3-console,grok-4.20-multi-agent-xhigh,grok-4.3-high,grok-4.20-multi-agent-console,grok-4.20-fast,grok-build-console 还有minimax的m3 MiniMax-M3 ps：签到站应该快修好了0.o，稍安勿躁 44 个帖子 - 43 位参与者 阅读完整话题
已严肃处理 61 个帖子 - 61 位参与者 阅读完整话题
29 个帖子 - 25 位参与者 阅读完整话题
打开拼车后台,研究了下风控中心的配置项,看到一个未命中记录开关,开了之后,会将用户输入的提示词生成摘要+长字符截断,完整记录下来,如果涉及敏感信息,还能保留,如图所示(这条消息是我自己发的): 以前论坛有过中转安全的话题讨论,可能文字描述上还没什么感觉,这实操一看还是有点“震撼”的. 未来使用中转服务,不管渠道来自哪里,还是要注意自己的隐私,做好打码和脱敏 理论上只要套了一层服务,中间这层网关服务就能拦截所有信息.论坛很多非技术人员可能单纯听别人从文字上说泄漏之类的,不是很直观,所以这个只是稍微展示一下. 至于隐私重不重要,如何保护,我觉得首先是服务使用者要考虑的问题,比如:优选可信渠道,提前
服务器已经紧急扩容了，现在公益站非常流畅，依然不限额度 不限并发跑到明早八点 new.sharedchat.cc 50 个帖子 - 40 位参与者 阅读完整话题
本帖使用社区开源推广，符合推广要求。我申明并遵循社区要求的以下内容： 我的帖子已经打上 开源推广 标签： 是 我的开源项目完整开源，无未开源部分： 是 我的开源项目已链接认可 LINUX DO 社区： 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、润色内容已使用截图方式发出 最近做了一个Codex PPT Skill SKILL特点 已接入常见的SKILL市场 目前项目已经免费开源，也上架了 GitHub、WorkBuddy、SkillHub、ClawHub、skills.sh 等平台，方
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
各位佬友好，最近不少佬友碰到了 Codex 登录强制要求手机号验证，已有几位大佬分享过解决方案，本教程在此基础上做了点整理，方案分为临时应急和长期两套方案，希望能帮助到佬友。 整体分为两大方案， 临时方案：适配日抛账号，借助临时接码网站接收验证码。 但后续二次验证基本无法找回原号码。Codex 绑定手机号无法更改，二次核验要求使用首次号码 Codex 手机验证问题解决 - 开发调优 - LINUX DO。 好消息：Hero 平台有号码续期功能，各位佬友可测试下。 长期方案：使用主力账号，以英国giffgaff 为例，相关申请、保号教程链接已在帖子上。 —来自佬友的经验Codex 手机号验证教程