All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
arXiv:2610.31918v1 Announce Type: new Abstract: Distilling interactive LLM agents requires choosing between teacher-generated demonstrations and student-generated experience, corresponding broadly to off-policy and on-policy distillation. While both have proven effective, we…
arXiv:2610.31972v1 Announce Type: new Abstract: Evaluating conversational agents that act on live, mutable enterprise data is hard: replayed sessions drift as backend state changes, and a benchmark built today can silently go stale as the data it describes moves on. We present…
arXiv:2610.31985v1 Announce Type: new Abstract: LLM agents are increasingly deployed in collaborative settings where they pursue separate tasks while sharing resources and operating under review or oversight processes. Such settings create safety risks not only when agents are…
arXiv:2610.32022v1 Announce Type: new Abstract: Intent recognition in human-robot interaction requires agents to resolve ambiguous natural language instructions by inferring the speaker's underlying goals. Research has increasingly focused on two notable paradigms for addressing…
arXiv:2610.32024v1 Announce Type: new Abstract: Task instructions from users for agents are inherently underspecified, especially regarding safety boundaries--creating behavioral risks. To study these risks, we introduce BARC-Bench, a collection of 110 tasks across nine…
arXiv:2610.32026v1 Announce Type: new Abstract: Conventional neural-network training typically follows a predefined optimization recipe, motivating a LLM agent that monitors training dynamics and adjusts optimizer settings as training progresses, but a fixed agent policy does…
arXiv:2610.32034v1 Announce Type: new Abstract: The growing population of orbital debris has intensified interest in active debris removal and on-orbit servicing, for which dual-arm space manipulators offer improved grasping stability and load distribution relative to single-arm…
arXiv:2610.32045v1 Announce Type: new Abstract: AI-for-Science agents are increasingly being used for formulating scientific hypotheses, running autonomous experiments, and interpreting evidence. These agents are constructed by integrating a large language model (LLM) into a…
arXiv:2610.32046v1 Announce Type: new Abstract: Recent \emph{test-time training} (TTT) frameworks have enabled open-weight large language models (LLMs) to outperform inference-only frameworks powered by frontier models on scientific discovery tasks. However, TTT introduces…
arXiv:2610.32057v1 Announce Type: new Abstract: We present HyScale, a long-context training system for learned sparse attention. Learned sparse attention is a promising architecture for million-token contexts, widely adopted in production since DeepSeek-V3.2. Selection, however,…
arXiv:2610.32060v1 Announce Type: new Abstract: Multi-agent LLM systems aim to improve reasoning through debate, evidence sharing, and mutual correction, but interaction can also introduce failures that final accuracy alone cannot explain. Agents may converge too early, ignore…
arXiv:2610.32096v1 Announce Type: new Abstract: Diffusion language models (DLMs) support bidirectional denoising and iterative refinement, but generation remains largely controlled by token-level masking schedules. This leaves draft-level refinement implicit and limits explicit…
arXiv:2610.32069v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) can perceive a traffic scene, reason about it, and propose a driving action within a single model. However, existing MLLM-based drivers reason from scratch at each frame and commit to…
arXiv:2610.32087v1 Announce Type: new Abstract: Understanding language-agent behaviour requires learning how actions are organised across a trajectory and how this organisation relates to context and outcomes. We propose a general framework that connects data-driven behavioural…
arXiv:2610.32099v1 Announce Type: new Abstract: Fixed source superposition and frequency partitioning constrain how communication content interacts with a probing reference in integrated sensing and communication (ISAC). We learn nonlinear waveform fusion across scales for image…
arXiv:2610.32106v1 Announce Type: new Abstract: Scientific agents collaborate with researchers whose expertise and preferences differ, but benchmarks usually hold the collaborator fixed. We introduce PersonaScienceBench: 200 tasks from five benchmarks across four scientific…
arXiv:2610.31937v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) remain vulnerable to carefully orchestrated multi-turn interactions that progressively bypass safety mechanisms. However, many existing red-teaming approaches rely on heuristics or impose strong…
arXiv:2610.31971v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly participate in negotiations on behalf of individuals and organizations, yet they remain vulnerable to manipulation, particularly in repeated multi-party interactions. Classical…
Paragon 已联系 - 总结当天的成果！今天的主要事情🟠25.10 🟠Rippling - 因为价格而离开 Claude 去 OpenAI 🟠Uber - ChatGPT 为 3 万名员工工作🟠Claude 和 Theorem - 123 个库经过证明验证🟠NVIDIA OpenShell - 代理将在几毫秒内停止......
猫王埃尔维斯·普雷斯利音乐目录的所有者起诉 Anthropic 公司，指控其未经许可使用 274 首歌曲训练其 AI 模型。这起诉讼对 AI 开发者构成了来自艺人继承人的重大法律挑战，……
科学文章太长，所以我只想请AI转述一下。 But there is a fear that he will miss important mathematical calculations and conditions. And if you need to return to the original, you will have to look for the desired section again. TextFold 的开发人员已经创建了相当......
沃尔玛将允许人工智能代理自行购物，而亚马逊则阻止他们 美国零售连锁店沃尔玛推出了 Agent Gateway，这是一个新系统，允许人工智能代理代表用户选择产品并进行购买。与竞争对手不同...
今天，我们重点介绍来自 Moonshot 的一种新语言模型，该模型有望成为开源解决方案的领导者，以及来自宾夕法尼亚州的一项令人惊讶的创新，人工智能生成的广告应该是
🌟 Recursive 发布了编码代理模型 由 Richard Socher 创立的初创公司 Recursive Superintelligence 在 5 月份投资 6.5 亿美元走出阴影，展示了其第一个模型 - Flint。 Recursive 甚至在第一个模型出现之前就收到了这笔钱，很大程度上是由于......
P-Zero Research 的新基准衡量人工智能模型自行设计和评估实验的效果。结果改善得如此之快，以至于 Anthropic 联合创始人 Jack Clark 现在认为自我改进的人工智能可能会在 2027 年到来。Anthropic 联合创始人 Jack Clark 的文章......
Sam Altman承认，没有人知道人工智能是否有意识 OpenAI首席执行官Sam Altman表示，今天没有人能肯定地说现代神经网络是否有意识。 “我想澄清的是：事实上，没有人……
Anthropic 表示，公司应该评估是否可以将子代理合并为一个可按需加载上下文的代理。在一项架构比较中，单代理设置的运行速度大约是前者的两倍。 Anthropic 在 GitHub 上发布了一个迁移工具包，以帮助团队......
在《外交事务》中，历史学家尼尔·弗格森、研究员丽莎·克拉森和谷歌前首席执行官埃里克·施密特将美国和中国视为人工智能帝国，将其他国家视为附属国。比赛的胜负不是由突破决定的，而是由谁能够为其提供资金决定的。仅美国企业...