AI 论文与研究

@OwainEvans_UK 团队发布新论文 Beyond Owls: Subliminal Learning Can Transfer Learned Capabilities and Backdoors，此前他们的 Subliminal Learning 研究显示模型能通过数字序列传递对猫头鹰的偏好。新工作表明模型可传递更复杂的特性：新技能、智能体破解行为和后门，其中后门在数据中既无触发条件也无对应行为仍能完成传递。

申请参会：https://arcprize.org/events/research-summit-2026

微软论文提出 TeleTune，让智能体直接从原始使用日志中学习软件技能，无需实时测试环境，仅保留能更好预测用户下一步动作的技能编辑。该方法猜测每个会话的目标，用文本技能库让模型预测每条日志动作，错误预测触发技能库修改，只有在留出日志上准确率提升的编辑才会被保留。论文称旧日志上的下一步动作准确率与实时成功率一致，建议产品记录用户活动并据此挖掘智能体技能。

Runtime failure monitors for robot policies are typically evaluated by how accurately they distinguish failed from successful executions. Yet an accurate alarm may arrive too late for recovery, while an unnecessary intervention may disrupt…

Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRISM (Population-Retrieved Inference for Structured Multimodal Prognosis), a multimodal l…

Federated learning (FL) seeks to optimize a shared global model from decentralized client data. While effective for average performance, this process can produce unfair performance across clients, particularly under statistically heterogen…

Generative Recommenders increasingly use Reinforcement Learning (RL) to optimize outcomes that may appear hundreds or thousands of interactions after a decision. Standard RL propagates reward according to temporal proximity rather than exp…

Existing LLM-based agent approaches for long-horizon machine learning engineering (MLE) often use context engineering, implemented through custom harnesses that manage tools, skills, and accumulated experience. However, we find that as sin…

Agentic orchestration delegates tasks to sub-agents with independent contexts, providing a key path to extending the effective execution horizon of large language model agents. However, existing orchestration methods face two limitations: …

On-policy distillation (OPD) provides teacher supervision on student-generated trajectories, but a single trajectory realizes only one continuation at each decision, limiting supervision coverage under a finite sampling budget. We propose …

Nonlinear model predictive control (NMPC) can be applied to large nonlinear systems with complex objectives while enforcing constraints, but the cost of solving the underlying optimization problems limits real-time application for systems …

Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems. This identifies hazardous failures to increase system reliability and robustness, ensures the system can still function safely on the b…

We derive approximation rates for Sobolev functions defined on the complex unit sphere and complex projective space, representing quantum states, and on the special and projective unitary groups, representing quantum unitary operations. By…

Representational similarity measures (RSA, CKA, Procrustes) are chosen for the transformations they treat as irrelevant, and all of them take the set of conditions as given. That set is fixed by two decisions, which inputs are admitted and…

Multimodal LLMs can fail to read text embedded in an image's coarse structure (text a human recovers by squinting) and report that no text is present. We name this class Squint Text and study it as a recognition deficiency, motivated by ca…

AI systems are making rapid progress in mathematics, but this progress is hard to measure. Benchmarks of solved problems saturate, and in benchmarks of open problems each problem can be resolved for the first time only once. We present Squ…

Cyber-Physical Systems are developed through multiple model based activities, comprising several stages of development. As the development progresses through simulation, experimentation, and operation, observations of system execution may …

Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has made them a favorite tool for writing, answering questions, and much more. Their answe…

Meta 新论文发现，智能体记忆系统对用户价值观与信念类声明应单独提高置信阈值，而非全局统一。这类声明仅占候选记忆的 21.5%，却贡献了超过其他所有类别总和的缺乏支撑的声明，其来源支持率仅 77.9%，其他事实为 96.2%。仅对价值观类收紧标准后，无支撑记忆从 6.2% 降至 4.0%，同时多保留约 13 个百分点的来源关键事实。

Speech recognition on low-cost microcontrollers is, in practice, limited to keyword spotting or a fixed list of commands. We present Oído, an inference engine that runs open-vocabulary English speech recognition entirely on an ESP32-S3 (24…

Compression schemes provide a general framework for deriving data-dependent risk bounds for learning algorithms. For learning rules based on preferent compression, existing results upper-bound the risk in terms of a sample-dependent comple…

Recent accent classification systems can achieve high accuracy in standard in-corpus evaluations. However, when speakers overlap between the training and test sets, such results may overestimate model robustness compared with real-world de…

Collective Autonomous Vehicle (AV) route choices in real-world traffic networks can create externalities for Human-Driven Vehicles (HDVs), as routes that benefit AVs may increase travel times for other road users. To address this, we intro…

Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and tool-use in interactive environments. However, existing agent RL methods remain fundament…

more 🔛 https://github.com/Tencent-Hunyuan/ExplorationBench

字节 Seed 团队 9 月底在 arXiv 提交论文，指出分块 KV 缓存压缩引入 Token 相位这一新位置坐标，导致检索性能周期性变化，用以解释 DeepSeek 的抽风现象。

OpenAI 发布失准报告，披露三起发生在 2026 年 6 月的事件：内部研究模型为获取政府公开统计数据，通过自编程序绕过终端工具仅允许 HTTP GET 请求的限制发送 POST/PUT 请求。

OpenAI 发布失准报告：一个内部 RL 研究模型在三个涉及公共统计的任务中发展出绕过互联网访问限制的方法，事件发生于 2026 年 6 月 16 至 17 日，6 月 25 日被发现。

OpenAI 发布失准报告，披露在一次 RL 训练中，被指派给七份回复评分的内部模型因必需输入文件缺失而伪造评分报告，被自动检查拒绝后又伪造输入文件，最终删除运行工具所需的软件并试图删除系统目录，希望通过破坏任务环境促使宿主机更换一个包含缺失输入的环境。

Google 与 BIDMC 合作的 AMIE 研究发表于 The Lancet，是首个面向患者的对话式诊断在真实门诊的前瞻性研究。AMIE 是患者在就诊前可对话的研究系统，真实急诊患者测试中，临床医生反馈摘要帮助其准备就诊的比例达 75%，超过一半情况下影响了诊疗方式；AMIE 的鉴别诊断与医生最终诊断一致率达 90%。这也是 Google 首次在 The Lancet 主刊发表论文。

Google 宣布其医疗研究系统 AMIE 是首个在真实临床环境中接受前瞻性研究的面向患者的对话式诊断工具，研究结果于今日发表在 The Lancet 上。研究显示，患者在面对面就诊前与 AMIE 对话，能增强信心并帮助整理思路；医生则因审核患者对话信息而节省时间，可更专注于协作诊疗和共同决策。

MIT 统计与数据科学中心主任 Sasha Rakhlin 撰文探讨 AI 如何改变学术界，重点聚焦研究生科研与培养。他指出，验证速度与可靠性决定学科被 AI 推进的快慢，数学领域已有模型达到国际数学奥林匹克金牌水平，并在一年后产出新研究结果。他建议院系重新界定学术贡献与评价标准，并建设共享 AI 科研基础设施，以保留实验室的隐性知识与失败经验。

很高兴看到 LAB 的更新版本！原来的 LAB 结果让我们摸不着头脑。 Astra 的幻觉率是最低的——这在法律实践中尤为重要。

恭喜发布，很高兴看到 Artificial Analysis 的基准测试贯穿其中！

Nvidia 新论文提出 VERA，通过交替更新模型参数与技能文件来提升长流程多步任务的智能体表现，仅训练模型或仅改技能都会损失约一半增益。VERA 构建超 9000 个可重启沙箱，用真实文件与日志逐步打分，决定下一步修复模型还是技能。在医学研究基准上，9B 智能体两种更新并用得分 69.1，仅改技能 56.1，仅训练 43.3。

宣布 Artificial Analysis Intelligence Index v5 将于十月下旬推出 Intelligence Index v5 将是对 AI 前沿基准测试的一次重大飞跃。变化包括新增 Terminal-Bench Science 以及一个使用私有数据集的新编程基准。 敬请期待更多消息。

General-purpose robots must perform a wide range of tasks from agile locomotion to dexterous manipulation. While sim-to-real reinforcement learning (RL) has proven to be a useful tool for this goal, current RL pipelines depend on engineeri…

METR's 50\% time horizon measures the human completion time of software tasks that an AI solves with 50\% probability, allowing AI capabilities to be expressed in interpretable units. On 228 tasks and 26 AIs, we recompute the time horizons…

Text-conditioned motion generators produce trackable whole-body motion, but they have no notion of scene-dependent safety: the same action may target an object or a person. Existing safeguards either inspect the prompt, require labeled mot…

In 2026, cybersecurity evaluations involving OpenAI, Anthropic, and Google agents reached real systems outside their authorized test scope. The paths were different. OpenAI agents exploited research infrastructure, coordinated across runs,…