AI 论文与研究

随着机器人变得越来越可靠，DAgger 的效率就大大降低了。 例如 90% 的成功率意味着人 >90% 的时间都在被动地看着机器人 核心思路：失败来自相似的初始状态，我们可以把学习聚焦在这些状态上！ 论文：https://arxiv.org/abs/2610.05882

Harvard 研究者 Fiona Chen 和 James Stratton 基于 Jellyfish 的数据分析发现，AI 编码工具的编码阶段效率提升被生产流程下游瓶颈吸收，企业软件产出和就业未见明显变化。研究覆盖 2021 年至 2026 年 3 月超过 700 家公司约 70 万员工的 3 亿条工作事件，显示代码审查时间显著变长、pull request 更易要求修改、审查者留下更多评论。

Epoch AI 推出 InnovationEval 评测，测试 AI 能否独立复现人类论文中的机器学习创新，对照对象为 Self-Distillation Policy Optimization（SDPO）。

Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requires specialist linguistic or scientific knowledge. We used the Wikipedia Game to test …

Interpreting machine learning model predictions is a central challenge, particularly for black-box vision models. Concept-based attribution methods interpret models using human-understandable concepts. Existing concept-based methods can on…

The expressivity of a neural network $Φ$ describes the class of functions that a network can express. The term topological expressivity refers to a family of measures particularly suited to understand binary classification and is often for…

Capability evaluations aim to surface dangerous model behaviors before deployment, but their reliability depends on the assumption that hidden capabilities can be elicited. We show this assumption does not hold under adversarial conditions…

A parallel sampler can choose at random which coordinates to generate together. For a target $p$ and the output law $q_U$ of a schedule $U$ drawn afresh for each output, we compare the schedule-averaged divergence $\mathbb{E}_U D_{\mathrm{…

Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints. In such networks, the Bundle Protocol enables store-carry-forward communication, requiring relay nodes to manage lim…

Clinical sleep medicine repeatedly documents profound divergences between objective sleep duration and subjective daytime impairment, notably exemplified by sleep state misperception in paradoxical insomnia and boundary instability in narc…

A central challenge in de novo protein design is generating proteins with desired structural and functional properties. Existing design models typically require a dedicated input representation for each property, limiting the design object…

Recursive self-improvement (RSI) aims to transform interaction experience into persistent improvements, yet external feedback is costly and world-model predictions may become unreliable as policies evolve. We introduce RSI-Anything, a doma…

Vision-Language Models (VLMs) increasingly analyze and reason about images, yet it remains unclear whether their internal representations faithfully encode the structured relations required for such reasoning. We introduce EICS (Evaluation…

While deep learning models for tabular data have recently received significant research attention, the choice of objective functions for regression tasks remains an understudied degree of freedom. Several lines of research offer alternativ…

We study the last iterate of standard asynchronous Q-learning from a single trajectory of a finite Markov decision process. The trajectory follows a fixed behavior policy whose state--action chain is irreducible and may be periodic. For di…

Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfold during generation. Constrained decoding prevents locally invalid tokens but does not…

Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in each task. A natural source of inspiration is task-dependent interactions among shared brain…

As AI agents increasingly rely on external tools, accurate retrieval is essential for reliable behavior. Existing methods optimize semantic relevance but largely ignore tool availability during execution. To address this gap, we propose RA…

Personal agents increasingly connect to services across the web and applications by using tools. As the effects of their actions accumulate and interact across services, unintended or harmful outcomes can arise when agents fulfill benign u…

A memory that reproduces every current prediction may still have forgotten how to learn from the next observation. We characterize this distinction for exact cumulative learning and attention. For smooth convex residual losses with unrestr…

Many optimization problems provide direct access to only part of the gradient, while the remaining component must be inferred from function evaluations. This structure arises in performative prediction, performative reinforcement learning,…

We establish finite-sample guarantees for conditional diffusion models learned from data and implemented with finitely many denoising steps. Our approach aligns the score-training objective with the sampling grid, allowing statistical esti…

Generative molecular design typically relies on over-generation and post-hoc filtering. Inference-time steering methods like Feynman-Kac (FK) steering improve efficiency by biasing trajectories toward high-reward candidates, yet they optim…

a16z 援引 Zitzewitz 的 NBER 工作论文指出，汇总逾百年预测市场数据后，政治倾向、性别、肤色、年龄等维度均未出现超过标准误的收益系数，仅非美国选举样本显示市场略微高估右倾候选人，但 95% 置信区间表明该偏差不具统计显著性。文章还以巴西总统选举首轮为例，称预测市场比市场反应提前约 3 周押中结果。

Ethan Mollick 引用一项基于旧版 GPT-4o 的随机对照实验研究：获得 AI 访问能提高测试成绩，较小的提升在一周后仍然保留。以 AI 作为辅导工具（augmentation）的学生成绩提升保持，而让 AI 代写（automation）的学生提升消失。作者称所有实验均显示正面效果。

我们在一个 11.6 万行的代码库中埋了 70 个 bug。3 次运行中，单个智能体分别找到了 14、15 和 27 个 bug。而一个工作流在 3 次运行中每次都稳定找到 66 个。

@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…