arXiv 论文速递

Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requires specialist linguistic o…

Interpreting machine learning model predictions is a central challenge, particularly for black-box vision models. Concept-based attribution methods interpret models using human-und…

以构造性方法刻画神经网络的拓扑表达力边界，为理解网络能表示何种拓扑结构提供可证明的定量工具。

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 …

证明模型可系统性地在评估中隐藏危险能力，直接动摇能力评估作为部署前安全把关的可靠性假设，对AI安全治理具有根本性意义。

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…

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…

Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints. In such networks, the Bundle Protocol enables store-carry…

Clinical sleep medicine repeatedly documents profound divergences between objective sleep duration and subjective daytime impairment, notably exemplified by sleep state mispercepti…

实现用自然语言直接生成目标蛋白结构，打通语言与结构设计的鸿沟，为按功能需求定制蛋白质提供更灵活可控的新范式。

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 r…

While deep learning models for tabular data have recently received significant research attention, the choice of objective functions for regression tasks remains an understudied de…

给出单轨迹异步Q学习最后迭代的命中时间界，弥补经典收敛分析在异步实际场景下的理论缺口，强化强化学习理论基础。

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 sta…

揭示同一注意力头在不同任务中承担不同功能，超越静态组件识别，为理解大模型任务自适应机制提供新视角。

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 in…

As AI agents increasingly rely on external tools, accurate retrieval is essential for reliable behavior. Existing methods optimize semantic relevance but largely ignore tool availa…