arXiv 论文速递

Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built in this way now operate robot…

Embedding spaces define notions of semantic similarity and distance. We study whether those embeddings reflect physical measurements of mass, distance, time and volume, which admit…

Complex robotic manipulation tasks frequently require a long-term memory of past events and actions. As conditioning on full histories renders policies prone to spurious correlatio…

从稀疏单目视角前馈式建模铰接物体的几何与运动，突破稀疏观测下部分几何与运动证据不足的难题，对机器人操作与3D感知有重要意义。

Modeling articulated objects from sparse monocular views is challenging because each observation reveals only partial geometry and motion evidence. Most feed-forward methods infer …

Professional design requires any-color control: the ability to specify an object's target color with any 24-bit hex value for image generation and editing. Prior work has explored …

Hereditary polyposis syndromes can be precursor lesions to colorectal cancer and are associated with a broad spectrum of extracolonic tumors. Early identification and accurate clas…

Pretraining a neural PDE surrogate can reduce the amount of new CFD data needed when geometry or modeled physics changes. However, it remains unclear how different components of di…

提出量化前沿LLM智能体过度宣称倾向的方法，直击自主编码智能体长期运行中成果报告可信度这一核心安全问题，对智能体可靠性评估至关重要。

Frontier coding agents are increasingly trusted to work autonomously for long periods, yet an agent's final response is often the only account of that work a user sees. We quantify…

针对大语言模型强化学习中训练与推理引擎差异导致的敏感性问题，提出分数中心化方法稳定离策略RL，对提升LLM后训练稳定性有重要价值。

Reinforcement learning (RL) of large language models is notoriously sensitive to small differences between training and inference engines, often referred to as the training-inferen…

系统研究编码智能体的harness设计如何影响长程软件工程表现，为构建更可靠的自主编程智能体提供关键实证依据，对当前智能体工程实践具有直接指导意义。

Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing work typically evaluates harnesses…

Generative models are increasingly used to solve scientific inverse problems, but existing evaluations still focus primarily on whether a method can produce a single plausible reco…

解决多轮智能体RL中仅靠单一标量奖励导致信用分配困难的问题，提出自退出的在策略蒸馏方法，为智能体强化学习训练提供新思路。

Multi-turn agents trained with reinforcement learning (RL) receive a single scalar reward per trajectory, which motivates self on-policy distillation (OPD) to supply dense token-le…