arXiv 论文速递

Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action (VLA) tools under the guidanc…

Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors trained on one geometry family frequently fail to beat parameter-free…

系统研究示范数据质量在VLA预训练中的作用，给出基准与实证结论，为机器人策略预训练的数据筛选提供关键指导。

How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We compare weighting, filtering, and …

长时程智能体训练缺乏可扩展环境与稠密奖励信号，本文提出稠密进度奖励来扩展环境，对自主智能体从小时级到天级任务的能力提升至关重要。

Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a capability essential to automated…

Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative samplers that can produce indep…

Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existing ways to shorten the CoT requi…

Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the outputs are structured, editable, and verifiable. Yet code mod…

探索超越自然语言、但仍以语言与环境交互的智能体推理范式，为构建更通用的具身与工具使用智能体提供新思路。

How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and interact through text, while …

Persistent homology summarizes the topological evolution of a graph as persistence diagrams (PDs). Generating graphs whose topology matches a target descriptor is increasingly impo…

揭示RLVR中大批量rollout学习更慢却按时失效的双时钟现象，为可验证奖励强化学习的批量与调度设计提供理论解释。

Reinforcement learning with verifiable rewards (RLVR) relies on costly model-generated responses, motivating larger rollout batches and square-root learning-rate scaling. Reported …

Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule to simultaneously improve multiple properties while maintaining …

针对相机移位、重装等硬件变化，建立VLA鲁棒性基准，填补部署环境泛化评估空白，对真实机器人落地意义重大。

Robot policies are expected to generalize across deployment environments, including variations in the robot itself: cameras are bumped and remounted, calibrations drift, controller…