6 papers
One Demonstration Is Enough for Real-World Robotic Reinforcement Learning
Yuwan Liu, Hongze Yu, Song Liu +5
Learning effective robot control policies on physical hardware is challenging due to costly data collection and the difficulty of reward specification. Prior work has incorporated…
System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma +16
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-ma…
Beyond Self-Interest: Modeling Social-Oriented Motivation for Human-like Multi-Agent Interactions
Jingzhe Lin, Ceyao Zhang, Yaodong Yang +3
Large Language Models (LLMs) demonstrate significant potential for generating complex behaviors, yet most approaches lack mechanisms for modeling social motivation in human-like mu…
Does LLM Alignment Really Need Diversity? An Empirical Study of Adapting RLVR Methods for Moral Reasoning
Zhaowei Zhang, Xiaohan Liu, Xuekai Zhu +6
Reinforcement learning with verifiable rewards (RLVR) has achieved remarkable success in logical reasoning tasks, yet whether large language model (LLM) alignment requires fundamen…
DexKnot: Generalizable Visuomotor Policy Learning for Dexterous Bag-Knotting Manipulation
Jiayuan Zhang, Ruihai Wu, Haojun Chen +5
Knotting plastic bags is a common task in daily life, yet it is challenging for robots due to the bags' infinite degrees of freedom and complex physical dynamics. Existing methods…
DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Grasping
Yifan Zhong, Xuchuan Huang, Ruochong Li +9
Dexterous grasping remains a fundamental yet challenging problem in robotics. A general-purpose robot must be capable of grasping diverse objects in arbitrary scenarios. However, e…