1 citations · 1 across the 5 of their papers we have counts for
5 papers
Execution-Verified Reinforcement Learning for Optimization Modeling
Runda Guan, Xiangqing Shen, Jiajun Zhang +3
Automating optimization modeling with LLMs is a promising path toward scalable decision intelligence, but existing approaches either rely on agentic pipelines built on closed-sourc…
RoboNeuron: A Middle-Layer Infrastructure for Agent-Driven Orchestration in Embodied AI
Weifan Guan, Qinghao Hu, Huasen Xi +3
Vision-language-action (VLA) models and LLM agents have advanced rapidly, yet reliable deployment on physical robots is often hindered by an interface mismatch between agent tool A…
Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey
Weifan Guan, Qinghao Hu, Aosheng Li +1
Vision-Language-Action (VLA) models extend vision-language models to embodied control by mapping natural-language instructions and visual observations to robot actions. Despite the…
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong, Jian Cheng, Xi Sheryl Zhang
The Soft Actor-Critic (SAC) algorithm with a Gaussian policy has become a mainstream implementation for realizing the Maximum Entropy Reinforcement Learning (MaxEnt RL) objective,…
We Choose to Go to Space: Agent-driven Human and Multi-Robot Collaboration in Microgravity
Miao Xin, Zhongrui You, Zihan Zhang +7
We present SpaceAgents-1, a system for learning human and multi-robot collaboration (HMRC) strategies under microgravity conditions. Future space exploration requires humans to wor…