3 papers
cs.RO2026
Open-Loop Planning, Closed-Loop Verification: Speculative Verification for VLA
Zihua Wang, Zhitao Lin, Ruibo Li +4
Vision-Language-Action (VLA) models, as large foundation models for embodied control, have shown strong performance in manipulation tasks. However, their performance comes at high…
cs.LG2026
OPRIDE: Offline Preference-based Reinforcement Learning via In-Dataset Exploration
Yiqin Yang, Hao Hu, Yihuan Mao +10
Preference-based reinforcement learning (PbRL) can help avoid sophisticated reward designs and align better with human intentions, showing great promise in various real-world appli…
cs.RO2024
DaDu-E: Rethinking the Role of Large Language Model in Robotic Computing Pipeline
Wenhao Sun, Sai Hou, Zixuan Wang +6
Performing complex tasks in open environments remains challenging for robots, even when using large language models (LLMs) as the core planner. Many LLM-based planners are ineffici…