3 papers
cs.LG2026
IPD: Boosting Sequential Policy with Imaginary Planning Distillation in Offline Reinforcement Learning
Yihao Qin, Yuanfei Wang, Hang Zhou +3
Decision transformer based sequential policies have emerged as a powerful paradigm in offline reinforcement learning (RL), yet their efficacy remains constrained by the quality of…
cs.RO2025
InternData-A1: Pioneering High-Fidelity Synthetic Data for Pre-training Generalist Policy
Yang Tian, Yuyin Yang, Yiman Xie +13
Recent works explore how real and synthetic data contribute to Vision-Language-Action (VLA) models' generalization. While current VLA models have shown the strong effectiveness of…
cs.RO2024
Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation
Yang Tian, Sizhe Yang, Jia Zeng +4
Current efforts to learn scalable policies in robotic manipulation primarily fall into two categories: one focuses on "action," which involves behavior cloning from extensive colle…