Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
What Can RL Bring to VLA Generalization? An Empirical Study
Jijia Liu, Feng Gao, Bingwen Wei +5
Large Vision-Language Action (VLA) models have shown significant potential for embodied AI. However, their predominant training via supervised fine-tuning (SFT) limits generalizati…
cs.LG2025
Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance
Songsheng Wang, Rucheng Yu, Zhihang Yuan +4
Vision-Language-Action (VLA) models have made substantial progress by leveraging the robust capabilities of Visual Language Models (VLMs). However, VLMs' significant parameter size…
cs.LG2025
Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
Jijia Liu, Feng Gao, Qingmin Liao +2
Reinforcement learning (RL) for continuous control often requires large amounts of online interaction data. Value-based RL methods can mitigate this burden by offering relatively h…