Yu-Hui Wang

Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning

Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across turns. Although end-to-end training in agentic environments can improve such multi-turn decision-making abilities, current methods mainly rely on either token-wise opti...