Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning
This work proposes HyGAE, an actor-critic framework that jointly optimizes token- and turn-level objectives with the hybrid advantage and unified critic and provides an in-depth analysis showing that the exact analytic form of the hybrid advantage and return is crucial for optimization.