Anqi Li

Learning robotic reward functions from a million trajectories reveals that comparing entire trajectories, not just individual frames, unlocks better generalization and learning from suboptimal data.

LLMs can now predict client-perceived therapeutic alliance with significantly higher accuracy and provide interpretable rationales, bridging the gap between counselor evaluations and client experiences.