2026
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
ICML 2026spotlight
Designing dense rewards is crucial for reinforcement learning (RL), yet in robotics it often demands extensive manual effort and lacks scalability. One promising solution is to view task progress as a dense reward signal, as it quantifies the degree to which actions advance the system toward task co…