Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning.

arXiv:2602.14868v3 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in language models. However, relying on sparse rewards makes this process highly sample-inefficient, as mod