LEARNING TO REASON WITHOUT EXTERNAL REWARDS

Summary from the TLDR AI newsletter

INTUITOR is a reinforcement learning method that uses an LLM's internal confidence level as a reward signal instead of costly domain-specific supervision. The resulting models match performance on math benchmarks while achieving superior generalization on coding tasks, offering a potential alternative to current RL methods that struggle without verifiable rewards.