Paper summary
Paper summary: Reinforcement Pre-Training
Reinforcement Pre-Training reframes next-token prediction as a reasoning task: the model reasons before predicting the next token and gets a verifiable reward when it's right, so ordinary text becomes RL training data.
- Every next token in a corpus becomes a small verifiable RL problem: reason, then predict, then get rewarded if correct.
- This lets general web-scale text feed RL, instead of only domain-specific Q&A sets.