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AI Summary
- Nathan Lambert discusses evolution from RLHF to RLVR (Reinforcement Learning with Verifiable Rewards) in Tulu 3 paper for tasks with clear success criteria
- RLVR leverages deterministic, objective reward signals for math, code correctness, and instruction-following instead of relying solely on subjective human feedback
- Tulu model series positioned as reproducible, state-of-the-art post-training recipe; RLVR still rapidly evolving regarding tool use and multi-step reasoning