Researchers Debate RL Entropy Collapse as Potential Energy Loss and SFT Re-injection

Researchers discuss RL entropy collapse, with tensorqt arguing there is no sample-efficient fix and framing it as consumed 'potential energy' that can be re-injected via SFT-souping-RL cycles, while others suggest fixing the collapse itself may remove the need for SFT re-injection.

2026-10-07 ~ 2026-10-07 · 4 related posts

• RL Practitioner Postmortem: Alternating SFT, Souping and RL Yields a Good Explore-Exploit Cycle — tensorqt · 2026-10-07
• Entropy Collapse May Not Need SFT Reinsertion; Souping in Pretraining Works Surprisingly Well — ar0cket1 · 2026-10-07
• Fixing RL collapse: 59 SFT steps to reinject exploration 'potential energy', researcher says — tensorqt · 2026-10-07
• Entropy Collapse as Spent Potential Energy: Rethinking Exploration Loss in RL Training — tensorqt · 2026-10-07