New Research Reveals Flaws in KL Estimators for LLM RL Training

Recent preprints reveal that common reverse KL estimators used in LLM reinforcement learning, such as the K3 estimator used in DeepSeek, provide incorrect gradients. The studies show that K1 can suffer from near-zero gradients, highlighting critical implementation pitfalls in RL training.

2026-07-25 ~ 2026-07-26 · 4 related posts

• RL KL estimators may optimize the wrong direction, and k1 can collapse to zero gradient — auto_grad_ · 2026-07-25
• RLVR preprint finds only one reverse-KL estimator stays unbiased in LLM fine-tuning — heghbalz · 2026-07-26
• Paper finds common KL estimators in LLM RL can produce the wrong gradients — burny_tech · 2026-07-26
• New RL paper flags two common mistakes in KL-gradient estimation for LLM training — kastnerkyle · 2026-07-26