DARLING: diversity-aware RL beats standard RL on both quality and diversity
DanielKhashabi · x · 2026-09-25
- Jason Weston's team introduces DARLING (Diversity Aware RL), tackling the repetition problem amplified by post-training by jointly optimizing response diversity and quality in online RL.
- The method uses a learned partition function to balance quality and diversity.
- It outperforms standard RL on both axes (e.g. higher pass@1/pass@k) and works for both verifiable and non-verifiable tasks.
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