Noisy Data Disrupts RLVR: High-Quality Data Remains Irreplaceable

A new study reveals that noisy data significantly degrades RLVR training, disproving prior claims that models can learn from mislabeled data. The authors emphasize that high-quality data remains strictly essential, as RLVR is not a shortcut for improving reasoning.

2026-08-04 ~ 2026-08-04 · 3 related posts

• RLVR alone won’t unlock stronger reasoning, the authors say high-quality data still matters more — ddkang · 2026-08-04
• Noisy data breaks RLVR: Qwen2.5-Math-7B loses 9% on truly incorrect labels — ddkang · 2026-08-04

1 near-duplicate retellings: ddkang