Hasty Briefsbeta

Binary Retrieval-Augmented Reward Mitigates Hallucinations

a day ago
  • #hallucination-mitigation
  • #language-models
  • #reinforcement-learning
  • Proposes a binary retrieval-augmented reward (RAR) method to mitigate hallucinations in language models.
  • Achieves a 39.3% reduction in hallucination rates for open-ended generation.
  • Enables calibrated abstention in short-form question answering, reducing incorrect answers by 44.4% on PopQA and 21.7% on GPQA.
  • Maintains performance on instruction following, math, and coding tasks without degradation.
  • Outperforms supervised training and continuous-reward RL baselines in factuality.