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arXiv Computation and Language By Jingfeng Chen, Raghuveer Thirukovalluru, Junlin Wang, Kaiwei Luo, Bhuwan Dhingra

Atomic Consistency Preference Optimization for Long-Form Question Answering

Read the original on arXiv Computation and Language →

Atomic Consistency Preference Optimization (ACPO) is a self‑supervised preference‑tuning method that improves factual accuracy in large language models without external supervision. It uses atomic consistency signals—agreement of individual facts across multiple stochastic responses—to identify high‑ and low‑quality data pairs for model alignment. ACPO outperforms a strong supervised alignment baseline by 1.95 points on the LongFact and BioGen datasets for Phi‑3 and Llama‑3 models.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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