HAVE uses head-adaptive gating and value calibration to build token evidence and fuse it with the LM distribution, yielding modest QA gains over DAGCD.
Retrieval-augmented generation for knowledge- intensive nlp tasks
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HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models
HAVE uses head-adaptive gating and value calibration to build token evidence and fuse it with the LM distribution, yielding modest QA gains over DAGCD.