Survey on Factuality in LLMs
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A survey covering evaluation and enhancement techniques for LLM factuality.
Evaluation taxonomy: Organizes factuality evaluation by granularity (token, sentence, passage), task (QA, generation, dialogue), and reference availability.
Enhancement taxonomy: Reviews enhancement techniques including better training data, retrieval augmentation, factuality-aware decoding, and post-hoc verification.
Factuality vs. truthfulness: Clarifies the often-confused distinction between factuality (correct facts) and truthfulness (model reports its beliefs honestly).
Open problems: Highlights persistent gaps in cross-lingual factuality, open-ended generation factuality, and calibration.
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