Survey on Factuality in LLMs
First page

Paper summary
A survey covering evaluation and enhancement techniques for LLM factuality.
Ask this paper
01
Evaluation taxonomy: Organizes factuality evaluation by granularity (token, sentence, passage), task (QA, generation, dialogue), and reference availability.
02
Enhancement taxonomy: Reviews enhancement techniques including better training data, retrieval augmentation, factuality-aware decoding, and post-hoc verification.
03
Factuality vs. truthfulness: Clarifies the often-confused distinction between factuality (correct facts) and truthfulness (model reports its beliefs honestly).
04
Open problems: Highlights persistent gaps in cross-lingual factuality, open-ended generation factuality, and calibration.