Papers › FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

23 May 2023arXiv:2305.14251archive 2025-07-28

Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi

Evaluating the factuality of long-form text generated by large language models (LMs) is non-trivial because (1) generations often contain a mixture of supported and unsupported pieces of information, making binary judgments of quality inadequate, and (2) human evaluation is time-consuming and costly. In this paper, we introduce FACTSCORE, a new evaluation that breaks a generation into a series of atomic facts and computes the percentage of atomic facts supported by a reliable knowledge source. We conduct an extensive human evaluation to obtain FACTSCOREs of people biographies generated by several state-of-the-art commercial LMs -- InstructGPT, ChatGPT, and the retrieval-augmented PerplexityAI -- and report new analysis demonstrating the need for such a fine-grained score (e.g., ChatGPT only achieves 58%). Since human evaluation is costly, we also introduce an automated model that estimates FACTSCORE using retrieval and a strong language model, with less than a 2% error rate. Finally, we use this automated metric to evaluate 6,500 generations from a new set of 13 recent LMs that would have cost $26K if evaluated by humans, with various findings: GPT-4 and ChatGPT are more factual than public models, and Vicuna and Alpaca are some of the best public models. FACTSCORE is available for public use via `pip install factscore`.

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shmsw25/factscore officialmentioned in papermentioned on GitHubpytorchMIT report
freshllms/freshqa mentioned on GitHubApache-2.0 report
tatsu-lab/linguistic_calibration mentioned on GitHubpytorch report

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best_demos shmsw25/factscore/factscore/atomic_facts.py official repository ran MIT (permissive) · 510528f4db1006bc · report
call_ChatGPT shmsw25/factscore/factscore/openai_lm.py official repository ran MIT (permissive) · 6c0eab0d68ea3036 · report
call_GPT3 shmsw25/factscore/factscore/openai_lm.py official repository ran MIT (permissive) · e5bb87d92ea99a8b · report
get_memory_footprint shmsw25/factscore/factscore/utils.py official repository ran MIT (permissive) · f06c53e363e1ebaa · report
is_invalid_paragraph_ppl shmsw25/factscore/factscore/abstain_detection.py official repository ran MIT (permissive) · 8eb846a8e76a79b8 · report
is_invalid_ppl shmsw25/factscore/factscore/abstain_detection.py official repository ran MIT (permissive) · 672bd38d830be48d · report
normalize_answer shmsw25/factscore/factscore/atomic_facts.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 6a96435eba311b08 · report
remove_citation shmsw25/factscore/factscore/abstain_detection.py official repository ran fingerprinted MIT (permissive) · 3635046105ae0fce · report
text_to_sentences shmsw25/factscore/factscore/atomic_facts.py official repository ran fingerprinted MIT (permissive) · 13867f872a481bd3 · report
convert_model_to_int8_on_gpu shmsw25/factscore/factscore/utils.py official repository unverified MIT (permissive) · 7e4c366c4dbf9568 · report
recover_instruct_llama shmsw25/factscore/factscore/download_data.py official repository unverified MIT (permissive) · 02c83d89394be1c7 · report
softmax shmsw25/factscore/factscore/npm.py official repository unverified MIT (permissive) · 925c59b7e44138ab · report
Retrieval tatsu-lab/linguistic_calibration/src/linguistic_calibration/auto_annotations/factscore_retrieval_utils.py community (archive-listed) ran Apache-2.0 (permissive) · 7ad7a356ddeef1cb · report
DocDB tatsu-lab/linguistic_calibration/src/linguistic_calibration/auto_annotations/factscore_retrieval_utils.py community (archive-listed) unverified Apache-2.0 (permissive) · c4456232ee580c04 · report
FactScorer tatsu-lab/linguistic_calibration/src/linguistic_calibration/auto_annotations/factscore_retrieval_utils.py community (archive-listed) unverified Apache-2.0 (permissive) · d14a268e400630cf · report

Tasks

FormLanguage ModellingRetrievalText Generation

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Methods

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutGPT-4Label SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

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