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cs.CL2024
DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text Generation
Miriam Wanner, Benjamin Van Durme, Mark Dredze
The decompose-then-verify strategy for verification of Large Language Model (LLM) generations decomposes claims that are then independently verified. Decontextualization augments t…
cs.CL2024
Core: Robust Factual Precision with Informative Sub-Claim Identification
Zhengping Jiang, Jingyu Zhang, Nathaniel Weir +6
Hallucinations pose a challenge to the application of large language models (LLMs) thereby motivating the development of metrics to evaluate factual precision. We observe that popu…
cs.CL2024
A Closer Look at Claim Decomposition
Miriam Wanner, Seth Ebner, Zhengping Jiang +2
As generated text becomes more commonplace, it is increasingly important to evaluate how well-supported such text is by external knowledge sources. Many approaches for evaluating t…