Papers with FIZZ

1 papers
FIZZ: Factual Inconsistency Detection by Zoom-in Summary and Zoom-out Document (2024.emnlp-main)

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Challenge: Existing methods for evaluating factual consistency in abstractive summarization systems have significant limitations, especially on refinement and interpretability.
Approach: They propose a method for detecting summary factual inconsistency based on fine-grained atomic facts decomposition and adaptive granularity expansion.
Outcome: The proposed method outperforms existing systems on the AGGREFACT benchmark dataset and achieves state-of-the-art performance.

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