Papers with summary factuality
Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality (2023.acl-short)
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| Challenge: | Recent studies have shown that most abstractive summarization models are unfaithful and suffer from a wide range of hallucination. |
| Approach: | They propose a candidate summary generation and ranking technique to improve summary factuality without sacrificing quality. |
| Outcome: | The proposed method shows that the model trained using the proposed method improves on factuality and similarity-based metrics without conflicting with the model. |