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SummIt: Iterative Text Summarization via ChatGPT

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arxiv 2305.14835 v2 pith:B3WYLAMP submitted 2023-05-24 cs.CL

Haopeng Zhang , Xiao Liu , Jiawei Zhang This is my paper · ORCID
classification cs.CL
keywords summarizationframeworkiterativesummarytextchatgptgeneratedpotential
verification ladder T0 review T1 audit T2 compute T3 formal
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Text summarization systems have made significant progress in recent years, but typically generate summaries in one single step. However, the one-shot summarization setting is sometimes inadequate, as the generated summary may contain hallucinations or overlook essential details related to the reader's interests. This paper addresses this limitation by proposing SummIt, an iterative text summarization framework based on large language models like ChatGPT. Our framework enables the model to refine the generated summary iteratively through self-evaluation and feedback, resembling humans' iterative process when drafting and revising summaries. Furthermore, we explore the potential benefits of integrating knowledge and topic extractors into the framework to enhance summary faithfulness and controllability. We automatically evaluate the performance of our framework on three benchmark summarization datasets. We also conduct a human evaluation to validate the effectiveness of the iterative refinements and identify a potential issue of over-correction.

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Cited by 5 Pith papers

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