mlsanityData to 14 Oct 2026

Where did you get that? Towards Summarization Attribution for Analysts

arXiv 2511.08589 ↗First posted 28 Oct 2025cs.CL cs.AIcited by 0

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Abstract (arXiv)

Analysts require attribution, as nothing can be reported without knowing the source of the information. In this paper, we will focus on automatic methods for attribution, linking each sentence in the summary to a portion of the source text, which may be in one or more documents. We explore using a hybrid summarization, i.e., an automatic paraphrase of an extractive summary, to ease attribution. We also use a custom topology to identify the proportion of different categories of attribution-related errors.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). First posted on arXiv 28 Oct 2025.

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