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arxiv logo>cs> arXiv:2411.06524
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Computer Science > Artificial Intelligence

arXiv:2411.06524 (cs)
[Submitted on 10 Nov 2024]

Title:Does This Summary Answer My Question? Modeling Query-Focused Summary Readers with Rational Speech Acts

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Abstract:Query-focused summarization (QFS) is the task of generating a summary in response to a user-written query. Despite its user-oriented nature, there has been limited work in QFS in explicitly considering a user's understanding of a generated summary, potentially causing QFS systems to underperform at inference time. In this paper, we adapt the Rational Speech Act (RSA) framework, a model of human communication, to explicitly model a reader's understanding of a query-focused summary and integrate it within the generation method of existing QFS systems. In particular, we introduce the answer reconstruction objective which approximates a reader's understanding of a summary by their ability to use it to reconstruct the answer to their initial query. Using this objective, we are able to re-rank candidate summaries generated by existing QFS systems and select summaries that better align with their corresponding query and reference summary. More generally, our study suggests that a simple and effective way of improving a language generation system designed for a user-centered task may be to explicitly incorporate its user requirements into the system's generation procedure.
Subjects:Artificial Intelligence (cs.AI)
Cite as:arXiv:2411.06524 [cs.AI]
 (orarXiv:2411.06524v1 [cs.AI] for this version)
 https://doi.org/10.48550/arXiv.2411.06524
arXiv-issued DOI via DataCite

Submission history

From: Cesare Spinoso-Di Piano [view email]
[v1] Sun, 10 Nov 2024 16:48:21 UTC (2,144 KB)
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