DiSCo: Making Absence Visible in Intelligent Summarization Interfaces
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866915727543369728 |
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| author | Fainman, Eran Shoshan, Hagit Ben Solomon, Adir Mokryn, Osnat |
| author_facet | Fainman, Eran Shoshan, Hagit Ben Solomon, Adir Mokryn, Osnat |
| contents | Intelligent interfaces increasingly use large language models to summarize user-generated content, yet these summaries emphasize what is mentioned while overlooking what is missing. This presence bias can mislead users who rely on summaries to make decisions. We present Domain Informed Summarization through Contrast (DiSCo), an expectation-based computational approach that makes absences visible by comparing each entity's content with domain topical expectations captured in reference distributions of aspects typically discussed in comparable accommodations. This comparison identifies aspects that are either unusually emphasized or missing relative to domain norms and integrates them into the generated text. In a user study across three accommodation domains, namely ski, beach, and city center, DiSCo summaries were rated as more detailed and useful for decision making than baseline large language model summaries, although slightly harder to read. The findings show that modeling expectations reduces presence bias and improves both transparency and decision support in intelligent summarization interfaces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07229 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | DiSCo: Making Absence Visible in Intelligent Summarization Interfaces Fainman, Eran Shoshan, Hagit Ben Solomon, Adir Mokryn, Osnat Human-Computer Interaction Artificial Intelligence Information Retrieval Intelligent interfaces increasingly use large language models to summarize user-generated content, yet these summaries emphasize what is mentioned while overlooking what is missing. This presence bias can mislead users who rely on summaries to make decisions. We present Domain Informed Summarization through Contrast (DiSCo), an expectation-based computational approach that makes absences visible by comparing each entity's content with domain topical expectations captured in reference distributions of aspects typically discussed in comparable accommodations. This comparison identifies aspects that are either unusually emphasized or missing relative to domain norms and integrates them into the generated text. In a user study across three accommodation domains, namely ski, beach, and city center, DiSCo summaries were rated as more detailed and useful for decision making than baseline large language model summaries, although slightly harder to read. The findings show that modeling expectations reduces presence bias and improves both transparency and decision support in intelligent summarization interfaces. |
| title | DiSCo: Making Absence Visible in Intelligent Summarization Interfaces |
| topic | Human-Computer Interaction Artificial Intelligence Information Retrieval |
| url | https://arxiv.org/abs/2601.07229 |