mlsanityData to 14 Oct 2026

FAMuS: Frames Across Multiple Sources

arXiv 2311.05601 ↗First posted 9 Nov 2023cs.CLcited by 2

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Abstract (arXiv)

Understanding event descriptions is a central aspect of language processing, but current approaches focus overwhelmingly on single sentences or documents. Aggregating information about an event across documents can offer a much richer understanding. To this end, we present FAMuS, a new corpus of Wikipedia passages that report on some event, paired with underlying, genre-diverse (non-Wikipedia) source articles for the same event. Events and (cross-sentence) arguments in both report and source are annotated against FrameNet, providing broad coverage of different event types. We present results on two key event understanding tasks enabled by FAMuS: source validation -- determining whether a document is a valid source for a target report event -- and cross-document argument extraction -- full-document argument extraction for a target event from both its report and the correct source article. We release both FAMuS and our models to support further research.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 28 of its 72 references that are in the map. First posted on arXiv 9 Nov 2023.

Builds on

28 of 72 references.

References · 28

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16 more
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Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2025WikiVideo: Article Generation from Multiple Videoscited by 13
  2. 2024A Survey of Video Datasets for Grounded Event Understandingcited by 9