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WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset

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arxiv 2305.05432 v1 pith:QMTCI3JR submitted 2023-05-09 cs.CL cs.CV

Andrea Burns , Krishna Srinivasan , Joshua Ainslie , Geoff Brown , Bryan A. Plummer , Kate Saenko , Jianmo Ni , Mandy Guo This is my paper · ORCID
classification cs.CLcs.CV
keywords taskswebpagewikiweb2mdatamultimodalpagetextwebpages
verification ladder T0 review T1 audit T2 compute T3 formal
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Webpages have been a rich resource for language and vision-language tasks. Yet only pieces of webpages are kept: image-caption pairs, long text articles, or raw HTML, never all in one place. Webpage tasks have resultingly received little attention and structured image-text data underused. To study multimodal webpage understanding, we introduce the Wikipedia Webpage 2M (WikiWeb2M) suite; the first to retain the full set of images, text, and structure data available in a page. WikiWeb2M can be used for tasks like page description generation, section summarization, and contextual image captioning.

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  1. MRAMG-Bench: A Comprehensive Benchmark for Advancing Multimodal Retrieval-Augmented Multimodal Generation

    cs.LG 2025-02 conditional novelty 6.0 of 10

    A human-annotated benchmark with 4,800 QA pairs evaluates how well AI models can retrieve and generate interleaved text-and-image answers.

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