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WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse

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arxiv 1808.09422 v1 pith:BAJMAG2Z submitted 2018-08-28 cs.CL

Manaal Faruqui , Ellie Pavlick , Ian Tenney , Dipanjan Das This is my paper · ORCID
classification cs.CL
keywords editscorpusdiscourselanguagecontiguousmodelsphraserelease
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We release a corpus of 43 million atomic edits across 8 languages. These edits are mined from Wikipedia edit history and consist of instances in which a human editor has inserted a single contiguous phrase into, or deleted a single contiguous phrase from, an existing sentence. We use the collected data to show that the language generated during editing differs from the language that we observe in standard corpora, and that models trained on edits encode different aspects of semantics and discourse than models trained on raw, unstructured text. We release the full corpus as a resource to aid ongoing research in semantics, discourse, and representation learning.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. NewsEdits 2.0: Learning the Intentions Behind Updating News

    cs.CL 2024-11 conditional novelty 6.0 of 10

    NewsEdits 2.0 introduces an edit-intention taxonomy and text-based models that predict factual updates in news revisions, enabling LLMs to abstain from answering with outdated facts at near-oracle accuracy.

  2. AI4Research: A Survey of Artificial Intelligence for Scientific Research

    cs.CL 2025-07 conditional novelty 4.0 of 10

    A survey that organizes AI-for-research work into five tasks, comprehension, survey, discovery, writing, and peer review, and compiles associated tools and benchmarks.

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