Ruan, Qian ; Kuznetsov, Ilia ; Gurevych, Iryna (2024)
Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision.
62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand (11.08.2024 - 16.08.2024)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Collaborative review and revision of textual documents is the core of knowledge work and a promising target for empirical analysis and NLP assistance. Yet, a holistic framework that would allow modeling complex relationships between document revisions, reviews and author responses is lacking. To address this gap, we introduce Re3, a framework for joint analysis of collaborative document revision. We instantiate this framework in the scholarly domain, and present Re3-Sci, a large corpus of aligned scientific paper revisions manually labeled according to their action and intent, and supplemented with the respective peer reviews and human-written edit summaries. We use the new data to provide first empirical insights into collaborative document revision in the academic domain, and to assess the capabilities of state-of-the-art LLMs at automating edit analysis and facilitating text-based collaboration. We make our annotation environment and protocols, the resulting data and experimental code publicly available.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Ruan, Qian ; Kuznetsov, Ilia ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision |
| Sprache: | Englisch |
| Publikationsjahr: | August 2024 |
| Verlag: | ACL |
| Buchtitel: | Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) |
| Veranstaltungstitel: | 62nd Annual Meeting of the Association for Computational Linguistics |
| Veranstaltungsort: | Bangkok, Thailand |
| Veranstaltungsdatum: | 11.08.2024 - 16.08.2024 |
| URL / URN: | https://aclanthology.org/2024.acl-long.255/ |
| Kurzbeschreibung (Abstract): | Collaborative review and revision of textual documents is the core of knowledge work and a promising target for empirical analysis and NLP assistance. Yet, a holistic framework that would allow modeling complex relationships between document revisions, reviews and author responses is lacking. To address this gap, we introduce Re3, a framework for joint analysis of collaborative document revision. We instantiate this framework in the scholarly domain, and present Re3-Sci, a large corpus of aligned scientific paper revisions manually labeled according to their action and intent, and supplemented with the respective peer reviews and human-written edit summaries. We use the new data to provide first empirical insights into collaborative document revision in the academic domain, and to assess the capabilities of state-of-the-art LLMs at automating edit analysis and facilitating text-based collaboration. We make our annotation environment and protocols, the resulting data and experimental code publicly available. |
| Freie Schlagworte: | UKP_p_PEER, UKP_p_InterText |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung |
| Hinterlegungsdatum: | 20 Aug 2024 09:01 |
| Letzte Änderung: | 20 Aug 2024 09:01 |
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