The ShareLM Collection and Plugin: Contributing Human-Model Chats for the Benefit of the Community

Shachar Don-Yehiya, Leshem Choshen, Omri Abend

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Human-model conversations provide a window into users’ real-world scenarios, behavior, and needs, and thus are a valuable resource for model development and research. While for-profit companies collect user data through the APIs of their models, using it internally to improve their own models, the open source and research community lags behind. We introduce the ShareLM collection, a unified set of human conversations with large language models, and its accompanying plugin, a Web extension for voluntarily contributing user-model conversations. Where few platforms share their chats, the ShareLM plugin adds this functionality, thus, allowing users to share conversations from most platforms. The plugin allows the user to rate their conversations, both at the conversation and the response levels, and delete conversations they prefer to keep private before they ever leave the user’s local storage. We release the plugin conversations as part of the ShareLM collection, and call for more community effort in the field of open human-model data.

Original languageEnglish
Title of host publicationSystem Demonstrations
EditorsPushkar Mishra, Smaranda Muresan, Tao Yu
PublisherAssociation for Computational Linguistics (ACL)
Pages167-177
Number of pages11
ISBN (Electronic)9798891762534
DOIs
StatePublished - 2025
Event63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025 - Vienna, Austria
Duration: 27 Jul 20251 Aug 2025

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume3
ISSN (Print)0736-587X

Conference

Conference63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025
Country/TerritoryAustria
CityVienna
Period27/07/251/08/25

Bibliographical note

Publisher Copyright:
©2025 Association for Computational Linguistics.

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