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 language | English |
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| Title of host publication | System Demonstrations |
| Editors | Pushkar Mishra, Smaranda Muresan, Tao Yu |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 167-177 |
| Number of pages | 11 |
| ISBN (Electronic) | 9798891762534 |
| DOIs | |
| State | Published - 2025 |
| Event | 63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025 - Vienna, Austria Duration: 27 Jul 2025 → 1 Aug 2025 |
Publication series
| Name | Proceedings of the Annual Meeting of the Association for Computational Linguistics |
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| Volume | 3 |
| ISSN (Print) | 0736-587X |
Conference
| Conference | 63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025 |
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| Country/Territory | Austria |
| City | Vienna |
| Period | 27/07/25 → 1/08/25 |
Bibliographical note
Publisher Copyright:©2025 Association for Computational Linguistics.