{"ID":2878992,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.17489","arxiv_id":"2508.17489","title":"A Dynamic Approach to Collaborative Document Writing (Full Version)","abstract":"We introduce a model for collaborative text aggregation in which an agent community coauthors a document, modeled as an unordered collection of paragraphs, using a dynamic mechanism: agents propose paragraphs and vote on those suggested by others. We formalize the setting and explore its realizations, concentrating on voting mechanisms that aggregate votes into a single, dynamic document. We focus on two desiderata: the eventual stability of the process and its expected social welfare. Following an impossibility result, we describe several aggregation methods and report on agent-based simulations that utilize natural language processing (NLP) and large-language models (LLMs) to model agents and their contexts. Using these simulations, we demonstrate promising results regarding the possibility of rapid convergence to a high social welfare collaborative text.","short_abstract":"We introduce a model for collaborative text aggregation in which an agent community coauthors a document, modeled as an unordered collection of paragraphs, using a dynamic mechanism: agents propose paragraphs and vote on those suggested by others. We formalize the setting and explore its realizations, concentrating on...","url_abs":"https://arxiv.org/abs/2508.17489","url_pdf":"https://arxiv.org/pdf/2508.17489v2","authors":"[\"Avital Finanser\",\"Nimrod Talmon\"]","published":"2025-08-24T18:47:16Z","proceeding":"cs.GT","tasks":"[\"cs.GT\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}