Who is answering to whom? Modeling reply-to relationships in Russian asynchronous chats


Sochenkov I.


The study highlights the asynchronous nature of modern group chats and related problems such as retrieving relevant information on the asked question and understanding reply-to relationships. In this work, we formalize the reply recovery task as a building block toward solving described problems. Using simple heuristics, we try to apply the result reply recovery model to a thread reconstruction problem. As a result, we show that modern pre-trained models such as BERT show great results on the task of reply recovery compared to more simple models, though it cannot be applied to thread reconstruction with just simple heuristics. In addition, experiments have shown that model performance depends on the chat domain. We open-sourced a model that can automatically predict which message the particular reply responds to and provide a representative Russian dataset that we built from Telegram chats of different domains. We also provide a test set for a thread reconstruction task.

External links

DOI: 10.28995/2075-7182-2023-22-1052-1060

Download article (PDF) at the Dialogue 2023 website: https://www.dialog-21.ru/media/5871/buyanoviplusetal046.pdf

Download conference proceedings (PDF) at the Dialogue 2023 website: https://www.dialog-21.ru/media/6033/dialog2023rinzlr.pdf

Download article (PDF) from eLibrary (registration required): https://elibrary.ru/item.asp?id=54231177

Reference link

Buyanov, I., Yas'kova, D., Sochenkov, I. Who is answering to whom? Modeling reply-to relationships in Russian asynchronous chats // Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference “Dialogue 2023”. June 14–16, 2023. Pp. 1052-1060.