A Survey of Challenges and Methods in the Computational Modeling of Multi-Party Dialog

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Abstract

Advances in conversational AI systems, powered in particular by large language models, have facilitated rapid progress in understanding and generating dialog. Typically, task-oriented or open-domain dialog systems have been designed to work with two-party dialog, i.e., the exchange of utterances between a single user and a dialog system. However, modern dialog systems may be deployed in scenarios such as classrooms or meetings where conversational analysis of multiple speakers is required. This survey will present research around computational modeling of “multi-party dialog”, outlining differences from two-party dialog, challenges and issues in working with multi-party dialog, and methods for representing multiparty dialog. We also provide an overview of dialog datasets created for the study of multiparty dialog, as well as tasks that are of interest in this domain.

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APA

Ganesh, A., Palmer, M., & Kann, K. (2023). A Survey of Challenges and Methods in the Computational Modeling of Multi-Party Dialog. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 140–154). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.nlp4convai-1.12

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