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Formal dialogue and large language models.

Snaith, Mark; Wells, Simon

Authors

Simon Wells



Contributors

Abstract

In this paper, we present preliminary work into combining formal models of dialogue and large language models, before going on to discuss how this provides a foundation for similar approaches involving computational models of argument. First, we address the twin issues of how a formal dialogue game can usefully regulate dialogical utterances generated by an LLM during an extended, goal-oriented conversation, and conversely, how LLMs can close the human-level language generation gap associated with formal dialogue games. We then proceed to identify how our solution to these issues can underpin future work towards using computational argumentation to provide reasoning-like capabilities to LLMs, and using LLMs for tasks such as searching and summarisation of analysed argument data.

Citation

SNAITH, M. and WELLS, S. 2024. Formal dialogue and large language models. In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 24-31. Available from: https://ceur-ws.org/Vol-3822/short3.pdf

Presentation Conference Type Conference Paper (published)
Conference Name 2024 SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024)
Start Date Oct 17, 2024
Acceptance Date Oct 1, 2024
Online Publication Date Oct 17, 2024
Publication Date Nov 4, 2024
Deposit Date Dec 5, 2024
Publicly Available Date Dec 5, 2024
Publisher CEUR-WS
Peer Reviewed Peer Reviewed
Pages 24-31
Series Title CEUR workshop proceedings
Series Number 3822
Series ISSN 1613-0073
Keywords Formal dialogue; Argumentation
Public URL https://rgu-repository.worktribe.com/output/2613516
Publisher URL https://ceur-ws.org/Vol-3822/

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