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Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog

18 July 2025
Lautaro Estienne
Gabriel Ben Zenou
Nona Naderi
Jackie Chi Kit Cheung
Pablo Piantanida
ArXiv (abs)PDFHTML
Main:9 Pages
6 Figures
Bibliography:3 Pages
1 Tables
Appendix:3 Pages
Abstract

As AI systems take on collaborative roles, they must reason about shared goals and beliefs-not just generate fluent language. The Rational Speech Act (RSA) framework offers a principled approach to pragmatic reasoning, but existing extensions face challenges in scaling to multi-turn, collaborative scenarios. In this paper, we introduce Collaborative Rational Speech Act (CRSA), an information-theoretic (IT) extension of RSA that models multi-turn dialog by optimizing a gain function adapted from rate-distortion theory. This gain is an extension of the gain model that is maximized in the original RSA model but takes into account the scenario in which both agents in a conversation have private information and produce utterances conditioned on the dialog. We demonstrate the effectiveness of CRSA on referential games and template-based doctor-patient dialogs in the medical domain. Empirical results show that CRSA yields more consistent, interpretable, and collaborative behavior than existing baselines-paving the way for more pragmatic and socially aware language agents.

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