@inproceedings{jiang-etal-2025-towards,
title = "Towards Rationality in Language and Multimodal Agents: A Survey",
author = "Jiang, Bowen and
Xie, Yangxinyu and
Wang, Xiaomeng and
Yuan, Yuan and
Hao, Zhuoqun and
Bai, Xinyi and
Su, Weijie J and
Taylor, Camillo Jose and
Mallick, Tanwi",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-long.186/",
doi = "10.18653/v1/2025.naacl-long.186",
pages = "3656--3675",
ISBN = "979-8-89176-189-6",
abstract = "This work discusses how to build more rational language and multimodal agents and what criteria define rationality in intelligent systems.Rationality is the quality of being guided by reason, characterized by decision-making that aligns with evidence and logical principles. It plays a crucial role in reliable problem-solving by ensuring well-grounded and consistent solutions. Despite their progress, large language models (LLMs) often fall short of rationality due to their bounded knowledge space and inconsistent outputs. In response, recent efforts have shifted toward developing multimodal and multi-agent systems, as well as integrating modules like external tools, programming codes, symbolic reasoners, utility function, and conformal risk controls rather than relying solely on a single LLM for decision-making. This paper surveys state-of-the-art advancements in language and multimodal agents, assesses their role in enhancing rationality, and outlines open challenges and future research directions. We maintain an open repository at https://github.com/bowen-upenn/Agent{\_}Rationality."
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%0 Conference Proceedings
%T Towards Rationality in Language and Multimodal Agents: A Survey
%A Jiang, Bowen
%A Xie, Yangxinyu
%A Wang, Xiaomeng
%A Yuan, Yuan
%A Hao, Zhuoqun
%A Bai, Xinyi
%A Su, Weijie J.
%A Taylor, Camillo Jose
%A Mallick, Tanwi
%Y Chiruzzo, Luis
%Y Ritter, Alan
%Y Wang, Lu
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-189-6
%F jiang-etal-2025-towards
%X This work discusses how to build more rational language and multimodal agents and what criteria define rationality in intelligent systems.Rationality is the quality of being guided by reason, characterized by decision-making that aligns with evidence and logical principles. It plays a crucial role in reliable problem-solving by ensuring well-grounded and consistent solutions. Despite their progress, large language models (LLMs) often fall short of rationality due to their bounded knowledge space and inconsistent outputs. In response, recent efforts have shifted toward developing multimodal and multi-agent systems, as well as integrating modules like external tools, programming codes, symbolic reasoners, utility function, and conformal risk controls rather than relying solely on a single LLM for decision-making. This paper surveys state-of-the-art advancements in language and multimodal agents, assesses their role in enhancing rationality, and outlines open challenges and future research directions. We maintain an open repository at https://github.com/bowen-upenn/Agent_Rationality.
%R 10.18653/v1/2025.naacl-long.186
%U https://aclanthology.org/2025.naacl-long.186/
%U https://doi.org/10.18653/v1/2025.naacl-long.186
%P 3656-3675
Markdown (Informal)
[Towards Rationality in Language and Multimodal Agents: A Survey](https://aclanthology.org/2025.naacl-long.186/) (Jiang et al., NAACL 2025)
ACL
- Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Yuan Yuan, Zhuoqun Hao, Xinyi Bai, Weijie J Su, Camillo Jose Taylor, and Tanwi Mallick. 2025. Towards Rationality in Language and Multimodal Agents: A Survey. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 3656–3675, Albuquerque, New Mexico. Association for Computational Linguistics.