@inproceedings{yadav-etal-2026-effects,
title = "Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of {LLM}s in Ultimatum Games",
author = "Yadav, Neemesh and
Lan, Yihuai and
Dong, Shan and
Hien, Mai Hieu and
Achananuparp, Palakorn and
Jiang, Jing and
Lim, Ee-Peng",
editor = "Zhang, Yue and
Xu, Ruifeng and
Purwarianti, Ayu and
Rong, Tong and
Suzuki, Jun",
booktitle = "Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the {A}sia-Pacific Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = nov,
year = "2026",
address = "Hengqin, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.aacl-long.148/",
pages = "3252--3277",
ISBN = "979-8-89176-439-2",
abstract = "Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for complex social interactions. We investigate ToM reasoning{'}s role in aligning agentic behaviors with human norms in negotiation tasks, using the ultimatum game as our referenced task. We initialized LLM agents with different prosocial beliefs (Greedy, Fair, Selfless) and reasoning methods (chain of thought and ToM reasoning of varying levels), examining their decision-making processes and outcomes across multiple LLMs, including reasoning models like o3-mini and DeepSeek-R1 Distilled Qwen 32B. We perform 2,700 simulations to show that ToM reasoning enhances behavioral alignment with human norms, decision-making consistency, and negotiation outcomes. Consistent with prior findings, reasoning LLMs exhibit limited capability compared to ToM-enhanced LLMs, with different game roles benefiting from different ToM orders.Fair proposers and responders accepting offers were the most consistent with their strategic reasonings, whereas all agents showed strong consistencies with human beliefs when rejecting offers, except when the offer was fair. Human verification further revealed that Llama 3.3 70B produces reasoning most consistent with its actions and beliefs. Our findings advance understanding of ToM{'}s role in human-AI interaction and cooperative decision-making. The code used for our experiments can be found at https://anonymous.4open.science/r/UltimatumToM."
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<abstract>Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for complex social interactions. We investigate ToM reasoning’s role in aligning agentic behaviors with human norms in negotiation tasks, using the ultimatum game as our referenced task. We initialized LLM agents with different prosocial beliefs (Greedy, Fair, Selfless) and reasoning methods (chain of thought and ToM reasoning of varying levels), examining their decision-making processes and outcomes across multiple LLMs, including reasoning models like o3-mini and DeepSeek-R1 Distilled Qwen 32B. We perform 2,700 simulations to show that ToM reasoning enhances behavioral alignment with human norms, decision-making consistency, and negotiation outcomes. Consistent with prior findings, reasoning LLMs exhibit limited capability compared to ToM-enhanced LLMs, with different game roles benefiting from different ToM orders.Fair proposers and responders accepting offers were the most consistent with their strategic reasonings, whereas all agents showed strong consistencies with human beliefs when rejecting offers, except when the offer was fair. Human verification further revealed that Llama 3.3 70B produces reasoning most consistent with its actions and beliefs. Our findings advance understanding of ToM’s role in human-AI interaction and cooperative decision-making. The code used for our experiments can be found at https://anonymous.4open.science/r/UltimatumToM.</abstract>
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%0 Conference Proceedings
%T Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games
%A Yadav, Neemesh
%A Lan, Yihuai
%A Dong, Shan
%A Hien, Mai Hieu
%A Achananuparp, Palakorn
%A Jiang, Jing
%A Lim, Ee-Peng
%Y Zhang, Yue
%Y Xu, Ruifeng
%Y Purwarianti, Ayu
%Y Rong, Tong
%Y Suzuki, Jun
%S Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, China
%@ 979-8-89176-439-2
%F yadav-etal-2026-effects
%X Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for complex social interactions. We investigate ToM reasoning’s role in aligning agentic behaviors with human norms in negotiation tasks, using the ultimatum game as our referenced task. We initialized LLM agents with different prosocial beliefs (Greedy, Fair, Selfless) and reasoning methods (chain of thought and ToM reasoning of varying levels), examining their decision-making processes and outcomes across multiple LLMs, including reasoning models like o3-mini and DeepSeek-R1 Distilled Qwen 32B. We perform 2,700 simulations to show that ToM reasoning enhances behavioral alignment with human norms, decision-making consistency, and negotiation outcomes. Consistent with prior findings, reasoning LLMs exhibit limited capability compared to ToM-enhanced LLMs, with different game roles benefiting from different ToM orders.Fair proposers and responders accepting offers were the most consistent with their strategic reasonings, whereas all agents showed strong consistencies with human beliefs when rejecting offers, except when the offer was fair. Human verification further revealed that Llama 3.3 70B produces reasoning most consistent with its actions and beliefs. Our findings advance understanding of ToM’s role in human-AI interaction and cooperative decision-making. The code used for our experiments can be found at https://anonymous.4open.science/r/UltimatumToM.
%U https://aclanthology.org/2026.aacl-long.148/
%P 3252-3277
Markdown (Informal)
[Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games](https://aclanthology.org/2026.aacl-long.148/) (Yadav et al., AACL-IJCNLP 2026)
ACL