@inproceedings{sinha-etal-2026-language,
title = "The Language of Bargaining: Linguistic Effects in {LLM} Negotiations",
author = "Sinha, Stuti and
Kumar, Himanshu and
Mandapati, Aryan Raju and
Sakhuja, Rakshit and
Kumar, Dhruv",
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.51/",
pages = "1064--1088",
ISBN = "979-8-89176-439-2",
abstract = "Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work shows that LLMs can engage in multi-turn negotiation, yet nearly all evaluations occur exclusively in English. We systematically isolate language effects across English and three Indic framings (Hindi, Punjabi, Gujarati) by holding game rules, model parameters, and incentives constant for multi-agent simulations for Ultimatum, Buy-Sell, and Resource Exchange games. Our results indicate that language choice is correlated to agreement and process dynamics, while final payoffs are statistically unchanged, and that this correlation persists across model architectures. Crucially, effects are task-contingent: Indic languages lower acceptance and longer negotiations in the Ultimatum Game, and higher trade volume in Resource Exchange. Further, they suggest that findings obtained under English-only conditions may not generalize to other linguistic settings. Even within one related language family, we observe task-contingent divergence from English, which cautions against treating English-only evaluation as representative. Whether this extends to typologically distant languages remains open."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sinha-etal-2026-language">
<titleInfo>
<title>The Language of Bargaining: Linguistic Effects in LLM Negotiations</title>
</titleInfo>
<name type="personal">
<namePart type="given">Stuti</namePart>
<namePart type="family">Sinha</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Himanshu</namePart>
<namePart type="family">Kumar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aryan</namePart>
<namePart type="given">Raju</namePart>
<namePart type="family">Mandapati</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rakshit</namePart>
<namePart type="family">Sakhuja</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Dhruv</namePart>
<namePart type="family">Kumar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>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)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yue</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ruifeng</namePart>
<namePart type="family">Xu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ayu</namePart>
<namePart type="family">Purwarianti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tong</namePart>
<namePart type="family">Rong</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jun</namePart>
<namePart type="family">Suzuki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Hengqin, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-439-2</identifier>
</relatedItem>
<abstract>Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work shows that LLMs can engage in multi-turn negotiation, yet nearly all evaluations occur exclusively in English. We systematically isolate language effects across English and three Indic framings (Hindi, Punjabi, Gujarati) by holding game rules, model parameters, and incentives constant for multi-agent simulations for Ultimatum, Buy-Sell, and Resource Exchange games. Our results indicate that language choice is correlated to agreement and process dynamics, while final payoffs are statistically unchanged, and that this correlation persists across model architectures. Crucially, effects are task-contingent: Indic languages lower acceptance and longer negotiations in the Ultimatum Game, and higher trade volume in Resource Exchange. Further, they suggest that findings obtained under English-only conditions may not generalize to other linguistic settings. Even within one related language family, we observe task-contingent divergence from English, which cautions against treating English-only evaluation as representative. Whether this extends to typologically distant languages remains open.</abstract>
<identifier type="citekey">sinha-etal-2026-language</identifier>
<location>
<url>https://aclanthology.org/2026.aacl-long.51/</url>
</location>
<part>
<date>2026-11</date>
<extent unit="page">
<start>1064</start>
<end>1088</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T The Language of Bargaining: Linguistic Effects in LLM Negotiations
%A Sinha, Stuti
%A Kumar, Himanshu
%A Mandapati, Aryan Raju
%A Sakhuja, Rakshit
%A Kumar, Dhruv
%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 sinha-etal-2026-language
%X Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work shows that LLMs can engage in multi-turn negotiation, yet nearly all evaluations occur exclusively in English. We systematically isolate language effects across English and three Indic framings (Hindi, Punjabi, Gujarati) by holding game rules, model parameters, and incentives constant for multi-agent simulations for Ultimatum, Buy-Sell, and Resource Exchange games. Our results indicate that language choice is correlated to agreement and process dynamics, while final payoffs are statistically unchanged, and that this correlation persists across model architectures. Crucially, effects are task-contingent: Indic languages lower acceptance and longer negotiations in the Ultimatum Game, and higher trade volume in Resource Exchange. Further, they suggest that findings obtained under English-only conditions may not generalize to other linguistic settings. Even within one related language family, we observe task-contingent divergence from English, which cautions against treating English-only evaluation as representative. Whether this extends to typologically distant languages remains open.
%U https://aclanthology.org/2026.aacl-long.51/
%P 1064-1088
Markdown (Informal)
[The Language of Bargaining: Linguistic Effects in LLM Negotiations](https://aclanthology.org/2026.aacl-long.51/) (Sinha et al., AACL-IJCNLP 2026)
ACL
- Stuti Sinha, Himanshu Kumar, Aryan Raju Mandapati, Rakshit Sakhuja, and Dhruv Kumar. 2026. The Language of Bargaining: Linguistic Effects in LLM Negotiations. In 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), pages 1064–1088, Hengqin, China. Association for Computational Linguistics.