[Submitted on 4 Nov 2026]
Title:τ-bench-LILT: Evaluating Conversational Agents on Realistic Multilingual Tool-Use Tasks
View a PDF of the paper titled {\tau}-bench-LILT: Evaluating Conversational Agents on Realistic Multilingual Tool-Use Tasks, by Kaden Uhlig and 4 other authors
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Abstract:Frontier evaluations of tool-using conversational agents are conducted almost exclusively in English, leaving a critical gap for organizations deploying agents in other languages and regions. We present ${\tau}$-bench-LILT, a multilingual extension of ${\tau^3}$-bench covering German, Korean, Turkish, and Farsi in the airline, retail, telecom, and banking domains. We natively localize every layer of the benchmark: customer databases are populated with culturally appropriate records, user-simulator prompts are refined iteratively through contrastive annotation by native-language experts, and tasks are updated according to the localized database and to reflect realistic tasks in the target region. Evaluation across eight agent models shows the largest drops compared to English in the Korean and Farsi retail domains, by up to 61 points in pass^4. Code and data released at this https URL.
Comments: 17 pages, 14 figures
Subjects:
Computation and Language (cs.CL)
ACM classes: I.2.7; I.2.11
Cite as: arXiv:2611.07203 [cs.CL]
(or arXiv:2611.07203v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2611.07203
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Kaden Uhlig [view email] [v1] Wed, 4 Nov 2026 22:47:38 UTC (9,520 KB)
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