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arXiv — NLP / Computation & Language · · 3 min read

SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding

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Computer Science > Computation and Language

arXiv:2606.03284 (cs)
[Submitted on 2 Jun 2026]

Title:SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding

View a PDF of the paper titled SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding, by Peerawat Chomphooyod and 7 other authors
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Abstract:Frontier LLMs perform well in Western contexts, but remain poorly tested on underrepresented cultures such as those in Southeast Asia (SEA). Existing NLI benchmarks are largely Western-centric, translation-derived, or monolingual, limiting their ability to measure culturally grounded reasoning. We introduce SEA-NLI, a native, culturally grounded NLI benchmark covering eight SEA countries in English and native regional languages, verified by native speakers. Across 17 encoder and decoder models, we observe a low performance from all models, especially for knowledge-intensive categories such as Languages and Science and Technology. Our analysis shows that failure cases mainly stem from missing SEA cultural knowledge: SEA-adapted models and culture-aware prompting improve performance, while CoT prompting offers limited gains.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2606.03284 [cs.CL]
  (or arXiv:2606.03284v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2606.03284
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Peerat Limkonchotiwat [view email]
[v1] Tue, 2 Jun 2026 07:49:50 UTC (1,588 KB)
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