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ACL 2025aclfindings

SEA-HELM: Southeast Asian Holistic Evaluation of Language Models

Yosephine Susanto, Adithya Venkatadri Hulagadri, Jann Railey Montalan, Jian Gang Ngui, Xianbin Yong, Wei Qi Leong, Hamsawardhini Rengarajan, Peerat Limkonchotiwat, Yifan Mai, William Chandra Tjhi

National University of Singapore · AI Singapore and Ateneo de Manila University · AI Singapore · Stanford University

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2025.findings-acl.636 ↗

摘要

With the rapid emergence of novel capabilities in Large Language Models (LLMs), the need for rigorous multilingual and multiculturalbenchmarks that are integrated has become more pronounced. Though existing LLM benchmarks are capable of evaluating specificcapabilities of LLMs in English as well as in various mid- to low-resource languages, including those in the Southeast Asian (SEA)region, a comprehensive and culturally representative evaluation suite for the SEA languages has not been developed thus far.Here, we present SEA-HELM, a holistic linguistic and cultural LLM evaluation suite that emphasises SEA languages, comprisingfive core pillars: (1) NLP CLASSICS, (2) LLM-SPECIFICS, (3) SEA LINGUISTICS, (4) SEA CULTURE, (5) SAFETY. SEA-HELMcurrently supports Filipino, Indonesian, Tamil, Thai, and Vietnamese. We also introduce the SEA-HELM leaderboard, which allows users to understand models’ multilingual and multicultural performance in a systematic and user-friendly manner. We make the SEA-HELM evaluation code publicly available.