SEA-HELM: Southeast Asian Holistic Evaluation of Language Models

Fuente: arXiv
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Main Authors: Susanto, Yosephine, Hulagadri, Adithya Venkatadri, Montalan, Jann Railey, Ngui, Jian Gang, Yong, Xian Bin, Leong, Weiqi, Rengarajan, Hamsawardhini, Limkonchotiwat, Peerat, Mai, Yifan, Tjhi, William Chandra
Format: Preprint
Published: 2025
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author Susanto, Yosephine
Hulagadri, Adithya Venkatadri
Montalan, Jann Railey
Ngui, Jian Gang
Yong, Xian Bin
Leong, Weiqi
Rengarajan, Hamsawardhini
Limkonchotiwat, Peerat
Mai, Yifan
Tjhi, William Chandra
author_facet Susanto, Yosephine
Hulagadri, Adithya Venkatadri
Montalan, Jann Railey
Ngui, Jian Gang
Yong, Xian Bin
Leong, Weiqi
Rengarajan, Hamsawardhini
Limkonchotiwat, Peerat
Mai, Yifan
Tjhi, William Chandra
contents With the rapid emergence of novel capabilities in Large Language Models (LLMs), the need for rigorous multilingual and multicultural benchmarks that are integrated has become more pronounced. Though existing LLM benchmarks are capable of evaluating specific capabilities 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, comprising five core pillars: (1) NLP Classics, (2) LLM-specifics, (3) SEA Linguistics, (4) SEA Culture, (5) Safety. SEA-HELM currently 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.
format Preprint
id arxiv_https___arxiv_org_abs_2502_14301
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle SEA-HELM: Southeast Asian Holistic Evaluation of Language Models
Susanto, Yosephine
Hulagadri, Adithya Venkatadri
Montalan, Jann Railey
Ngui, Jian Gang
Yong, Xian Bin
Leong, Weiqi
Rengarajan, Hamsawardhini
Limkonchotiwat, Peerat
Mai, Yifan
Tjhi, William Chandra
Computation and Language
Artificial Intelligence
With the rapid emergence of novel capabilities in Large Language Models (LLMs), the need for rigorous multilingual and multicultural benchmarks that are integrated has become more pronounced. Though existing LLM benchmarks are capable of evaluating specific capabilities 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, comprising five core pillars: (1) NLP Classics, (2) LLM-specifics, (3) SEA Linguistics, (4) SEA Culture, (5) Safety. SEA-HELM currently 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.
title SEA-HELM: Southeast Asian Holistic Evaluation of Language Models
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2502.14301