SEA-HELM: Southeast Asian Holistic Evaluation of Language Models

TL;DR

SEA-HELM is a comprehensive evaluation suite designed to assess large language models' multilingual and multicultural capabilities specifically for Southeast Asian languages, addressing a gap in culturally representative benchmarks.

Contribution

It introduces SEA-HELM, the first holistic evaluation framework for SEA languages, covering linguistic, cultural, safety, and model-specific aspects, with an accessible leaderboard.

Findings

Supports Filipino, Indonesian, Tamil, Thai, Vietnamese

Provides systematic multilingual and multicultural performance insights

Open-source evaluation code available

Abstract

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.