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SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?
Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Raymond Ng +9
Multilingual text embeddings are often assumed to encode meaning in a perspective-independent semantic space, yielding stable similarity judgments across tasks and languages. Our r…
Batayan: A Filipino NLP benchmark for evaluating Large Language Models
Jann Railey Montalan, Jimson Paulo Layacan, David Demitri Africa +5
Recent advances in large language models (LLMs) have demonstrated remarkable capabilities on widely benchmarked high-resource languages. However, linguistic nuances of under-resour…
SEA-HELM: Southeast Asian Holistic Evaluation of Language Models
Yosephine Susanto, Adithya Venkatadri Hulagadri, Jann Railey Montalan +7
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…