Papers by Lawrence Chieng
MalayMMLU: A Multitask Benchmark for the Low-Resource Malay Language (2024.findings-emnlp)
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Soon Poh, Sze Jue Yang, Jeraelyn Tan, Lawrence Chieng, Jia Tan, Zhenyu Yu, Foong Mun, Chee Seng Chan
| Challenge: | Large Language Models (LLMs) and Large Vision Language Model (LVLMs) exhibit advanced proficiency in language reasoning and comprehension across a wide array of languages. |
| Approach: | They propose to use a multitask language understanding benchmark specifically designed for the Malay language to assess their proficiency. |
| Outcome: | The proposed model performs well in well-resourced languages, but in low-resource languages such as Bahasa Melayu, they are less studied due to a lack of studies and benchmarks. |