3 papers
cs.CL2026
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…
cs.CL2025
Assessing Thai Dialect Performance in LLMs with Automatic Benchmarks and Human Evaluation
Peerat Limkonchotiwat, Kanruethai Masuk, Surapon Nonesung +4
Large language models show promising results in various NLP tasks. Despite these successes, the robustness and consistency of LLMs in underrepresented languages remain largely unex…
cs.CL2024
Space Decomposition for Sentence Embedding
Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Ekapol Chuangsuwanich +1
Determining sentence pair similarity is crucial for various NLP tasks. A common technique to address this is typically evaluated on a continuous semantic textual similarity scale f…