SEA-Embedding: Open and Reproducible Text Embeddings for Southeast Asia
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Computer Science > Computation and Language
Title:SEA-Embedding: Open and Reproducible Text Embeddings for Southeast Asia
Abstract:Text embeddings are fundamental to many downstream applications, making robustness important for real-world NLP. However, most recent state-of-the-art embedding models are not reproducible because they rely on closed or undisclosed training data, and they remain insufficiently robust for Southeast Asian languages. We present SEA-Embedding, a fully open and reproducible text-embedding pipeline for Southeast Asian languages trained only on publicly available data, and use it to study three core factors of robust embedding design: data composition, training objective, and base encoder initialization. SEA-Embedding achieves state-of-the-art results on SEA-BED while enabling systematic and reproducible analysis of robust text embeddings for the region.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.03027 [cs.CL] |
| (or arXiv:2606.03027v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.03027
arXiv-issued DOI via DataCite (pending registration)
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Submission history
From: Peerat Limkonchotiwat [view email][v1] Tue, 2 Jun 2026 02:05:14 UTC (9,147 KB)
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