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Multi-Lingual Malaysian Embedding: Leveraging Large Language Models for Semantic Representations
Feb. 6, 2024, 5:46 a.m. | Husein Zolkepli Aisyah Razak Kamarul Adha Ariff Nazhan
cs.LG updates on arXiv.org arxiv.org
For Semantic Similarity, our 600 million parameter Llama2 model outperforms OpenAI text-embedding-ada-002 across all recall@k metrics for b.cari.com.my, c.cari.com.my, Malay news, and Malaysian Twitter test sets.
In the realm of RAG models, our approach proves competitive with OpenAI text-embedding-ada-002 in the Malaysian …
ada cs.cl cs.lg embedding exploration finetuning language language models large language large language models llama2 mistral negative openai positive rag release retrieval retrieval-augmented semantic tasks text work
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