ChEmbed: Enhancing Chemical Literature Search Through Domain-Specific Text Embeddings

Name: ChEmbed: Enhancing Chemical Literature Search Through Domain-Specific Text Embeddings
Uploaded: 2026-10-03T23:57:50.429464+00:00
Duration: 383 s
Description: ChEmbed is a domain-adapted text embedding model fine-tuned on chemistry literature to improve search retrieval for RAG systems. It uses synthetic data and a novel tokenizer to better represent chemical terms, achieving an nDCG@10 of 0.911. This specialized model outperforms general embeddings by effectively capturing the nuances of chemical text.

ChEmbed is a domain-adapted text embedding model fine-tuned on chemistry literature to improve search retrieval for RAG systems. It uses synthetic data and a novel tokenizer to better represent chemical terms, achieving an nDCG@10 of 0.911. This specialized model outperforms general embeddings by effectively capturing the nuances of chemical text.

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