I developed a fine-tuned retrieval head for RAG that learns to more reliably retrieve relevant passages by transforming the query embeddings before retrieval. It is trained on synthetically generated question-chunk pairs from the corpus, and benchmarked against standard top-K cosine similarity on the isaacus/legal-rag-bench legal corpus.
☆18May 21, 2026Updated 5 months ago
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