A softmax-weighted centroid of the local top-K documents interpolated with the query improves nDCG@10 for frozen embedding models across seven families on held-out BEIR data.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP) , year =
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Test-Time Compute for Dense Retrieval: Agentic Program Generation with Frozen Embedding Models
A softmax-weighted centroid of the local top-K documents interpolated with the query improves nDCG@10 for frozen embedding models across seven families on held-out BEIR data.