Kavli Affiliate: Feng Wang
| First 5 Authors: Feng Wang, Feng Wang, , ,
| Summary:
jina-reranker-v3 is a 0.6B-parameter multilingual listwise reranker that
introduces a novel "last but not late" interaction. Unlike late interaction
models like ColBERT that encode documents separately before multi-vector
matching, our approach applies causal attention between the query and all
candidate documents in the same context window, enabling rich interactions
before extracting contextual embeddings from each document’s final token. The
new model achieves state-of-the-art BEIR performance with 61.94 nDCG@10 while
being significantly smaller than other models with comparable performance.
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