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arxiv:2509.25085

jina-reranker-v3: Last but Not Late Interaction for Document Reranking

Published on Sep 29
· Submitted by Han Xiao on Oct 1
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Abstract

A multilingual document reranker using causal self-attention achieves state-of-the-art performance with a compact architecture.

AI-generated summary

jina-reranker-v3 is a 0.6B parameter multilingual document reranker that introduces a novel last but not late interaction. Unlike late interaction models such as ColBERT that perform separate encoding followed by multi-vector matching, our approach conducts causal self-attention between query and documents within the same context window, enabling rich cross-document interactions before extracting contextual embeddings from the last token of each document. This compact architecture achieves state-of-the-art BEIR performance with 61.94 nDCG@10 while being ten times smaller than generative listwise rerankers.

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our latest gen of reranker model

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Hi, really impressive work there!

I needed a clarification, on page 5, the equation for dual matching loss ℓdual is mentioned to be Eq. but there is no Eq 4, also the link is pointing to page 4

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