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.

翻译：jina-reranker-v3 是一个拥有 6 亿参数的多语言列表式重排序模型，其引入了一种新颖的“最后但非延迟”交互机制。与 ColBERT 等延迟交互模型（需先分别编码文档再进行多向量匹配）不同，我们的方法在查询与所有候选文档之间于同一上下文窗口中应用因果注意力机制，从而在从每个文档的最终词元提取上下文嵌入之前实现丰富的交互。该新模型在 BEIR 基准上取得了 61.94 nDCG@10 的最先进性能，同时其模型规模显著小于具有相当性能的其他模型。