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Kai Zhang

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Book Open access Jul 2026

Good Ranks Follow Good Answers: Unsupervised Answer-Driven Reranking for Multimodal Document QA

AD-Reranker is proposed, a novel framework that shifts reranker training from proxy imitation to answer-driven utility optimization, and reformulate the reranker as an environment-grounded agent that interacts with a downstream reader, modeled as a deterministic environment.

Keyu Zhu, Shuanghong Shen, Xianquan Wang et al. · 0 citations