Papers by Zishuai Zhang

1 papers
An Efficient Framework for Whole-Page Reranking via Single-Modal Supervision (2026.acl-industry)

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Challenge: Existing whole-page reranking methods require large-scale expert annotations to achieve high-quality results.
Approach: They propose a whole-page reranking framework that converts single-modal rankers into page-level guidance by constructing budget-aware candidates for cross-modal annotations and distilling intra-modality preferences to align relevance scales across modalities.
Outcome: The proposed framework reduces annotation costs by 70-90% while outperforming fully-annotated reranking baselines.

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