DualView: Adaptive Local-Global Fusion for Multi-Hop Document Reranking

ArXi:2605.18767v1 Announce Type: cross Multi-hop question answering requires aggregating information from multiple documents, a critical capability for knowledge-intensive applications. A fundamental challenge lies in efficiently identifying the minimal relevant document set from retrieved candidates while maintaining high recall. We present an efficient dual-view cascaded reranking framework for multi-hop document reranking.