arXiv Computation and Language By Long Wang

NativeScope: Relation-Localized Retrieval over Native Topology with a Correct Anchor

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NativeScope is a retrieval method that first scopes candidate text chunks using a known anchor and a relation (such as belonging, before, or after) and then ranks only those chunks that overlap the selected scope. In experiments on 200 controlled documents and memory records, NativeScope achieved 89.28 % recall for documents and 72.50 % for memories, outperforming instance‑wide Dense RAG by 42.75 and 22.00 percentage points. An internal variant, NS‑FullQ, which ranks candidates with the full question, showed similar performance, indicating that the primary benefit comes from relational scoping rather than query length. whyItMatters: The study demonstrates that incorporating native structural relations into retrieval can substantially improve recall, especially when anchor coordinates and relations are reliable.

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arXiv AI
3d ago

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

DualView is an efficient dual‑view cascaded reranking framework designed for multi‑hop document reranking in question answering. It combines a Local Scorer that uses stacked cross‑attention for fine‑grained query‑document relevance with a Global Scorer that models inter‑document dependencies via Transformer‑based context aggregation. An Adaptive Gate dynamically fuses these views based on query semantics, achieving high recall and low latency on benchmarks such as MuSiQue.

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