DeepWeaver: Bridging the Evidence Synthesis Gap in Open-Ended Question Answering
Retrieve-then-generate pipelines are commonly used to produce deep-research answers for open-ended questions, but retrieval alone is insufficient: LLMs must organize noisy and fragmented evidence into comprehensive, well-cited answers. We refer to this process as evidence synthesis. However, direct generation often underuses evidence, misaligns citations, and collapses diverse information into shallow summaries, exposing an evidence synthesis gap between retrieval and generation. Thus, we propose DeepWeaver, a novel framework that weaves noisy retrieved evidence into comprehensive answers by maintaining Thought Block Chains (TBCs), a structured representation that groups claims, salient i...
| Authors | Xujia Wang, Yizhe Zhang, Bin Xu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 19 August 2026 |
| Last updated at source | 6 September 2026 |
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