Papers by Zhanli Li

1 papers
Navigating Large-Scale Document Collections: MuDABench for Multi-Document Analytical QA (2026.findings-acl)

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Challenge: Existing multi-document QA benchmarks require information from only a few documents with limited cross-document reasoning.
Approach: They propose a benchmark for multi-document analytical QA that extracts and synthesizes information across multiple documents to perform quantitative analysis.
Outcome: The proposed approach improves both process and outcome metrics but still has bottlenecks compared to human experts.

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