Papers by Jiyuan Shen
HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop Questions (2026.acl-long)
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| Challenge: | Multi-Hop Question Answering (MHQA) is a critical benchmark for evaluating the model’s ability to integrate information from diverse sources. |
| Approach: | They propose a framework that synthesizes authentic multi-hop questions without manual annotation without the need for manual guidance. |
| Outcome: | The proposed framework synthesizes bridge and comparison questions without human intervention and achieves comparable or superior quality to human-annotated datasets at a lower cost. |
CARE: A Disagreement Detection Framework with Concept Alignment and Reasoning Enhancement (2025.emnlp-main)
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| Challenge: | Existing approaches to disagreement detection are limited by conceptual gap and reasoning gap. |
| Approach: | They propose a conceptual alignment and reasoning enhancement framework to address the conceptual gap and the reasoning gap in disagreement detection. |
| Outcome: | The proposed framework shows superior performance in zero-shot and supervised learning settings, both within and across domains. |
OCR or Not? Rethinking Document Information Extraction in the MLLMs Era with Real-World Large-Scale Datasets (2026.eacl-industry)
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| Challenge: | Multimodal Large Language Models (MLLMs) are used for document information extraction, but their impact on document information processing remains unclear. |
| Approach: | They propose an automated hierarchical error analysis framework that leverages large language models to diagnose errors systematically. |
| Outcome: | The proposed framework can achieve comparable performance to OCR-enhanced approaches. |