Papers by Xiaodong Ge
Benchmarking Vision-Language Models on Chinese Ancient Documents: From OCR to Knowledge Reasoning (2026.findings-acl)
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Haiyang Yu, Yuchuan Wu, Fan Shi, Jinghui Lu, Ke Niu, Xiaodong Ge, Minghan Zhuo, Jingqun Tang, Bin Li
| Challenge: | Existing document benchmarks focus on English printed texts or simplified Chinese . current vision-language models struggle with visual complexity and poor adaptability . |
| Approach: | They propose a benchmark to evaluate Chinese ancient documents' visual/linguistic complexity . ancient documents are valuable cultural heritage, but they face challenges in digitization and understanding . |
| Outcome: | the first benchmark for Chinese ancient documents evaluates VLMs from OCR to knowledge reasoning . ancient documents carry thousands of years of Chinese history and culture . traditional methods only scan images, while current models struggle with visual complexity . |
Micro-Act: Mitigate Knowledge Conflict in Question Answering via Actionable Self-Reasoning (2025.acl-long)
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| Challenge: | Existing approaches to mitigate knowledge conflict by comparing two knowledge sources can overwhelm LLMs with extraneous or lengthy contexts. |
| Approach: | They propose a framework that decomposes knowledge into fine-grained comparisons . they propose 'Micro-Act' framework that allows for reasoning beyond the superficial context . |
| Outcome: | The proposed framework achieves significant increase in QA accuracy over state-of-the-art baselines on five benchmark datasets. |