Papers by Xinwen Xu
Assessing and Mitigating Medical Knowledge Drift and Conflicts in Large Language Models (2025.findings-emnlp)
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| Challenge: | Rapid medical concept drift can lead LLMs to provide incorrect or outdated advice. |
| Approach: | They propose to evaluate how large language models manage knowledge conflicts in clinical guidelines. |
| Outcome: | The proposed benchmark evaluates how LLMs manage varied knowledge conflicts in clinical guidelines. |
ProtoVQA: An Adaptable Prototypical Framework for Explainable Fine-Grained Visual Question Answering (2025.emnlp-main)
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| Challenge: | Visual Question Answering (VQA) is increasingly used in diverse applications where models must provide accurate answers and explanations that humans can easily understand and verify. |
| Approach: | They propose a unified prototypical framework that learns question-aware prototypes that serve as reasoning anchors and applies spatially constrained matching to ensure that the selected evidence is coherent and semantically relevant. |
| Outcome: | The proposed framework yields faithful, fine-grained explanations while maintaining competitive accuracy. |