Papers by Zhongzhen Huang
MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression (2025.findings-acl)
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| Challenge: | Existing datasets and models fail to consider critical aspects of medical diagnostics, authors argue . MMXU enables multi-image questions incorporating both current and historical patient data. |
| Approach: | They propose a dataset for MedVQA that focuses on identifying changes in specific regions between two patient visits. |
| Outcome: | The proposed dataset improves diagnostic accuracy by 20% by integrating historical data. |
DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models (2026.findings-acl)
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Yakun Zhu, Zhongzhen Huang, Linjie Mu, Yutong Huang, Wei Nie, Jiaji Liu, Shaoting Zhang, Pengfei Liu, Xiaofan Zhang
| Challenge: | Existing medical benchmarks for diagnostic reasoning are limited in their ability to perform complex tasks. |
| Approach: | They propose to benchmark diagnostic capabilities of large language models to assess their accuracy and generalization bottlenecks. |
| Outcome: | The proposed model achieves 45.82%, 31.09%, and 17.79% accuracy, compared to current models, o3-mini, e1 and DeepSeek-R1 . |
MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration (2026.acl-long)
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| Challenge: | Existing benchmarks focus on static single-step calculations with explicit instructions. |
| Approach: | They propose a benchmark for evaluating medical calculators in realistic scenarios . they use 118 scenario tasks across 4 clinical domains to evaluate medical calculator performance . |
| Outcome: | The first benchmark for evaluating medical calculators in realistic scenarios is released . it features 118 scenario tasks across 4 clinical domains and is based on a model context protocol integration. |