🔗 Who cites «MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding»

62 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← back to «MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding»

1. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
2. MedGemma Technical ReportarXiv:2507.05201Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri, et al.2025 · 150 citations
3. Qwen3.5-Omni Technical ReportarXiv:2604.15804Qwen Team2026 · 29 citations
4. Baichuan-M2: Scaling Medical Capability with Large Verifier SystemarXiv:2509.02208Chengfeng Dou, Chong Liu, Fan Yang, et al.2025 · 19 citations
5. Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RLarXiv:2505.17952Che Liu, Haozhe Wang, Jiazhen Pan, et al.2025 · 10 citations
6. DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language ModelsFindings of the Association for Computational LinguisticsYakun Zhu, Zhongzhen Huang, Linjie Mu, et al.2026 · 7 citations
7. Patient-Similarity Cohort Reasoning in Clinical Text-to-SQLConference of the European Chapter of the Association for Computational Linguistics (EACL)Yifei Shen, Yilun Zhao, Justice Ou, et al.2026 · 4 citations
8. LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General IntelligenceFindings of the Association for Computational LinguisticsWenjin Liu, Haoran Luo, Xin Feng, et al.2026 · 2 citations
9. DeepMed: Building a Medical DeepResearch Agent via Multi-hop Med-Search Data and Turn-Controlled Agentic Training & InferenceFindings of the Association for Computational LinguisticsZihan Wang, Hao Wang, Shi Feng, et al.2026 · 1 citation
10. How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical ContextsFindings of the Association for Computational LinguisticsMinh-Vuong Nguyen, Fatemeh Shiri, Zhuang Li, et al.2026 · 1 citation
11. Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Rahul Thapa, Qingyang Wu, Kevin Wu, et al.2026 · 1 citation
12. TAGS: A Test-Time Generalist–Specialist Framework with Retrieval-Augmented Reasoning and VerificationFindings of the Association for Computational LinguisticsJianghao Wu, Feilong Tang, Yulong Li, et al.2026 · 1 citation
13. Benchmarking the Medical Understanding and Reasoning of Large Language Models in Arabic Healthcare TasksarXiv:2508.15797Nouar AlDahoul, Yasir Zaki2025 · 1 citation
14. Beyond Single View: A Comprehensive Benchmark for Medical Multimodal Large Language Models on Multi-Image UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Dexuan Xu, Yuan Jiayin, Jianing Wang, et al.2026
15. Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical ReasoningFindings of the Association for Computational LinguisticsFlavio Merenda, Jose Manuel Gomez-Perez, German Rigau2026
16. ClinAlign: Scaling Healthcare Alignment from Clinician PreferenceFindings of the Association for Computational LinguisticsShiwei Lyu, Xidong Wang, Hao Zhu, et al.2026
17. Scaling is Not All You Need: Clinical-Oriented Reinforcement Learning Makes Parameter-Efficient Clinical ReasoningFindings of the Association for Computational LinguisticsChi Liu, Yan Shu, Mengzhuo Chen, et al.2026
18. TARo: Token-level Adaptive Routing for LLM Test-time AlignmentFindings of the Association for Computational LinguisticsArushi Rai, Qiang Zhang, Hanqing Zeng, et al.2026
19. Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and ReasoningFindings of the Association for Computational LinguisticsCong Wan, Ying He, Zhongzhan Huang, et al.2026

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