---
title: "Who cites Baichuan-M1: Pushing the — 19 citing papers"
description: "19 papers of the Elamur Research library cite «Baichuan-M1: Pushing the Medical Capability of Large Language Models», found in their…"
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---
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# Who cites «Baichuan-M1: Pushing the Medical Capability of Large Language Models»

19 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Baichuan-M1: Pushing the Medical Capability of Large Language Models»](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)

1. [**Baichuan-M2: Scaling Medical Capability with Large Verifier System arXiv:2509.02208**Chengfeng Dou, Chong Liu, Fan Yang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-m2-baichuan-m2-scaling-medical/)
2. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
3. **[DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-diagnosisarena-benchmarking-diagnostic-reasoning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yakun Zhu, Zhongzhen Huang, Linjie Mu, et al.*2026 · 7 citations*
4. [**Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making arXiv:2602.06570**Chengfeng Dou, Fan Yang, Fei Li, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-m3-baichuan-m3-modeling-clinical/)
5. **[PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics](https://md.research.elamur.ai/free/en/papers/shen-2026-psychethicsbench-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaling Shen, Stephanie Fong, Yiwen Jiang, et al.*2026 · 2 citations*
6. **[Diffusion with Truncated Blocks: Fast and High-Quality Text Generation using Truncated Block Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffusion-truncated-blocks-fast-high/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Weiyu Chen, James Kwok*2026*
7. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*

12 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/) — Baichuan-M1: Pushing the Medical Capability of Large Language Models
