🧑‍🔬 Xiangrong Zeng

🏛️ Affiliations

🎓National University of Defense TechnologyChangsha · China2009–2023 · 8 papers🎓China Agricultural UniversityBeijing · China2024–2025 · 4 papers🏛️Chinese Academy of SciencesBeijing · China2017–2019 · 3 papers🔬Institute of AutomationBeijing · China2017–2019 · 3 papers🎓University of Chinese Academy of SciencesBeijing · China2017–2019 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism (2018 · 612 citations)
   The paper addresses joint extraction of relational triplets (a relation plus a head and a tail entity) from raw sentences in which several triplets may share entities.
2. Baichuan-M1: Pushing the Medical Capability of Large Language Models (2025 · 24 citations)
   General-purpose LLMs often lack depth in medicine, where knowledge is specialized and good training data is scarce.
3. Baichuan-M2: Scaling Medical Capability with Large Verifier System (2025 · 19 citations)
   Medical LLMs often do well on exam-style tests such as USMLE but less well in real consultations, where information comes in gradually over many turns and communication matters.
4. Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making (2026 · 2 citations)
   Medical LLMs score well on static benchmarks but often stall in real consultations: they rarely ask for missing facts, and they may hallucinate when filling gaps.

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Extracting Relational Facts by an End-to-End Neural Model with Copy MechanismAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangrong Zeng, Daojian Zeng, Shizhu He, et al.2018 · 612 citations
2. Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetXiangrong Zeng et al.2019 · 169 citations
3. Baichuan-M1: Pushing the Medical Capability of Large Language ModelsarXiv:2502.12671Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.2025 · 24 citations
4. Baichuan-M2: Scaling Medical Capability with Large Verifier SystemarXiv:2509.02208Chengfeng Dou, Chong Liu, Fan Yang, et al.2025 · 19 citations
5. Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-MakingarXiv:2602.06570Chengfeng Dou, Fan Yang, Fei Li, et al.2026 · 2 citations

🤝 Co-authors here

12 of 20 co-authors with a page, the most papers together first.

• Chengfeng Dou ×2
• Fan Yang ×2
• Fei Li ×2
• Jiyuan Jia ×2
• Qiang Ju ×2
• Shuai Wang ×2
• Tianpeng Li ×2
• Yijie Zhou ×2
• Bingning Wang
• Chong Liu
• Da Pan
• Daojian Zeng

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2018
• Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

🔗 Cited by

Papers of our library cite their works 550 times (of the 149,439 papers whose bibliographies we read); 105 citing papers with a page here →.

Updated 31 October 2026

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