🧑‍🔬 Weiyan Zhang

🏛️ Affiliations

🔬China Academy of Engineering PhysicsMianyang · China2004–2026 · 13 paperscurrent🎓East China University of Science and TechnologyShanghai · China2021–2026 · 11 paperscurrent🎓Hangzhou Dianzi UniversityHangzhou · China2018–2019 · 4 papers🔬German Research Centre for Artificial IntelligenceKaiserslautern · Germany2022–2023 · 3 papers🎓University of BremenBremen · Germany2024–2025 · 2 papers🏢China Electronics Technology Group CorporationBeijing · China2022–2023 · 2 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

📄 Papers

The most cited first (OpenAlex and our library).

1. Can Multimodal Large Language Models Understand Spatial Relations? (2025 · 11 citations)
   Spatial relation reasoning is a basic skill for multimodal large language models (MLLMs), but existing benchmarks have several weaknesses.
2. AIDA-SEAT: Towards Reliable AI Doctor Assistant via State-Evaluation-Action Tree Enhanced LLMs in Online Hospital (2026)
   Clinical assistants built on LLMs, whether prompted directly or grounded through text or graph retrieval (RAG), mostly receive isolated medical facts.
3. PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs (2026)
   Adapting an LLM to a particular information extraction (IE) task involves many interacting choices: how to prepare the training data, how to tune the model, and how to prompt it at inference time.

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Can Multimodal Large Language Models Understand Spatial Relations?Annual Meeting of the Association for Computational Linguistics (ACL)Jingping Liu, Ziyan Liu, Zhedong Cen, et al.2025 · 11 citations
2. AIDA-SEAT: Towards Reliable AI Doctor Assistant via State-Evaluation-Action Tree Enhanced LLMs in Online HospitalAnnual Meeting of the Association for Computational Linguistics (ACL)Lianxin Sun, Xiaoying Ying, Guangya Yu, et al.2026
3. PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMsFindings of the Association for Computational LinguisticsJiacheng Wang, Weiyan Zhang, Guangya Yu2026
4. MedKInstruct: A Multimodal Knowledge Graph Based Framework for Multi-Hop and Hard-Negative Instruction Data Synthesis in MedVQA ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYinan Wu et al.2026
5. Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical Dialogue ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetGuangya Yu et al.2026
6. Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetMu Zhang et al.2026

🤝 Co-authors here

7 co-authors with a page, the most papers together first.

• Guangya Yu ×2
• Tong Ruan ×2
• Haiyun Jiang
• Hao He
• Jingping Liu
• Yan Zhou
• Ziyan Liu

Venues

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

• Findings of the Association for Computational Linguistics: ACL 2026 ×3
• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2026, ACL 2025
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026

🔗 Cited by

Papers of our library cite their works 6 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated 1 November 2026

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