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Guangya Yu

Guangya Yu has 2 papers in our library, in 2026, most of them on Language models & pretraining, Information extraction; often with Weiyan Zhang, Hao He, Tong Ruan.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 1 · 18 works · 8 citations OpenAlex, 2026-10-14

📄 2 works in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #12005

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓East China University of Science and TechnologyShanghai · China2024–2026 · 12 paperscurrent🏢Ant GroupHangzhou · China2026 · 3 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workHealth Informatics · 1 workHealth Information Management · 1 workHealth Professions · 1 workLanguage and Linguistics · 1 workMedicine · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksInformation extraction · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. 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.
  2. 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

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. 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
  2. PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMsFindings of the Association for Computational LinguisticsJiacheng Wang, Weiyan Zhang, Guangya Yu2026
  3. 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
  4. 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

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

Venues

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

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/guangya-yu/