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Yasha Wang

Yasha Wang has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Information retrieval & search; often with Junfeng Zhao, Xinke Jiang, Xu Chu.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 35 · 168 works · 5,186 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 40 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #8797

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

🎓Peking UniversityBeijing · China2005–2026 · 128 papersEmployment since 2013 · Professorcurrent🏛️Ministry of Education of the People's Republic of ChinaBeijing · China2019–2024 · 2 papers🎓Zhejiang Wanli UniversityNingbo · China2017–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksInformation Systems · 1 workHealth Informatics · 1 workMedicine · 1 work

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

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Recurrent Knowledge Identification and Fusion for Language Model Continual Learning (2025 · 11 citations)
    This paper tackles continual learning for large language models, where a model must absorb tasks one after another without losing earlier skills (catastrophic forgetting) while still benefiting from links between tasks (knowledge transfer).
  2. Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning (2025 · 9 citations)
    Retrieval-augmented LLMs face two competing demands. They should trust retrieved evidence even when it contradicts what they memorized (adherence), and they should ignore retrieved passages that look relevant but are actually noise (robustness). Training aimed at one of these tends to hurt the other. The authors…
  3. ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs (2026 · 4 citations)
    Most medical LLMs answer straight away from the patient's first description. When that description is incomplete, this can produce misdiagnoses. ProMed is a reinforcement learning framework that trains models to ask follow-up questions and collect missing clinical details before giving an answer. Its core is the…

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. Explainable Recommendation through Attentive Multi-View Learning ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetJingyue Gao et al.2019 · 128 citations
  2. COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetKai Yang et al.2020 · 61 citations
  3. Recurrent Knowledge Identification and Fusion for Language Model Continual LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yujie Feng, Xujia Wang, Zexin Lu, et al.2025 · 11 citations
  4. Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Yongxin Xu, Ruizhe Zhang, Xinke Jiang, et al.2025 · 9 citations
  5. ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Hongxin Ding, Baixiang Huang, Yue Fang, et al.2026 · 4 citations
  6. DFAMS: Dynamic-flow guided Federated Alignment based Multi-prototype Search ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhibang Yang et al.2026

 Co-authors here

12 of 13 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.

 Cited by

Papers of our library cite their works 40 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

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