Elamur Research⌕
☰
home / authors / Ye Yuan

Ye Yuan

Ye Yuan has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Information retrieval & search, Interpretability; often with Haolun Wu, Xue Liu, Bohan Wu.

4 papers in our library · 2024–2026

OpenAlex · h-index 1 · 9 works · 2 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 76 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6207

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

🎓McGill UniversityMontreal · Canada2026 · 5 paperscurrent🔬Mila - Quebec Artificial Intelligence InstituteMontreal · Canada2026 · 4 paperscurrent🎓Beijing Institute of TechnologyBeijing · China2026 · 2 paperscurrent🎓Peking UniversityBeijing · China2026 · 1 papercurrent🎓University of TorontoToronto · Canada2026 · 1 papercurrent

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

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksArts and Humanities · 2 worksInformation Systems · 3 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 4Research subjects and languages the work is about.Information retrieval & search · 1 workInterpretability · 1 workLanguage models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Retrieval-Augmented Generation for Natural Language Processing: A Survey (2024 · 86 citations)
    Large language models store knowledge implicitly in their weights. As a result, they can produce fluent but false answers, they need costly retraining to refresh facts, and they often lack depth in specialised domains. Retrieval-augmented generation (RAG) addresses these issues by consulting an external knowledge…
  2. Large Language Model Agent: A Survey on Methodology, Applications and Challenges (2025 · 62 citations)
    Work on LLM-based agents has grown quickly but remains scattered. Existing reviews tend to cover one slice, such as games, deployment settings, multimodality or security, or they give broad overviews without a method-level breakdown. Luo et al. address this with a survey built around how agents are engineered. Its…
  3. Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization (2026 · 1 citation)
    LLMs can adapt to a user's tone and topical interests, but current personalization methods (prompting, retrieval of user profiles, fine-tuning) treat this ability as a black box.
  4. DORA: A Dual-Objective Reinforcement Learning Framework for Effective and Efficient Multimodal Agentic Search (2026)
    Multimodal LLMs trained with reinforcement learning can call search engines while answering knowledge-heavy visual questions.

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. Retrieval-Augmented Generation for Natural Language Processing: A SurveyArtificial Intelligence ReviewShangyu Wu, Ying Xiong, Yufei Cui, et al.2024 · 86 citations
  2. Large Language Model Agent: A Survey on Methodology, Applications and ChallengesarXiv:2503.21460Junyu Luo, Weizhi Zhang, Ye Yuan, et al.2025 · 62 citations
  3. Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable PersonalizationAnnual Meeting of the Association for Computational Linguistics (ACL)Weixu Zhang, Ye Yuan, Changjiang Han, et al.2026 · 1 citation
  4. DORA: A Dual-Objective Reinforcement Learning Framework for Effective and Efficient Multimodal Agentic SearchAnnual Meeting of the Association for Computational Linguistics (ACL)Guangming Qin, Yuhao Deng, Yukun Zhao, et al.2026
  5. FACTS: Table Summarization via Offline Template Generation with Agentic Workflows ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYe Yuan, Mohammad Amin Shabani, Siqi Liu2026

 Co-authors here

12 of 17 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 76 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

Updated

↑ back to top

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