--- title: "Ye Yuan — author profile and papers — Elamur Research" description: "Ye Yuan, Beijing Institute of Technology: 6 papers on Elamur Research (2023–2026), h-index 1 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/ye-yuan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ye-yuan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ye Yuan # Ye Yuan Ye Yuan has 6 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Summarization](https://md.research.elamur.ai/free/en/topics/summarization/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Haolun Wu](https://md.research.elamur.ai/free/en/authors/haolun-wu/), [Xue Liu](https://md.research.elamur.ai/free/en/authors/xue-liu/), [Bohan Wu](https://md.research.elamur.ai/free/en/authors/bohan-wu/). 6 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5139750890) · [**h-index 1**](https://openalex.org/authors/A5139750890) · [9 works](https://openalex.org/works?filter=author.id:A5139750890) · [2 citations](https://openalex.org/works?filter=author.id:A5139750890&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/ye-yuan/#papers) · [🔗 Cited 120 times in our library](https://md.research.elamur.ai/free/en/authors/ye-yuan/cited-by/) · [⭐ Paper Stars ranking: #6447](https://md.research.elamur.ai/free/en/paper-stars/page/65/#star-6447) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Ye+Yuan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ye+Yuan) · [dblp](https://dblp.org/search?q=Ye+Yuan) · [ACL Anthology](https://aclanthology.org/search/?q=Ye+Yuan) ## Affiliations [🎓**McGill University** Montreal · Canada 2026 · 5 papers*current*](https://md.research.elamur.ai/free/en/universities/mcgill-university/) · [🔬**Mila - Quebec Artificial Intelligence Institute** Montreal · Canada 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/labs/mila-quebec-artificial-intelligence-institute/) · [🎓**Beijing Institute of Technology** Beijing · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/beijing-institute-of-technology/) · [🎓**Peking University** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/peking-university/) · [🎓**University of Toronto** Toronto · Canada 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-toronto/) 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 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Information Systems · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) 🧭 Topics 6 Research subjects and languages the work is about.[Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Interpretability · 1 work](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Summarization · 1 work](https://md.research.elamur.ai/free/en/topics/summarization/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/ye-yuan/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/ye-yuan/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/ye-yuan/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/ye-yuan/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/)** *(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](https://md.research.elamur.ai/free/en/papers/luo-2025-large-language-model-agent-survey/)** *(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. **[FIMO: A Challenge Formal Dataset for Automated Theorem Proving](https://md.research.elamur.ai/free/en/papers/liu-2023-fimo-challenge-formal-dataset-automated/)** *(2023 · 53 citations)* Neural provers built on large language models still rarely solve olympiad-grade problems. Formal data is scarce and costly to produce, existing benchmarks contain few truly hard items, and most formal datasets lack natural-language counterparts. The authors address this with FIMO, a Lean benchmark drawn from the IMO… 4. **[Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization](https://md.research.elamur.ai/free/en/papers/zhang-2026-preference-heads-large-language-models/)** *(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. 5. **[DORA: A Dual-Objective Reinforcement Learning Framework for Effective and Efficient Multimodal Agentic Search](https://md.research.elamur.ai/free/en/papers/qin-2026-dora-dual-objective-reinforcement-learning/)** *(2026)* Multimodal LLMs trained with reinforcement learning can call search engines while answering knowledge-heavy visual questions. 6. **[FACTS: Table Summarization via Offline Template Generation with Agentic Workflows](https://md.research.elamur.ai/free/en/papers/yuan-2026-facts-table-summarization-offline-template/)** *(2026)* FACTS addresses query-focused table summarization, where a system writes a narrative answer to a user's request over one or more tables. ## Co-authors here 12 of 28 co-authors with a page, the most papers together first. - [Haolun Wu](https://md.research.elamur.ai/free/en/authors/haolun-wu/) ×2 - [Xue Liu](https://md.research.elamur.ai/free/en/authors/xue-liu/) ×2 - [Bohan Wu](https://md.research.elamur.ai/free/en/authors/bohan-wu/) - [Can Chen](https://md.research.elamur.ai/free/en/authors/can-chen/) - [Chuanyang Zheng](https://md.research.elamur.ai/free/en/authors/chuanyang-zheng/) - [Dawei Yin](https://md.research.elamur.ai/free/en/authors/dawei-yin/) - [Haiming Wang](https://md.research.elamur.ai/free/en/authors/haiming-wang/) - [Huajian Xin](https://md.research.elamur.ai/free/en/authors/huajian-xin/) - [Junfeng Wang](https://md.research.elamur.ai/free/en/authors/junfeng-wang/) - [Junwei Yang](https://md.research.elamur.ai/free/en/authors/junwei-yang/) - [Junyu Luo](https://md.research.elamur.ai/free/en/authors/junyu-luo/) - [Lin Li](https://md.research.elamur.ai/free/en/authors/lin-li/) ## 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)](https://md.research.elamur.ai/free/en/venues/acl/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2 - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) - [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/): [Artificial Intelligence Review 2024](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/2024/) ## Cited by Papers of our library cite their works 120 times (of the 149,439 papers whose bibliographies we read); [37 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ye-yuan/cited-by/). Updated 2 November 2026