--- title: "Yujin Yuan · Alibaba Group — author profile and papers" description: "Yujin Yuan, Alibaba Group: 3 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yujin-yuan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yujin-yuan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yujin Yuan # Yujin Yuan Yujin Yuan has 3 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/), [Haibin Chen](https://md.research.elamur.ai/free/en/authors/haibin-chen/), [Langming Liu](https://md.research.elamur.ai/free/en/authors/langming-liu/). 3 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139764089) · [**h-index 0**](https://openalex.org/authors/A5139764089) · [4 works](https://openalex.org/works?filter=author.id:A5139764089) · [0 citations](https://openalex.org/works?filter=author.id:A5139764089&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/yujin-yuan/#papers) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #11861](https://md.research.elamur.ai/free/en/paper-stars/page/119/#star-11861) 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=Yujin+Yuan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yujin+Yuan) · [dblp](https://dblp.org/search?q=Yujin+Yuan) · [ACL Anthology](https://aclanthology.org/search/?q=Yujin+Yuan) ## Affiliations [🏢**Alibaba Group** San Mateo · United States 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group-united-states/) · [🏢**Alibaba Group** Hangzhou · China 2026 · 4 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) 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 6 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 3 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/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/yujin-yuan/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning](https://md.research.elamur.ai/free/en/papers/liu-2026-pretrainrl-alleviating-factuality-hallucination-large/)** *(2026)* The paper addresses factual hallucinations in LLMs, meaning confident statements that can be checked and shown false. 2. **[Read As Human: Compressing Context via Parallelizable Close Reading and Skimming](https://md.research.elamur.ai/free/en/papers/tang-2026-read-as-human-compressing-context/)** *(2026)* Long prompts, such as those produced by retrieval-augmented generation, make LLM inference slow because attention cost grows quadratically. 3. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/)** *(2026)* Web-scraped pre-training corpora contain a lot of boilerplate and noise. Standard cleaning pipelines use document-level heuristics that can only keep or drop whole pages. Generative token-level refiners such as ProX-C are finer-grained but slow at scale and may hallucinate edits. The authors propose SelecT, which… ## All works 4 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. **[PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning](https://md.research.elamur.ai/free/en/papers/liu-2026-pretrainrl-alleviating-factuality-hallucination-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Langming Liu, Kangtao Lv, Haibin Chen, et al.*2026* 2. **[Read As Human: Compressing Context via Parallelizable Close Reading and Skimming](https://md.research.elamur.ai/free/en/papers/tang-2026-read-as-human-compressing-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiwei Tang, Shilei Liu, Zhicheng Zhang, et al.*2026* 3. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Tong, Weidong Zhang, Jiaang Li, et al.*2026* 4. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling ↗](https://aclanthology.org/2026.acl-long.1779/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Runsong Zhao et al.*2026* ## Co-authors here 12 of 14 co-authors with a page, the most papers together first. - [Bo Zheng](https://md.research.elamur.ai/free/en/authors/bo-zheng/) ×3 - [Haibin Chen](https://md.research.elamur.ai/free/en/authors/haibin-chen/) ×3 - [Langming Liu](https://md.research.elamur.ai/free/en/authors/langming-liu/) ×3 - [Shilei Liu](https://md.research.elamur.ai/free/en/authors/shilei-liu/) ×3 - [Wenbo Su](https://md.research.elamur.ai/free/en/authors/wenbo-su/) ×3 - [Kangtao Lv](https://md.research.elamur.ai/free/en/authors/kangtao-lv/) ×2 - [Weidong Zhang](https://md.research.elamur.ai/free/en/authors/weidong-zhang/) ×2 - [Xin Tong](https://md.research.elamur.ai/free/en/authors/xin-tong/) ×2 - [Hai-Tao Zheng](https://md.research.elamur.ai/free/en/authors/hai-tao-zheng/) - [Jiaang Li](https://md.research.elamur.ai/free/en/authors/jiaang-li/) - [Jiwei Tang](https://md.research.elamur.ai/free/en/authors/jiwei-tang/) - [Qingsong Lv](https://md.research.elamur.ai/free/en/authors/qingsong-lv/) ## 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/) ×3: [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/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) Updated 1 November 2026