--- title: "Lei Ji — author profile and papers — Elamur Research" description: "Lei Ji, Microsoft: 3 papers on Elamur Research (2025–2026), h-index 11 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/lei-ji/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/lei-ji/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Lei Ji # Lei Ji Lei Ji has 3 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Xiao Liu](https://md.research.elamur.ai/free/en/authors/xiao-liu/), [Yeyun Gong](https://md.research.elamur.ai/free/en/authors/yeyun-gong/), [Xiao Liang](https://md.research.elamur.ai/free/en/authors/xiao-liang/). 3 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5100754482) · [ORCID](https://orcid.org/0000-0001-7753-3313) · [**h-index 11**](https://openalex.org/authors/A5100754482) · [37 works](https://openalex.org/works?filter=author.id:A5100754482) · [788 citations](https://openalex.org/works?filter=author.id:A5100754482&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/lei-ji/#papers) · [🔗 Cited 16 times in our library](https://md.research.elamur.ai/free/en/authors/lei-ji/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #10004](https://md.research.elamur.ai/free/en/paper-stars/page/101/#star-10004) 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=Lei+Ji) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Lei+Ji) · [dblp](https://dblp.org/search?q=Lei+Ji) · [ACL Anthology](https://aclanthology.org/search/?q=Lei+Ji) ## Affiliations [🏢**Microsoft Research Asia** Beijing · China 2020–2026 · 9 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft-research-asia/) · [🏢**Microsoft** Redmond · United States 2020–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏛️**Chinese Academy of Sciences** Beijing · China 2010–2021 · 5 papers](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2020–2021 · 5 papers](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) · [🎓**Beijing University of Posts and Telecommunications** Beijing · China 2017–2020 · 5 papers](https://md.research.elamur.ai/free/en/universities/beijing-university-of-posts-and-telecommunications/) · [🏢**Huawei Technologies** Shenzhen · China 2023–2025 · 4 papers](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) · [🔬**Institute of Computing Technology** Beijing · China 2020–2021 · 4 papers](https://md.research.elamur.ai/free/en/labs/institute-of-computing-technology/) · [🎓**Southwest Jiaotong University** Chengdu · China 2021 · 3 papers](https://md.research.elamur.ai/free/en/universities/southwest-jiaotong-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 7 The field of science this work belongs to (OpenAlex fields).[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/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [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/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Management Science and Operations Research · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/management-science-and-operations-research/) 🧭 Topics 3 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/lei-ji/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/lei-ji/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression](https://md.research.elamur.ai/free/en/papers/li-2025-tl-dr-too-long-re/)** *(2025 · 8 citations)* Reasoning-focused LLMs that generate long Chain-of-Thought (CoT) often overthink, spending many tokens even on easy questions. Existing compression approaches usually need laborious data labeling, model interpolation (as in CoT-Valve), or costly RL with length penalties. 2. **[Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-data-mixing-agent-learning-re/)** *(2026 · 1 citation)* Continual pre-training of an LLM on a narrow target field, such as math, often causes catastrophic forgetting of general skills. 3. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/)** *(2026)* Instruction-tuning collections such as TÜLU combine many heterogeneous datasets, yet their mixing ratios are usually fixed by hand or need extra proxy models and validation sets to adjust. ## 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. **[A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos ↗](https://aclanthology.org/2020.nlpbt-1.4/) Proceedings of the First International Workshop on Natural Language Processing Beyond Text · no summary yet**Frank F. Xu et al.*2020 · 27 citations* 2. [**TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression arXiv:2506.02678**Zhong-Zhi Li, Xiao Liang, Zihao Tang, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-tl-dr-too-long-re/) 3. **[Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-data-mixing-agent-learning-re/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kailai Yang, Xiao Liu, Lei Ji, et al.*2026 · 1 citation* 4. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026* ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Xiao Liu](https://md.research.elamur.ai/free/en/authors/xiao-liu/) ×3 - [Yeyun Gong](https://md.research.elamur.ai/free/en/authors/yeyun-gong/) ×3 - [Xiao Liang](https://md.research.elamur.ai/free/en/authors/xiao-liang/) ×2 - [Haizhen Huang](https://md.research.elamur.ai/free/en/authors/haizhen-huang/) - [Hao Li](https://md.research.elamur.ai/free/en/authors/hao-li/) - [Haotian Xu](https://md.research.elamur.ai/free/en/authors/haotian-xu/) - [Kailai Yang](https://md.research.elamur.ai/free/en/authors/kailai-yang/) - [Mao Yang](https://md.research.elamur.ai/free/en/authors/mao-yang/) - [Peijie Wang](https://md.research.elamur.ai/free/en/authors/peijie-wang/) - [Peng Cheng](https://md.research.elamur.ai/free/en/authors/peng-cheng/) - [Qi Chen](https://md.research.elamur.ai/free/en/authors/qi-chen/) - [Weiwei Deng](https://md.research.elamur.ai/free/en/authors/weiwei-deng/) ## 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/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [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/) - Proceedings of the First International Workshop on Natural Language Processing Beyond Text ## Cited by Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); [4 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/lei-ji/cited-by/). Updated 1 November 2026