--- title: "Mengyu Zhou — author profile and papers — Elamur Research" description: "Mengyu Zhou, Microsoft: 2 papers on Elamur Research (2025–2026), h-index 9 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/mengyu-zhou/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/mengyu-zhou/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Mengyu Zhou # Mengyu Zhou Mengyu Zhou has 2 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 [Dongmei Zhang](https://md.research.elamur.ai/free/en/authors/dongmei-zhang/), [Haoyu Dong](https://md.research.elamur.ai/free/en/authors/haoyu-dong/), [Shi Han](https://md.research.elamur.ai/free/en/authors/shi-han/). 2 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5101603009) · [ORCID](https://orcid.org/0000-0002-0322-7513) · [Wikidata](https://www.wikidata.org/wiki/Q130803432) · [**h-index 9**](https://openalex.org/authors/A5101603009) · [48 works](https://openalex.org/works?filter=author.id:A5101603009) · [550 citations](https://openalex.org/works?filter=author.id:A5101603009&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/#papers) · [🔗 Cited 92 times in our library](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #10054](https://md.research.elamur.ai/free/en/paper-stars/page/101/#star-10054) 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=Mengyu+Zhou) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Mengyu+Zhou) · [dblp](https://dblp.org/search?q=Mengyu+Zhou) · [ACL Anthology](https://aclanthology.org/search/?q=Mengyu+Zhou) ## Affiliations [🏢**Microsoft** Redmond · United States 2018–2026 · 22 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Alibaba Group** Hangzhou · China 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) · [🏢**Microsoft Research Asia** Beijing · China 2021–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/microsoft-research-asia/) · [🏥**Affiliated Hospital of Nantong University** Nantong · China 2025–2026 · 2 papers*current*](https://ror.org/001rahr89) · [🎓**Nantong University** Nantong · China 2025–2026 · 2 papers*current*](https://ror.org/02afcvw97) · [🎓**Tsinghua University** Beijing · China 2016–2017 · 3 papers](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🎓**Shandong Normal University** Jinan · China 2025 · 2 papers](https://ror.org/01wy3h363) · [🎓**University of Hong Kong** Pok Fu Lam · China 2023–2024 · 2 papers](https://md.research.elamur.ai/free/en/universities/university-of-hong-kong/) · [🎓**Fudan University** Shanghai · China 2021–2023 · 2 papers](https://md.research.elamur.ai/free/en/universities/fudan-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 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** 1 paper](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/)** *(2025 · 8 citations)* Large language models often misread tables when tuned with parameter-efficient methods such as LoRA. Flattening a grid into a token sequence hides which cells share a row or column, and nested headers become hard to interpret. TableLoRA is a PEFT-compatible module that addresses these problems with two components: 2. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/)** *(2026 · 1 citation)* Reasoning LLMs often generate chains of thought much longer than they need to be. Earlier RL methods for shortening them apply length penalties uniformly across tokens, which can hurt answer correctness. This paper treats the problem at the token level. It notes that a large share of CoT tokens barely influence the… ## All works 3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. **[Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study ↗](https://arxiv.org/abs/2305.13062) arXiv:2305.13062 · no summary yet**Yuan Sui et al.*2023 · 235 citations* 2. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations* 3. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation* ## Co-authors here 6 co-authors with a page, the most papers together first. - [Dongmei Zhang](https://md.research.elamur.ai/free/en/authors/dongmei-zhang/) ×2 - [Haoyu Dong](https://md.research.elamur.ai/free/en/authors/haoyu-dong/) ×2 - [Shi Han](https://md.research.elamur.ai/free/en/authors/shi-han/) ×2 - [Hanbing Liu](https://md.research.elamur.ai/free/en/authors/hanbing-liu/) - [Lang Cao](https://md.research.elamur.ai/free/en/authors/lang-cao/) - [Yuanyi Ren](https://md.research.elamur.ai/free/en/authors/yuanyi-ren/) ## 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/), [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ## Cited by Papers of our library cite their works 92 times (of the 149,439 papers whose bibliographies we read); [17 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/mengyu-zhou/cited-by/). Updated 1 November 2026