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Mengyu Zhou

Mengyu Zhou has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Efficient models & compression; often with Dongmei Zhang, Haoyu Dong, Shi Han.

2 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 9 · 48 works · 550 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 92 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10054

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

🏢MicrosoftRedmond · United States2018–2026 · 22 paperscurrent🏢Alibaba GroupHangzhou · China2026 · 3 paperscurrent🏢Microsoft Research AsiaBeijing · China2021–2026 · 3 paperscurrent🏥Affiliated Hospital of Nantong UniversityNantong · China2025–2026 · 2 paperscurrent🎓Nantong UniversityNantong · China2025–2026 · 2 paperscurrent🎓Tsinghua UniversityBeijing · China2016–2017 · 3 papers🎓Shandong Normal UniversityJinan · China2025 · 2 papers🎓University of Hong KongPok Fu Lam · China2023–2024 · 2 papers🎓Fudan UniversityShanghai · China2021–2023 · 2 papers

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 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksEfficient models & compression · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models (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 (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 ↗arXiv:2305.13062 · no summary yetYuan Sui et al.2023 · 235 citations
  2. TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (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 LearningAnnual Meeting of the Association for Computational Linguistics (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.

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

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