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Yifan Mai

Yifan Mai has 2 papers in our library, in 2026, most of them on Language models & pretraining, Information extraction, Evaluation & benchmarks; often with Ariel Gera, Asaf Yehudai, Daniel Dahlmeier.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 5 · 24 works · 179 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 990 times in our library · 11 more in our library without a page yet · ⭐ Paper Stars ranking: #11315

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

🎓Stanford UniversityStanford · United States2024–2026 · 3 papersEmploymentcurrent🎓South China Normal UniversityGuangzhou · China2017Education since 2017

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 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 4Research subjects and languages the work is about.Information extraction · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. OCR or Not? Rethinking Document Information Extraction in the MLLMs Era with Real-World Large-Scale Datasets (2026 · 1 citation)
    Industrial document extraction systems usually run OCR first and then pass the recognized text to a separate extraction model. These pipelines are complex and carry OCR mistakes forward into extraction. The authors, from SAP and Stanford, ask whether modern multimodal LLMs can skip OCR entirely.
  2. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs (2026 · 1 citation)
    Large language models are often given tables, yet it is unclear how well they reason over them and how much their answers depend on how a table is written out.

All works

13 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. Holistic Evaluation of Language Models ↗arXiv:2211.09110 · Published in Transactions on Machine Learning Research (TMLR), 2023 · no summary yetPercy Liang et al.2022 · 1,001 citations
  2. VHELM: A Holistic Evaluation of Vision Language Models ↗neural information processing systems · no summary yetTong Lee et al.2024 · 34 citations
  3. AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies ↗SuperIntelligence - Robotics - Safety & Alignment · no summary yetYi Zeng et al.2024 · 23 citations
  4. MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks ↗arXiv (Cornell University) · no summary yetSuhana Bedi et al.2025 · 22 citations
  5. Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation ↗arXiv:2510.11977 · no summary yetSayash Kapoor et al.2025 · 11 citations
  6. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness ↗arXiv (Cornell University) · no summary yetShir Ashury-Tahan et al.2025 · 10 citations
  7. Language model developers should report train-test overlap ↗arXiv (Cornell University) · no summary yetAndy K. Zhang et al.2024 · 8 citations
  8. AHELM: A Holistic Evaluation of Audio-Language Models ↗arXiv (Cornell University) · no summary yetTong Lee et al.2025 · 7 citations
  9. Image2Struct: Benchmarking Structure Extraction for Vision-Language Models ↗neural information processing systems · no summary yetJosselin Somerville Roberts et al.2024 · 7 citations
  10. OCR or Not? Rethinking Document Information Extraction in the MLLMs Era with Real-World Large-Scale DatasetsConference of the European Chapter of the Association for Computational Linguistics (EACL)Jiyuan Shen, Yuan Peiyue, Atin Ghosh, et al.2026 · 1 citation
  11. The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMsWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraShir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.2026 · 1 citation
  12. DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots ↗arXiv (Cornell University) · no summary yetJared Moore et al.2026
  13. Structured Prompts Improve Evaluation of Language Models ↗arXiv (Cornell University) · no summary yetAsad Aali et al.2025

 Co-authors here

8 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 990 times (of the 149,439 papers whose bibliographies we read); 246 citing papers with a page here →.

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