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Xinnan Dai

Xinnan Dai has 2 papers in our library, in 2026, most of them on Language models & pretraining, Evaluation & benchmarks, Efficient models & compression; often with Dante Everaert, Kai Guo, Monica Xiao Cheng.

2 papers in our library · 2026

OpenAlex · h-index 7 · 17 works · 209 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #13191

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

🎓Michigan State UniversityEast Lansing · United States2023–2026 · 6 paperscurrent🎓ShanghaiTech UniversityShanghai · China2019–2023 · 4 papers🎓Southwest University of Science and TechnologyMianyang · China2019 · 2 papers

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 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 worksEvaluation & benchmarks · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation (2026 · 1 citation)
    LLM-based graph learning studies use inconsistent datasets, preprocessing and splits, so it remains unclear how pure LLMs compare with dedicated graph models.
  2. Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs (2026)
    Personalizing LLMs usually means feeding them long user histories and profiles, which raises inference latency and API costs.

 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.

Updated

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