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Yixin Chen

Yixin Chen has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Reasoning, Vision & language; often with Chengyao Wang, Jiaya Jia, Lingling Zhang.

2 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 18 · 63 works · 2,170 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 71 times in our library · ⭐ Paper Stars ranking: #7528

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

🎓National University of Defense TechnologyChangsha · China2009–2026 · 12 paperscurrent🎓University of MississippiOxford · United States2007–2017 · 9 papers🎓McGill UniversityMontreal · Canada2014–2016 · 5 papers🎓LSU New OrleansNew Orleans · United States2003–2006 · 5 papers🎓Jianghan UniversityWuhan · China2020–2024 · 4 papers🎓Pennsylvania State UniversityState College · United States2001–2004 · 4 papers🎓Chinese University of Hong KongHong Kong · China2022–2025 · 3 papers🎓Wuhan UniversityWuhan · China2011–2015 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 12 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).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models (2024 · 123 citations)
    Open vision language models still trail proprietary systems such as GPT-4 and Gemini. The common remedy, feeding more visual tokens from higher-resolution images, sharply raises compute costs. Mini-Gemini narrows this gap on an academic budget in three ways. First, it combines two vision encoders. A CLIP-pretrained…
  2. G-HiRel: Enhancing the Adaption to Knowledge Updating for Large Language Model Reasoning (2026)
    Large language models struggle when facts change after training: retraining or editing weights is expensive and scales poorly, and in-context injection of edited facts often fails on multi-hop questions.

 Co-authors here

5 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 71 times (of the 149,439 papers whose bibliographies we read); 23 citing papers with a page here →.

Updated

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