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Xuxi Chen

Xuxi Chen has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning; often with Andres Codas, Arindam Mitra, Erik Jones.

2 papers in our library · 2023–2024

OpenAlex · ORCID · Wikidata · h-index 14 · 64 works · 572 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 141 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7131

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

🎓Sichuan UniversityChengdu · China2020–2026 · 26 paperscurrent🎓The University of Texas at AustinAustin · United States2021–2026 · 20 paperscurrent🎓Fujian Medical UniversityFuzhou · China2018–2025 · 4 papers🏥PLA Navy General HospitalBeijing · China2013–2015 · 3 papers🏥West China Medical Center of Sichuan UniversityChengdu · China2022–2024 · 2 papers🎓University of Science and Technology of ChinaHefei · China2020–2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Orca 2: Teaching Small Language Models How to Reason (2023 · 162 citations)
    Small language models (below roughly 10B parameters) typically trail frontier LLMs in zero-shot reasoning.
  2. Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization (2024 · 8 citations)
    High-quality text for pretraining large language models is becoming scarce. This paper asks whether an already trained LLM can be improved cheaply by briefly continuing training on its own original data, without adding new sources. The authors first checked per-sample losses on C4 with LLaMA-2-7B. The very…

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. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 162 citations
  2. AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetTianlong Chen et al.2023 · 86 citations
  3. Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM GeneralizationarXiv:2402.14270Xuxi Chen, Zhendong Wang, Daouda Sow, et al.2024 · 8 citations

 Co-authors here

12 of 13 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 141 times (of the 149,439 papers whose bibliographies we read); 40 citing papers with a page here →.

Updated

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