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Shuhao Gu

Shuhao Gu has 3 papers in our library, in 2024–2025, most of them on Vision & language, Language models & pretraining, Reasoning; often with Bo-Wen Zhang, Liangdong Wang, Lei Li.

3 papers in our library · 2024–2025

OpenAlex · h-index 10 · 30 works · 218 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 125 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #7889

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

🏛️Chinese Academy of SciencesBeijing · China2019–2024 · 22 papers🔬Institute of Computing TechnologyBeijing · China2019–2024 · 17 papers🎓University of Chinese Academy of SciencesBeijing · China2019–2024 · 16 papers🔬Beijing Academy of Artificial IntelligenceBeijing · China2024 · 3 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 5The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksComputer Vision and Pattern Recognition · 3 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20251 paper20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. MiMo-VL Technical Report (2025 · 33 citations)
    Xiaomi's LLM-Core team presents MiMo-VL-7B, a compact open vision-language model that handles general visual understanding, multimodal reasoning and GUI grounding in one 7B system.
  2. Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction Data (2024 · 13 citations)
    Open vision-language models (VLMs) trained only on public instruction data still trail systems built on proprietary data.
  3. Aquila2 Technical Report (2024 · 1 citation)
    Most LLMs are pretrained on a fixed dataset over a long run, so it is hard to change the data mix or add new sources partway through. BAAI's Aquila2 is a family of Chinese–English bilingual models at 7B, 34B and an experimental 70B size. They were trained with HeuriMentor (HM), a framework with three parts:

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Modeling Fluency and Faithfulness for Diverse Neural Machine Translation ↗arXiv:1912.00178 · no summary yetYang Feng et al.2019 · 38 citations
  2. MiMo: Unlocking the Reasoning Potential of Language Model — From Pretraining to Posttraining ↗arXiv:2505.07608 · no summary yetLLM-Core Xiaomi et al.2025 · 37 citations
  3. MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
  4. Robust Neural Machine Translation with ASR Errors ↗Proceedings of the First Workshop on Automatic Simultaneous Translation · no summary yetHaiyang Xue et al.2020 · 15 citations
  5. Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction DataarXiv:2410.18558Shuhao Gu, Jialing Zhang, Siyuan Zhou, et al.2024 · 13 citations
  6. Aquila2 Technical ReportarXiv:2408.07410Bo-Wen Zhang, Liangdong Wang, Jijie Li, et al.2024 · 1 citation

 Co-authors here

10 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 125 times (of the 149,439 papers whose bibliographies we read); 39 citing papers with a page here →.

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