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Tianjun Xiao

Tianjun Xiao has 2 papers in our library, in 2015–2024, most of them on Language models & pretraining, Vision & language; often with Zheng Zhang, Bing Xu, Chiyuan Zhang.

2 papers in our library · 2015–2024

OpenAlex · ORCID · h-index 13 · 30 works · 3,814 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 320 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #1537

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

🏢AmazonSeattle · United States2021–2025 · 10 papers🎓Peking UniversityBeijing · China2014–2021 · 6 papers🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2019–2025 · 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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksHardware and Architecture · 1 workArts and Humanities · 1 workNeuroscience · 1 workCognitive Neuroscience · 1 workLanguage and Linguistics · 1 work

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

💡 Concepts 1Key ideas and methods explained on our concept pages.Machine learning · 1 work

 Works by year

2020s

20241 paper

2010s

20151 paper

 Papers

The most cited first (OpenAlex and our library).

  1. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems (2015 · 2,000 citations)
    Deep learning developers usually have to pick between two styles. Imperative tensor code is easy to debug and works with host-language tools. Declarative computation graphs expose the whole structure, so the system can optimize it. MXNet tries to give users both styles in one library. Network structure is described…
  2. Hallucination of Multimodal Large Language Models: A Survey (2024 · 120 citations)
    This survey examines cases where multimodal large language models (MLLMs, sometimes termed LVLMs) produce text that contradicts the image they are given, a failure known as hallucination.

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. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed SystemsarXiv:1512.01274Tianqi Chen, Mu Li, Yutian Li, et al.2015 · 2,000 citations
  2. The application of two-level attention models in deep convolutional neural network for fine-grained image classification ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetTianjun Xiao et al.2015 · 788 citations
  3. Hallucination of Multimodal Large Language Models: A SurveyarXiv:2404.18930Zechen Bai, Pichao Wang, Tianjun Xiao, et al.2024 · 120 citations

 Co-authors here

7 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 320 times (of the 149,439 papers whose bibliographies we read); 36 citing papers with a page here →.

Updated

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