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Andrew Tao

Andrew Tao has 2 papers in our library, in 2023–2025, most of them on Language models & pretraining, Vision & language; often with Aarti Basant, Abhinav Khattar, Adithya Renduchintala.

2 papers in our library · 2023–2025

OpenAlex · h-index 20 · 62 works · 8,558 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 265 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #4241

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

🏢NvidiaSanta Clara · United States2018–2026 · 25 paperscurrent🏢NvidiaReading · United Kingdom2018–2025 · 13 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. VILA: On Pre-training for Visual Language Models (2023 · 381 citations)
    Most work on visual language models (VLMs) has focused on instruction tuning. The pre-training stage, where an LLM first learns to handle images and text together, has received far less systematic study. This paper addresses that gap. Starting from Llama-2, the authors build auto-regressive VLMs, in which image…
  2. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models (2025 · 38 citations)
    Self-attention costs grow with sequence length, both in compute per generated token and in KV-cache memory.

All works

6 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. Improving Semantic Segmentation via Video Propagation and Label Relaxation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYi Zhu et al.2019 · 420 citations
  2. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
  3. Graphical Contrastive Losses for Scene Graph Parsing ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetJi Zhang et al.2019 · 261 citations
  4. Dual Contrastive Loss and Attention for GANs ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetNing Yu et al.2021 · 53 citations
  5. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
  6. Wolf: Dense Video Captioning with a World Summarization Framework ↗arXiv (Cornell University) · no summary yetBoyi Li et al.2024 · 6 citations

 Co-authors here

12 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 265 times (of the 149,439 papers whose bibliographies we read); 45 citing papers with a page here →.

Updated

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