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Thomas Kollar

Thomas Kollar has 2 papers in our library, in 2013–2024, most of them on Language models & pretraining; often with Jayant Krishnamurthy, Jean Mercat, Kushal Arora.

2 papers in our library · 2013–2024

OpenAlex · ORCID · h-index 32 · 91 works · 3,522 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 662 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #5486

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

🔬Toyota Research InstitutePalo Alto · United States2020–2026 · 23 papersEmploymentcurrent🎓Massachusetts Institute of TechnologyCambridge · United States2006–2013 · 23 papersEducation · Ph.D.🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2006–2013 · 12 papers🎓Carnegie Mellon UniversityPittsburgh · United States2012–2021 · 11 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

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

 Works by year

2020s

20241 paper

2010s

20131 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World (2013 · 207 citations)
    This paper addresses grounded language acquisition: connecting natural-language statements to the objects they describe when the world is available only as raw perceptual features, not as a ready-made logical database.
  2. Linearizing Large Language Models (2024 · 16 citations)
    Linear-attention models and other recurrent models keep a fixed-size state during generation, which makes inference cheaper than in softmax transformers.

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. OpenVLA: An Open-Source Vision-Language-Action Model ↗arXiv:2406.09246 · no summary yetMoo Jin Kim et al.2024 · 254 citations
  2. Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical WorldTransactions of the Association for Computational Linguistics (TACL)Jayant Krishnamurthy, Thomas Kollar2013 · 207 citations
  3. Open X-Embodiment: Robotic Learning Datasets and RT-X Models ↗arXiv:2310.08864 · no summary yetEmbodiment Collaboration et al.2023 · 204 citations
  4. Language-Driven Representation Learning for Robotics ↗arXiv:2302.12766 · no summary yetSiddharth Karamcheti et al.2023 · 88 citations
  5. Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models ↗arXiv (Cornell University) · no summary yetSiddharth Karamcheti et al.2024 · 51 citations
  6. Linearizing Large Language ModelsarXiv:2405.06640Jean Mercat, Igor Vasiljevic, Sedrick Keh, et al.2024 · 16 citations

 Co-authors here

4 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 662 times (of the 149,439 papers whose bibliographies we read); 87 citing papers with a page here →.

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