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Jake Poznanski

Jake Poznanski has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Vision & language; often with Kyle Lo, Luca Soldaini, Aman Rangapur.

3 papers in our library · 2025–2026

OpenAlex · h-index 2 · 6 works · 13 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 169 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5907

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

🔬Allen Institute for Artificial IntelligenceSeattle · United States2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksComputer Vision and Pattern Recognition · 3 worksLanguage and Linguistics · 3 works

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

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Olmo 3 (2025 · 130 citations)
    Most competitive language models publish only their final weights. This hides the data and intermediate steps that shaped them. Olmo 3 addresses this by releasing the complete "model flow" for 7B and 32B models: every training stage, checkpoint, dataset, code dependency and log. The base model is trained in three…
  2. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models (2025 · 44 citations)
    PDFs hold a vast amount of high-quality text that could serve as training data for language models. They are hard to use because the format records glyphs and their positions rather than logical structure or reading order. Open-source extractors tend to produce noisy output, and strong proprietary VLMs are expensive…
  3. The olmOCR Project: Building Fully Open OCR using VLMs (2026 · 2 citations)
    Turning PDFs into clean text is difficult because the format stores glyphs and coordinates rather than logical reading flow.

All works

4 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. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  2. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsarXiv:2502.18443Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.2025 · 44 citations
  3. FlexOLMo: Open Language Models for Flexible Data Use ↗neural information processing systems · no summary yetWeijia Shi et al.2025 · 5 citations
  4. The olmOCR Project: Building Fully Open OCR using VLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jake Poznanski, Kyle Lo, Luca Soldaini2026 · 2 citations

 Co-authors here

11 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 169 times (of the 149,439 papers whose bibliographies we read); 40 citing papers with a page here →.

Updated

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