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Kaj Bostrom

Kaj Bostrom has 2 papers in our library, in 2020–2023, most of them on Language models & pretraining, Reasoning, Tokenization & segmentation; often with Greg Durrett, Swarat Chaudhuri, Xi Ye.

2 papers in our library · 2020–2023

OpenAlex · h-index 5 · 20 works · 222 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 206 times in our library · ⭐ Paper Stars ranking: #4959

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 States2026 · 1 papercurrent🎓Carnegie Mellon UniversityPittsburgh · United States2026 · 1 papercurrent🎓University of MinnesotaMinneapolis · United States2026 · 1 papercurrent🎓The University of Texas at AustinAustin · United States2020–2024 · 10 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksPolitical Science and International Relations · 1 workSocial Sciences · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workTokenization & segmentation · 1 workReasoning · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Subword tokenization · 1 work

 Works by year

2020s

20231 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Byte Pair Encoding is Suboptimal for Language Model Pretraining (2020 · 310 citations)
    The authors test whether the subword tokenization algorithm affects the quality of pretrained language models.
  2. MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning (2023 · 74 citations)
    Existing reasoning benchmarks for LLMs tend to fall into two camps. Some use artificial text that rule-based solvers can crack. Others involve commonsense but only one or two inference steps. MuSR (Multistep Soft Reasoning) targets the gap between them: long natural-language narratives whose solution requires both…

 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 206 times (of the 149,439 papers whose bibliographies we read); 59 citing papers with a page here →.

Updated

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