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Julian Dolby

Julian Dolby has 2 papers in our library, in 2021–2026, most of them on Language models & pretraining, Reasoning; often with Jie Chen, Wei Zhang.

2 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 36 · 153 works · 4,572 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 69 times in our library · ⭐ Paper Stars ranking: #7244

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

🔬IBM Research - Thomas J. Watson Research CenterYorktown Heights · United States2000–2026 · 112 paperscurrent🏢IBMArmonk · United States2000–2025 · 83 papers🎓University of Illinois Urbana-ChampaignUrbana · United States1997–2002 · 7 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).Computer Science · 2 worksComputer Science Applications · 1 workInformation Systems · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20261 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks (2021 · 141 citations)
    AI for Code research has lacked a large, well-curated benchmark comparable to ImageNet. IBM Research addresses this with CodeNet, a dataset built from submissions to two online judge platforms, AIZU and AtCoder. It holds almost 14 million programs, about 500 million lines, in 55 programming languages, grouped under…
  2. Generalization in Graph Reasoning: A Systematic Comparison of LLM Training Approaches (2026)
    The paper asks which training strategy actually helps LLMs reason over graphs in a way that transfers beyond the training setting.

 Co-authors here

2 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 69 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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