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Yangjun Ruan

Yangjun Ruan has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Evaluation & benchmarks; often with Chris J. Maddison, Tatsunori Hashimoto, Andrew Wang.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 6 · 20 works · 628 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 127 times in our library · ⭐ Paper Stars ranking: #7329

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

🎓University of TorontoToronto · Canada2021–2025 · 8 papers🔬Vector InstituteToronto · Canada2022–2025 · 6 papers🎓Zhejiang UniversityHangzhou · China2019 · 2 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksSocial Sciences · 1 workSafety Research · 1 workSoftware · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Scaling laws · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Identifying the Risks of LM Agents with an LM-Emulated Sandbox (2023 · 96 citations)
    LM agents that call external tools, such as banking APIs, terminals or smart-home devices, can cause serious harm when they misread a request.
  2. Observational Scaling Laws and the Predictability of Language Model Performance (2024 · 40 citations)
    Classical scaling laws relate the training compute budget to the quality of a language model. Building them requires training a series of models of different sizes oneself, which few can afford. The authors propose an "observational" approach: instead of training, they take about a hundred open models and their…

 Co-authors here

8 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 127 times (of the 149,439 papers whose bibliographies we read); 26 citing papers with a page here →.

Updated

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