🧑‍🔬 James L. McClelland

🏛️ Affiliations

🎓Stanford UniversityStanford · United States2001–2026 · 115 papersEmployment since 2006 · Professor, Psychology and Center for Mind Brain and Computationcurrent🎓Carnegie Mellon UniversityPittsburgh · United States1985–2020 · 93 papersEmployment🔬Center for the Neural Basis of CognitionPittsburgh · United States1994–2020 · 43 papers🎓University of California San DiegoSan Diego · United States1975–1988 · 17 papers🏢Google DeepMindLondon · United Kingdom2020–2024 · 3 papers🎓University of PittsburghPittsburgh · United States1985–2018 · 3 papersEmployment🏛️Medical Research CouncilLondon · United Kingdom1996–2020 · 2 papers🎓University of Southern CaliforniaLos Angeles · United States1996–2020 · 2 papers🎓University of ManchesterManchester · United Kingdom2009–2018 · 2 papers🎓University of PennsylvaniaPhiladelphia · United States1973–1975 · 2 papersEducation since 1975 · PhD in Cognitive Psychology, Psychology

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 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.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Exact solutions to the nonlinear dynamics of learning in deep linear neural networks (2013 · 1,027 citations)
   Why deep networks train slowly, stall on long plateaus and then suddenly improve, and benefit from certain initializations has lacked a quantitative explanation.
2. Can language models learn from explanations in context? (2022 · 295 citations)
   Large language models can pick up new tasks from a handful of in-context examples. The authors test whether adding explanations to those examples, as people do when teaching, also helps models. They took 40 difficult tasks and subtasks from BIG-bench. For each, one author wrote post-answer explanations for 15 sampled…
3. Language models show human-like content effects on reasoning tasks (2022 · 162 citations)
   Ideally, abstract reasoning should not depend on what a problem is about. Yet people reason better when a problem's meaning agrees with the logically correct answer. Psychologists call these "content effects." This paper asks whether large language models, whose expectations come from human-written text, blend…

All works

5 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. Exact solutions to the nonlinear dynamics of learning in deep linear neural networksarXiv:1312.6120Andrew M. Saxe, James L. McClelland, Surya Ganguli2013 · 1,027 citations
2. Can language models learn from explanations in context?Findings of the Association for Computational LinguisticsAndrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.2022 · 295 citations
3. Language models show human-like content effects on reasoning tasksarXiv:2207.07051Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.2022 · 162 citations
4. Data Distributional Properties Drive Emergent In-Context Learning in Transformers ↗arXiv:2205.05055 · no summary yetStephanie C. Y. Chan et al.2022 · 158 citations
5. Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models ↗Proceedings of the National Academy of Sciences · no summary yetJames L. McClelland et al.2020 · 104 citations

🤝 Co-authors here

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

• Andrew Lampinen ×2
• Antonia Creswell ×2
• Felix Hill ×2
• Ishita Dasgupta ×2
• Stephanie Chan ×2
• Surya Ganguli

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2022
• Proceedings of the National Academy of Sciences

🔗 Cited by

Papers of our library cite their works 476 times (of the 149,439 papers whose bibliographies we read); 113 citing papers with a page here →.

Updated 2 November 2026

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