🧑‍🔬 Jack W. Rae

🏛️ Affiliations

🏢GoogleMountain View · United States2016–2022 · 12 papers🏢Google DeepMindLondon · United Kingdom2016–2021 · 10 papers🎓University College LondonLondon · United Kingdom2018–2021 · 9 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.

📅 Works by year

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Compressive Transformers for Long-Range Sequence Modelling (2019 · 340 citations)
   Transformer language models keep detailed activations of past tokens, but storing and attending over long histories gets expensive.
2. Reducing Sentiment Bias in Language Models via Counterfactual Evaluation (2019 · 104 citations)
   The paper examines whether text produced by large language models carries sentiment bias, where the tone of a continuation shifts depending on which country, occupation or person name appears in the prompt.

All works

9 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Scaling Language Models: Methods, Analysis & Insights from Training Gopher ↗arXiv:2112.11446 · no summary yetJack W. Rae et al.2021 · 928 citations
2. Improving language models by retrieving from trillions of tokens ↗arXiv:2112.04426 · no summary yetSebastian Borgeaud et al.2021 · 869 citations
3. Compressive Transformers for Long-Range Sequence ModellingarXiv:1911.05507Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.2019 · 340 citations
4. Unsupervised Predictive Memory in a Goal-Directed Agent ↗arXiv (Cornell University) · no summary yetGreg Wayne et al.2018 · 140 citations
5. Unified Scaling Laws for Routed Language Models ↗arXiv (Cornell University) · no summary yetAidan Clark et al.2022 · 111 citations
6. Reducing Sentiment Bias in Language Models via Counterfactual EvaluationarXiv:1911.03064Po-Sen Huang, Huan Zhang, Ray Jiang, et al.2019 · 104 citations
7. Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes ↗arXiv (Cornell University) · no summary yetJack W. Rae et al.2016 · 81 citations
8. Relational recurrent neural networks ↗arXiv (Cornell University) · no summary yetAdam Santoro et al.2018 · 43 citations
9. Memory-based Parameter Adaptation ↗arXiv (Cornell University) · no summary yetPablo Sprechmann et al.2018 · 42 citations

🤝 Co-authors here

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

• Anna Potapenko
• Dani Yogatama
• Huan Zhang
• Johannes Welbl
• Po-Sen Huang
• Pushmeet Kohli
• Robert Stanforth
• Timothy Lillicrap
• Vishal Maini

Venues

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

• Conference on Neural Information Processing Systems (NeurIPS)

🔗 Cited by

Papers of our library cite their works 17,168 times (of the 149,439 papers whose bibliographies we read); 3,050 citing papers with a page here →.

Updated 2 November 2026

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