🧑‍🔬 Richard S. Zemel

🏛️ Affiliations

🎓Columbia UniversityNew York · United States2020–2026 · 19 paperscurrent🎓University of TorontoToronto · Canada1990–2023 · 135 papers🔬Vector InstituteToronto · Canada2017–2023 · 26 papers🔬Canadian Institute for Advanced ResearchToronto · Canada2014–2019 · 17 papers🏢AmazonSeattle · United States2022–2025 · 12 papers🎓University of ArizonaTucson · United States1997–2000 · 8 papers🤝Salk Institute for Biological StudiesLa Jolla · United States1993–1998 · 6 papers🎓Carnegie Mellon UniversityPittsburgh · United States1994–2002 · 4 papers🎓University of Colorado BoulderBoulder · United States1991–2021 · 3 papers🎓University of RochesterRochester · United States2002–2003 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 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. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (2015 · 7,670 citations)
   The paper tackles automatic image captioning: producing a natural-language sentence that describes a photo.
2. Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books (2015 · 3,083 citations)
   The paper asks whether novels can supply rich, story-level descriptions for film footage, going far beyond the short captions found in existing vision-language datasets.
3. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models (2014 · 1,371 citations)
   The paper addresses automatic image description: learning to match images with sentences and to write new captions.
4. FLIRT: Feedback Loop In-context Red Teaming (2024 · 42 citations)
   The paper tackles automated red teaming: finding inputs that push generative models into producing unsafe content, without expensive human probing.
5. Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic (2022 · 33 citations)
   The paper asks whether sentiment and emotion systems treat people differently depending on gender, race or ethnicity, and on combinations of these.

All works

215 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

1. Show, Attend and Tell: Neural Image Caption Generation with Visual AttentionarXiv:1502.03044Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.2015 · 7,670 citations
2. Prototypical Networks for Few-shot Learning ↗arXiv:1703.05175 · no summary yetJake Snell, Kevin Swersky, Richard S. Zemel2017 · 5,249 citations
3. Fairness through awareness ↗no summary yetCynthia Dwork et al.2012 · 3,499 citations
4. Siamese Neural Networks for One-shot Image Recognition ↗ICML 2015 Deep Learning Workshop · no summary yetGregory Koch, Richard Zemel, Ruslan Salakhutdinov2015 · 3,175 citations
5. Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading BooksarXiv:1506.06724Yukun Zhu, Ryan Kiros, Richard Zemel, et al.2015 · 3,083 citations
6. Shortcut Learning in Deep Neural Networks ↗arXiv:2004.07780 · no summary yetRobert Geirhos et al.2020 · 2,366 citations
7. Advances in Neural Information Processing Systems 5 ↗no summary yetRichard S. Zemel, Christopher K. I. Williams, Michael C. Mozer1993 · 1,854 citations
8. Unifying Visual-Semantic Embeddings with Multimodal Neural Language ModelsarXiv:1411.2539Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel2014 · 1,371 citations
9. Skip-Thought Vectors ↗arXiv (Cornell University) · no summary yetRyan Kiros et al.2015 · 1,267 citations
10. The Helmholtz Machine ↗Neural Computation · no summary yetPeter Dayan et al.1995 · 1,202 citations
11. Autoencoders, Minimum Description Length and Helmholtz Free Energy ↗no summary yetGeoffrey E. Hinton, Richard S. Zemel1993 · 1,073 citations
12. Multiscale conditional random fields for image labeling ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetXuming He, Richard S. Zemel, Miguel Á. Carreira-Perpiñán2004 · 838 citations
13. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks ↗arXiv (Cornell University) · no summary yetWenjie Luo et al.2017 · 771 citations
14. Information processing with population codes ↗Nature reviews. Neuroscience · no summary yetAlexandre Pouget, Peter Dayan, Richard S. Zemel2000 · 753 citations
15. Meta-Learning for Semi-Supervised Few-Shot Classification ↗arXiv (Cornell University) · no summary yetMengye Ren et al.2018 · 742 citations
16. Gated Graph Sequence Neural Networks ↗arXiv:1511.05493 · no summary yetYujia Li et al.2015 · 576 citations
17. Exploring Models and Data for Image Question Answering ↗arXiv:1505.02074 · no summary yetMengye Ren, Ryan Kiros, Richard Zemel2015 · 455 citations
18. I NFERENCE AND C OMPUTATION WITH P OPULATION C ODES ↗Annual Review of Neuroscience · no summary yetAlexandre Pouget, Peter Dayan, Richard S. Zemel2003 · 434 citations
19. Probabilistic Interpretation of Population Codes ↗Neural Computation · no summary yetRichard S. Zemel, Peter Dayan, Alexandre Pouget1998 · 324 citations
20. Collaborative prediction and ranking with non-random missing data ↗ACM Conference on Recommender Systems (RecSys) · no summary yetBenjamin M. Marlin, Richard S. Zemel2009 · 317 citations
21. End-to-End Instance Segmentation with Recurrent Attention ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetMengye Ren, Richard S. Zemel2017 · 305 citations
22. Causal Effect Inference with Deep Latent-Variable Models ↗UvA-DARE (University of Amsterdam) · no summary yetChristos Louizos et al.2017 · 290 citations
23. Neural Relational Inference for Interacting Systems ↗UvA-DARE (University of Amsterdam) · no summary yetThomas Kipf et al.2018 · 281 citations
24. Learning Adversarially Fair and Transferable Representations ↗arXiv (Cornell University) · no summary yetDavid Madras et al.2018 · 204 citations
25. Object-based attention and occlusion: Evidence from normal participants and a computational model. ↗Journal of Experimental Psychology Human Perception & Performance · no summary yetMarlene Behrmann, Richard S. Zemel, Michael C. Mozer1998 · 195 citations

See all 215 works by Richard S. Zemel →

🤝 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

• Ruslan Salakhutdinov ×3
• Ryan Kiros ×3
• Aaron Courville
• Antonio B. Torralba
• Aram Galstyan
• Emily Allaway
• Jimmy Lei Ba
• Kai-Wei Chang
• Kelvin Xu
• Kyunghyun Cho
• Ninareh Mehrabi
• Palash Goyal

Venues

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

• Neural Computation ×9
• neural information processing systems ×9
• IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings ×6
• International Conference on Machine Learning ×6
• The MIT Press eBooks ×5
• International Conference on Learning Representations ×4
• Conference on Empirical Methods in Natural Language Processing (EMNLP) ×3: EMNLP 2024
• International Conference on Artificial Intelligence and Statistics ×3
• Journal of Experimental Psychology Human Perception & Performance ×3
• Lecture notes in computer science ×3
• Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) ×3
• ACM Conference on Fairness, Accountability, and Transparency (FAccT) ×2

🔗 Cited by

Papers of our library cite their works 4,711 times (of the 149,439 papers whose bibliographies we read); 554 citing papers with a page here →.

Updated 30 October 2026

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