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Richard S. Zemel — all works

215 works · page 2 of 3 · 101–200 · ← Richard S. Zemel

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  1. Flexible Priors for Exemplar-based Clustering ↗arXiv (Cornell University) · no summary yetDaniel Tarlow, Richard S. Zemel, Brendan J. Frey2012 · 21 citations
  2. The steerability of large language models toward data-driven personas ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetJunyi Li et al.2024 · 20 citations
  3. Causal Modeling for Fairness in Dynamical Systems ↗arXiv (Cornell University) · no summary yetElliot Creager et al.2019 · 20 citations
  4. Learning unbiased features ↗arXiv (Cornell University) · no summary yetYujia Li, Kevin Swersky, Richard S. Zemel2014 · 20 citations
  5. SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies ↗neural information processing systems · no summary yetSeyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard S. Zemel2019 · 19 citations
  6. Joint Embeddings of Scene Graphs and Images ↗Lirias · no summary yetEugene Belilovsky et al.2017 · 19 citations
  7. Cortical Belief Networks ↗Springer eBooks · no summary yetRichard S. Zemel2003 · 19 citations
  8. On the steerability of large language models toward data-driven personas ↗arXiv (Cornell University) · no summary yetJunyi Li et al.2023 · 18 citations
  9. Semantically Informed Slang Interpretation ↗Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetZhewei Sun, Richard Zemel, Yang Xu2022 · 18 citations
  10. Learning stick-figure models using nonparametric Bayesian priors over trees ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetEdward Meeds et al.2008 · 18 citations
  11. Unsupervised Learning of Skeletons from Motion ↗Lecture notes in computer science · no summary yetDavid A. Ross, Daniel Tarlow, Richard S. Zemel2008 · 18 citations
  12. Unsupervised Learning with Non-Ignorable Missing Data. ↗International Conference on Artificial Intelligence and Statistics · no summary yetBenjamin M. Marlin, Sam T. Roweis, Richard S. Zemel2005 · 18 citations
  13. Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies ↗Findings of the Association for Computational Linguistics: NAACL 2024 · no summary yetAnaelia Ovalle et al.2024 · 17 citations
  14. Learning a Universal Template for Few-shot Dataset Generalization ↗arXiv (Cornell University) · no summary yetEleni Triantafillou et al.2021 · 17 citations
  15. Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification ↗arXiv (Cornell University) · no summary yetRobert Adragna et al.2020 · 17 citations
  16. Wandering Within a World: Online Contextualized Few-Shot Learning ↗arXiv (Cornell University) · no summary yetMengye Ren et al.2020 · 17 citations
  17. Neural Guided Constraint Logic Programming for Program Synthesis ↗arXiv (Cornell University) · no summary yetLisa Zhang et al.2018 · 17 citations
  18. Graph cuts is a max-product algorithm ↗no summary yetDaniel Tarlow et al.2011 · 17 citations
  19. Learning population coes by minimizing description length ↗no summary yetRichard S. Zemel, Geoffrey E. Hinton1999 · 17 citations
  20. Reliable disparity estimation through selective integration ↗Visual Neuroscience · no summary yetMichael S. Gray et al.1998 · 17 citations
  21. Resolving Ambiguities in Text-to-Image Generative Models ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetNinareh Mehrabi et al.2023 · 16 citations
  22. Combining discriminative features to infer complex trajectories ↗International Conference on Machine Learning · no summary yetDavid A. Ross, Simon Osindero, Richard S. Zemel2006 · 16 citations
  23. Occlusion, symmetry, and object-based attention: Reply to Saiki (2000). ↗Journal of Experimental Psychology Human Perception & Performance · no summary yetMarlene Behrmann, Richard S. Zemel, Michael C. Mozer2000 · 16 citations
  24. Understanding the Limitations of Conditional Generative Models ↗arXiv (Cornell University) · no summary yetEthan Fetaya et al.2019 · 15 citations
  25. CRF framework for supervised preference aggregation ↗Proceedings of the ... ACM International Conference on Information & Knowledge Management · no summary yetMaksims Volkovs, Richard S. Zemel2013 · 15 citations
  26. Efficient Multiple Instance Metric Learning Using Weakly Supervised Data ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetMarc T. Law et al.2017 · 14 citations
  27. Towards Generalizable Sentence Embeddings ↗Proceedings of the 1st Workshop on Representation Learning for NLP · no summary yetEleni Triantafillou et al.2016 · 14 citations
  28. Directional-Unit Boltzmann Machines ↗neural information processing systems · no summary yetRichard S. Zemel, Christopher K. I. Williams, Michael C. Mozer1992 · 14 citations
  29. Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes ↗arXiv (Cornell University) · no summary yetJames Lucas et al.2021 · 13 citations
  30. Latent topic random fields: Learning using a taxonomy of labels ↗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. Zemel2008 · 13 citations
  31. Combining probabilistic population codes ↗no summary yetRichard S. Zemel, Peter Dayan1997 · 13 citations
  32. Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach ↗arXiv (Cornell University) · no summary yetMartin Mladenov et al.2020 · 12 citations
  33. A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ↗arXiv (Cornell University) · no summary yetRenjie Liao, Raquel Urtasun, Richard S. Zemel2020 · 11 citations
  34. Aggregated Momentum: Stability Through Passive Damping ↗arXiv (Cornell University) · no summary yetJames Lucas et al.2018 · 10 citations
  35. Probabilistic Sequential Independent Components Analysis ↗IEEE Transactions on Neural Networks · no summary yetMax Welling, Richard S. Zemel, Geoffrey E. Hinton2004 · 10 citations
  36. Slang Generation as Categorization. ↗eScholarship (California Digital Library) · no summary yetZhewei Sun, Richard S. Zemel, Yang Xu2019 · 9 citations
  37. Gradient-based Optimization of Neural Network Architecture. ↗International Conference on Learning Representations · no summary yetWill Grathwohl et al.2018 · 9 citations
  38. Dimensionality Reduction for Representing the Knowledge of Probabilistic Models ↗International Conference on Learning Representations · no summary yetMarc T. Law et al.2018 · 9 citations
  39. Exchanging Lessons Between Algorithmic Fairness and Domain Generalization ↗arXiv (Cornell University) · no summary yetElliot Creager, Joern-Henrik Jacobsen, Richard S. Zemel2021 · 8 citations
  40. Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes ↗arXiv (Cornell University) · no summary yetJake Snell, Richard S. Zemel2020 · 8 citations
  41. Leveraging user libraries to bootstrap collaborative filtering ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetLaurent Charlin, Richard S. Zemel, Hugo Larochelle2014 · 8 citations
  42. On the Expressive Power of Restricted Boltzmann Machines. ↗neural information processing systems · no summary yetJames Martens et al.2013 · 8 citations
  43. Encoding multiple orientations in a recurrent network ↗Neurocomputing · no summary yetRichard S. Zemel, Jonathan W. Pillow2000 · 8 citations
  44. Efficient Sampling for Bipartite Matching Problems ↗no summary yetMaksims Volkovs, Richard S. Zemel2012 · 7 citations
  45. Loss-sensitive Training of Probabilistic Conditional Random Fields ↗arXiv (Cornell University) · no summary yetMaksims Volkovs, Hugo Larochelle, Richard S. Zemel2011 · 7 citations
  46. Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models ↗arXiv (Cornell University) · no summary yetThomas P. Zollo et al.2023 · 6 citations
  47. Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ↗International Conference on Learning Representations · no summary yetLisa Zhang et al.2018 · 6 citations
  48. Online Queries for Collaborative Filtering ↗no summary yetCraig E. Boutilier, Richard S. Zemel2010 · 6 citations
  49. Population Coding with Motion Energy Filters: The Impact of Correlations ↗Neural Computation · no summary yetFrançois Klam, Richard S. Zemel, Alexandre Pouget2007 · 6 citations
  50. Minimizing Description Length in an Unsupervised Neural Network ↗no summary yetGeo rey E. Hinton, Richard S. Zemel2000 · 6 citations
  51. Minimum description length analysis ↗no summary yetRichard S. Zemel1998 · 6 citations
  52. Whiteboard-of-Thought: Thinking Step-by-Step Across Modalities ↗Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · no summary yetSachit Menon, Richard Zemel, Carl Vondrick2024 · 5 citations
  53. Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions ↗arXiv (Cornell University) · no summary yetJake C. Snell et al.2022 · 5 citations
  54. SketchEmbedNet: Learning Novel Concepts by Imitating Drawings ↗International Conference on Machine Learning · no summary yetAlexander Wang, Mengye Ren, Richard S. Zemel2021 · 5 citations
  55. Understanding the Relation Between Maximum-Entropy Inverse Reinforcement Learning and Behaviour Cloning. ↗International Conference on Learning Representations · no summary yetSeyed Kamyar Seyed Ghasemipour, Shane Gu, Richard S. Zemel2019 · 5 citations
  56. Efficient Parametric Projection Pursuit Density Estimation ↗arXiv (Cornell University) · no summary yetMax Welling, Richard S. Zemel, Geoffrey E. Hinton2012 · 5 citations
  57. Towards Effective Discrimination Testing for Generative AI ↗ACM Conference on Fairness, Accountability, and Transparency (FAccT) · no summary yetThomas P. Zollo et al.2025 · 4 citations
  58. JAB: Joint Adversarial Prompting and Belief Augmentation ↗arXiv (Cornell University) · no summary yetNinareh Mehrabi et al.2023 · 4 citations
  59. An Active Approach to Collaborative Filtering. ↗International Conference on Artificial Intelligence and Statistics · no summary yetRichard S. Zemel, Craig E. Boutilier2003 · 4 citations
  60. Managing Uncertainty in Cue Combination ↗no summary yetZhiyong Yang, Richard S. Zemel1999 · 4 citations
  61. Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex ↗neural information processing systems · no summary yetRichard S. Zemel, Terrence J. Sejnowski1994 · 4 citations
  62. Unsupervised learning of object models ↗no summary yetChristopher Williams, Richard S. Zemel, Michael C. Mozer1993 · 4 citations
  63. Guiding LLM Decision-Making with Fairness Reward Models ↗neural information processing systems · no summary yetZara Hall et al.2025 · 3 citations
  64. Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification ↗Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yetTao Meng et al.2024 · 3 citations
  65. ICL Markup: Structuring In-Context Learning using Soft-Token Tags ↗arXiv (Cornell University) · no summary yetMarc-Etienne Brunet, Ashton Anderson, Richard S. Zemel2023 · 3 citations
  66. Theoretical bounds on estimation error for meta-learning ↗arXiv (Cornell University) · no summary yetJames Lucas et al.2020 · 3 citations
  67. Out-of-distribution Detection in Few-shot Classification ↗no summary yetKuan-Chieh Wang et al.2019 · 3 citations
  68. Dynamic Cue Combination in Distributional Population Code Networks ↗Oxford University Press eBooks · no summary yetRama D Natarajan, Richard S. Zemel2011 · 3 citations
  69. Interpreting Graph Cuts as a Max-Product Algorithm ↗arXiv (Cornell University) · no summary yetDaniel Tarlow et al.2011 · 3 citations
  70. Learning Articulated Skeletons from Motion ↗no summary yetDavid A. Ross, Daniel Tarlow, Richard S. Zemel2007 · 3 citations
  71. Learning Population Codes by Minimizing Description Length ↗The MIT Press eBooks · no summary yetRichard S. Zemel, Geoffrey E. Hinton1999 · 3 citations
  72. Adaptive Elicitation of Latent Information Using Natural Language ↗arXiv (Cornell University) · no summary yetWang, Jimmy et al.2025 · 2 citations
  73. Towards Safety Reasoning in LLMs: AI-agentic Deliberation for Policy-embedded CoT Data Creation ↗Findings of the Association for Computational Linguistics: ACL 2025 · no summary yetTharindu Kumarage et al.2025 · 2 citations
  74. Training-free Deep Concept Injection Enables Language Models for Video Question Answering ↗Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · no summary yetXudong Lin et al.2024 · 2 citations
  75. Controlling the World by Sleight of Hand ↗Lecture notes in computer science · no summary yetSruthi Sudhakar et al.2024 · 2 citations
  76. Improving Predictor Reliability with Selective Recalibration ↗arXiv (Cornell University) · no summary yetThomas P. Zollo et al.2024 · 2 citations
  77. SurfsUp: Learning Fluid Simulation for Novel Surfaces ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetArjun Mani et al.2023 · 2 citations
  78. Lorentzian Distance Learning ↗no summary yetMarc T. Law, Jake Snell, Richard S. Zemel2018 · 2 citations
  79. Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data ↗arXiv (Cornell University) · no summary yetDavid Madras et al.2018 · 2 citations
  80. A Generative Model for Attractor Dynamics ↗neural information processing systems · no summary yetRichard S. Zemel, Michael C. Mozer1999 · 2 citations
  81. Learning to Segment Images Using Dynamic Feature Binding ; CU-CS-540-91 ↗CU Scholar (University of Colorado Boulder) · no summary yetMichael C. Mozer, Richard S. Zemel, Marlene Behrmann1991 · 2 citations
  82. Integrating Present and Past in Unsupervised Continual Learning ↗arXiv (Cornell University) · no summary yetYipeng Zhang et al.2024 · 1 citation
  83. Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift ↗arXiv (Cornell University) · no summary yetBenjamin Eyre et al.2023 · 1 citation
  84. Coordinated Replay Sample Selection for Continual Federated Learning ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track · no summary yetJack Good et al.2023 · 1 citation
  85. Disentanglement and Generalization Under Correlation Shifts ↗arXiv (Cornell University) · no summary yetChristina M. Funke et al.2021 · 1 citation
  86. On Monotonic Linear Interpolation of Neural Network Parameters ↗International Conference on Machine Learning · no summary yetJames Lucas et al.2021 · 1 citation
  87. Learning Flexible Classifiers with Shot-CONditional Episodic (SCONE) Training ↗no summary yetEleni Triantafillou et al.2021 · 1 citation
  88. Unintended cue learning: Lessons for deep learning from experimental psychology ↗Journal of Vision · no summary yetRobert Geirhos et al.2020 · 1 citation
  89. Dualing GANs ↗arXiv (Cornell University) · no summary yetYujia Li et al.2017 · 1 citation
  90. Stochastic Segmentation Trees for Multiple Ground Truths. ↗Uncertainty in Artificial Intelligence · no summary yetJake Snell, Richard S. Zemel2017 · 1 citation
  91. Population Codes ↗The MIT Press eBooks · no summary yetAlexandre Pouget, Richard S. Zemel2006 · 1 citation
  92. Schemex: Discovering Structural Abstractions from Examples ↗arXiv:2504.11795 · no summary yetSitong Wang et al.2026
  93. QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions ↗arXiv (Cornell University) · no summary yetZhun Deng et al.2025
  94. Replay Can Provably Increase Forgetting ↗arXiv (Cornell University) · no summary yetYasaman Mahdaviyeh et al.2025
  95. Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Heads ↗arXiv (Cornell University) · no summary yetTodd Morrill et al.2025
  96. Test-Time Warmup for Multimodal Large Language Models ↗arXiv (Cornell University) · no summary yetNikita Rajaneesh, Thomas P. Zollo, Richard S. Zemel2025
  97. Confidence Calibration in Vision-Language-Action Models ↗arXiv (Cornell University) · no summary yetThomas P. Zollo, Richard S. Zemel2025
  98. Partial Federated Learning ↗arXiv (Cornell University) · no summary yetTiantian Feng et al.2024
  99. Online Algorithmic Recourse by Collective Action ↗arXiv (Cornell University) · no summary yetElliot Creager, Richard S. Zemel2023
  100. Incorporating Fairness in Large Scale NLU Systems ↗no summary yetRahul Gupta et al.2023

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