| 2025 | NAACL | Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning. | Jeffrey Olmo, Jared Wilson, Max Forsey, Bryce Hepner, Thomas Vin Howe, David Wingate |
| 2023 | ICLR | Leveraging Large Language Models for Multiple Choice Question Answering. | Joshua Robinson, David Wingate |
| 2022 | ACL | An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. | Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting, Alexander Glenn Shaw, Kyle Jeffrey Rogers, Alexia Pauline Delorey, Mahmoud Khalil, Nancy Fulda, David Wingate |
| 2022 | EMNLP | Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models. | David Wingate, Mohammad Shoeybi, Taylor Sorensen |
| 2018 | AAAI | Threat, Explore, Barter, Puzzle: A Semantically-Informed Algorithm for Extracting Interaction Modes. | Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate |
| 2017 | CoRL | Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora. | Nancy Fulda, Nathan Tibbetts, Zachary Brown, David Wingate |
| 2017 | IJCAI | What Can You Do with a Rock? Affordance Extraction via Word Embeddings. | Nancy Fulda, Daniel Ricks, Ben Murdoch, David Wingate |
| 2017 | IROS | Deep visual gravity vector detection for unmanned aircraft attitude estimation. | Gary J. Ellingson, David Wingate, Timothy W. McLain |
| 2014 | ICML | A Physics-Based Model Prior for Object-Oriented MDPs. | Jonathan Scholz, Martin Levihn, Charles Lee Isbell Jr., David Wingate |
| 2011 | ICML | Infinite Dynamic Bayesian Networks. | Finale Doshi, David Wingate, Joshua B. Tenenbaum, Nicholas Roy |
| 2011 | IJCAI | Bayesian Policy Search with Policy Priors. | David Wingate, Noah D. Goodman, Daniel M. Roy, Leslie Pack Kaelbling, Joshua B. Tenenbaum |
| 2009 | ICML | Workshop summary: Results of the 2009 reinforcement learning competition. | David Wingate, Carlos Diuk, Lihong Li, Matthew Taylor, Jordan Frank |
| 2009 | UAI | A Bayesian Sampling Approach to Exploration in Reinforcement Learning. | John Asmuth, Lihong Li, Michael L. Littman, Ali Nouri, David Wingate |
| 2009 | UAI | The Infinite Latent Events Model. | David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum |
| 2008 | ICML | Efficiently learning linear-linear exponential family predictive representations of state. | David Wingate, Satinder Singh |
| 2007 | IJCAI | Relational Knowledge with Predictive State Representations. | David Wingate, Vishal Soni, Britton Wolfe, Satinder Singh |
| 2006 | AAAI | Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. | David Wingate, Satinder Singh |
| 2006 | ICML | Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. | David Wingate, Satinder Singh |
| 2005 | UAI | Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. | Matthew R. Rudary, Satinder Singh, David Wingate |
| 2004 | ICML | P3VI: a partitioned, prioritized, parallel value iterator. | David Wingate, Kevin D. Seppi |
| 2004 | ICMLA | Variable resolution discretization in the joint space. | Christopher K. Monson, David Wingate, Kevin D. Seppi, Todd S. Peterson |
| 2003 | ICMLA | Efficient Value Iteration Using Partitioned Models. | David Wingate, Kevin D. Seppi |