| 2026 | ACL | NSF-SciFy: Mining the NSF Awards Database for Scientific Claims. | Delip Rao, Weiqiu You, Eric Wong, Chris Callison-Burch |
| 2025 | ACL | Towards Style Alignment in Cross-Cultural Translation. | Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar |
| 2025 | EMNLP | Adaptively profiling models with task elicitation. | Davis Brown, Prithvi Balehannina, Helen Jin, Shreya Havaldar, Hamed Hassani, Eric Wong |
| 2025 | EMNLP | Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs. | Andong Hua, Kenan Tang, Chenhe Gu, Jindong Gu, Eric Wong, Yao Qin |
| 2025 | EMNLP | Probabilistic Soundness Guarantees in LLM Reasoning Chains. | Weiqiu You, Anton Xue, Shreya Havaldar, Delip Rao, Helen Jin, Chris Callison-Burch, Eric Wong |
| 2025 | ICLR | Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. | Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong |
| 2025 | ICML | DOLPHIN: A Programmable Framework for Scalable Neurosymbolic Learning. | Aaditya Naik, Jason Liu, Claire Wang, Amish Sethi, Saikat Dutta, Mayur Naik, Eric Wong |
| 2025 | ICML | Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups. | Weiqiu You, Helen Qu, Marco Gatti, Bhuvnesh Jain, Eric Wong |
| 2025 | IJCNLP | Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. | Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang |
| 2025 | NAACL | Avoiding Copyright Infringement via Large Language Model Unlearning. | Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, Eric Wong |
| 2024 | CVPR | Initialization Matters for Adversarial Transfer Learning. | Andong Hua, Jindong Gu, Zhiyu Xue, Nicholas Carlini, Eric Wong, Yao Qin |
| 2024 | ICLR | SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. | Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu |
| 2024 | ICLR | Evaluating Groups of Features via Consistency, Contiguity, and Stability. | Chaehyeon Kim, Weiqiu You, Shreya Havaldar, Eric Wong |
| 2024 | ICML | Towards Compositionality in Concept Learning. | Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong |
| 2024 | ICML | DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. | Yinjun Wu, Mayank Keoliya, Kan Chen, Neelay Velingker, Ziyang Li, Emily J. Getzen, Qi Long, Mayur Naik, Ravi B. Parikh, Eric Wong |
| 2023 | CVPR | A Data-Based Perspective on Transfer Learning. | Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry |
| 2023 | EMNLP | Comparing Styles across Languages. | Shreya Havaldar, Matthew Pressimone, Eric Wong, Lyle H. Ungar |
| 2023 | ICLR | TopEx: Topic-based Explanations for Model Comparison. | Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar |
| 2023 | ICML | Do Machine Learning Models Learn Statistical Rules Inferred from Data? | Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong |
| 2023 | IJCNLP | Faithful Chain-of-Thought Reasoning. | Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch |
| 2023 | WACV | Adversarial robustness in discontinuous spaces via alternating sampling & descent. | Rahul Mysore Venkatesh, Eric Wong, Zico Kolter |
| 2022 | CVPR | Certified Patch Robustness via Smoothed Vision Transformers. | Hadi Salman, Saachi Jain, Eric Wong, Aleksander Madry |
| 2022 | ICLR | Missingness Bias in Model Debugging. | Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry |
| 2021 | ICLR | Learning perturbation sets for robust machine learning. | Eric Wong, J. Zico Kolter |
| 2021 | ICML | Leveraging Sparse Linear Layers for Debuggable Deep Networks. | Eric Wong, Shibani Santurkar, Aleksander Madry |
| 2020 | HCI | Haptic Pattern Exploration in an Arm-Mounted Solenoid Array. | Dean Dijour, Aadya Krishnaprasad, Ian Shei, Eric Wong |
| 2020 | ICLR | Fast is better than free: Revisiting adversarial training. | Eric Wong, Leslie Rice, J. Zico Kolter |
| 2020 | ICML | Adversarial Robustness Against the Union of Multiple Perturbation Models. | Pratyush Maini, Eric Wong, J. Zico Kolter |
| 2020 | ICML | Overfitting in adversarially robust deep learning. | Leslie Rice, Eric Wong, J. Zico Kolter |
| 2019 | ICML | Wasserstein Adversarial Examples via Projected Sinkhorn Iterations. | Eric Wong, Frank R. Schmidt, J. Zico Kolter |
| 2018 | ICML | Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope. | Eric Wong, J. Zico Kolter |
| 2017 | ICML | A Semismooth Newton Method for Fast, Generic Convex Programming. | Alnur Ali, Eric Wong, J. Zico Kolter |
| 2015 | AAAI | An SVD and Derivative Kernel Approach to Learning from Geometric Data. | Eric Wong, J. Zico Kolter |
| 2007 | ICCD | Whitespace redistribution for thermal via insertion in 3D stacked ICs. | Eric Wong, Sung Kyu Lim |
| 2006 | DATE | 3D floorplanning with thermal vias. | Eric Wong, Sung Kyu Lim |
| 2006 | ICCAD | Decoupling capacitor planning and sizing for noise and leakage reduction. | Eric Wong, Jacob R. Minz, Sung Kyu Lim |
| 2004 | SIGGRAPH | There's more than one way to skin a wolf: wolf transformations in "Van Helsing". | Nigel Sumner, Ari Rapkin, Steve Aplin, Andrew Cawrse, Lee Fulton, Tony Pelle, Philip Peterson, Eric Wong |
| 1999 | SIGGRAPH | LIDAR: reality capture. | Eric Wong, Dennis Martin, Daniel Chudak, Alan Lasky, Grant McKinney, Lisa Simon-Parker, Benedikt Wolff, Guy Cutting, Wilvia Uchida, Ben Kacyra, Barbara Kacyra |