Eric Wong

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 43

Top Topics

Copyright Infringement

Semantic Smoothing

Top Venues

Tiny Papers @ ICLR

Publications

Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR (2024)
Chaehyeon Kim, Weiqiu You, Shreya Havaldar, Eric Wong
Evaluating Groups of Features via Consistency, Contiguity, and Stability. Tiny Papers @ ICLR (2024)
Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, Eric Wong
Avoiding Copyright Infringement via Machine Unlearning. CoRR (2024)
Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR (2024)
Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong
Towards Compositionality in Concept Learning. CoRR (2024)
Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang
Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. CoRR (2024)
Yinjun Wu, Mayank Keoliya, Kan Chen, Neelay Velingker, Ziyang Li, Emily J. Getzen, Qi Long, Mayur Naik, Ravi B. Parikh, Eric Wong
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. CoRR (2024)
Aaditya Naik, Adam Stein, Yinjun Wu, Mayur Naik, Eric Wong
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning. Proc. ACM Program. Lang. 8 (OOPSLA1) (2024)
Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong
Data-Efficient Learning with Neural Programs. CoRR (2024)
Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong
Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. CoRR (2024)
Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar
TopEx: Topic-based Explanations for Model Comparison. Tiny Papers @ ICLR (2023)
Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik
Rectifying Group Irregularities in Explanations for Distribution Shift. CoRR (2023)
Shreya Havaldar, Matthew Pressimone, Eric Wong, Lyle H. Ungar
Comparing Styles across Languages. EMNLP (2023)
Saachi Jain, Hadi Salman, Alaa Khaddaj, Eric Wong, Sung Min Park, Aleksander Madry
A Data-Based Perspective on Transfer Learning. CVPR (2023)
Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong
Do Machine Learning Models Learn Statistical Rules Inferred from Data? ICML (2023)
Aaditya Naik, Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik
MDB: Interactively Querying Datasets and Models. CoRR (2023)
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, Eric Wong
Jailbreaking Black Box Large Language Models in Twenty Queries. CoRR (2023)
Rahul Venkatesh, Eric Wong, Zico Kolter
Adversarial robustness in discontinuous spaces via alternating sampling & descent. WACV (2023)
Alexander Robey, Eric Wong, Hamed Hassani, George J. Pappas
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks. CoRR (2023)
Anton Xue, Rajeev Alur, Eric Wong
Stability Guarantees for Feature Attributions with Multiplicative Smoothing. NeurIPS (2023)
Shreya Havaldar, Adam Stein, Eric Wong, Lyle Ungar
TopEx: Topic-based Explanations for Model Comparison. CoRR (2023)
Shreya Havaldar, Matthew Pressimone, Eric Wong, Lyle H. Ungar
Comparing Styles across Languages. CoRR (2023)
Weiqiu You, Helen Qu, Marco Gatti, Bhuvnesh Jain, Eric Wong
Sum-of-Parts Models: Faithful Attributions for Groups of Features. CoRR (2023)
Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch
Faithful Chain-of-Thought Reasoning. IJCNLP (1) (2023)
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR (2023)
Eric Wong, J. Zico Kolter
Learning perturbation sets for robust machine learning. ICLR (2021)
Shaoru Chen, Eric Wong, J. Zico Kolter, Mahyar Fazlyab
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting. CoRR (2021)
Eric Wong, Tim Schneider, Joerg Schmitt, Frank R. Schmidt, J. Zico Kolter
Neural Network Virtual Sensors for Fuel Injection Quantities with Provable Performance Specifications. CoRR (2020)
Eric Wong, J. Zico Kolter
Learning perturbation sets for robust machine learning. CoRR (2020)
Leslie Rice, Eric Wong, J. Zico Kolter
Overfitting in adversarially robust deep learning. CoRR (2020)
Leslie Rice, Eric Wong, J. Zico Kolter
Overfitting in adversarially robust deep learning. ICML (2020)
Eric Wong, Leslie Rice, J. Zico Kolter
Fast is better than free: Revisiting adversarial training. ICLR (2020)
Pratyush Maini, Eric Wong, J. Zico Kolter
Adversarial Robustness Against the Union of Multiple Perturbation Models. ICML (2020)
Eric Wong, Leslie Rice, J. Zico Kolter
Fast is better than free: Revisiting adversarial training. CoRR (2020)
Eric Wong, Tim Schneider, Joerg Schmitt, Frank R. Schmidt, J. Zico Kolter
Neural Network Virtual Sensors for Fuel Injection Quantities with Provable Performance Specifications. IV (2020)
Eric Wong, Frank R. Schmidt, J. Zico Kolter
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations. CoRR (2019)
Eric Wong, Frank R. Schmidt, J. Zico Kolter
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations. ICML (2019)
Pratyush Maini, Eric Wong, J. Zico Kolter
Adversarial Robustness Against the Union of Multiple Perturbation Models. CoRR (2019)
Eric Wong, Frank R. Schmidt, Jan Hendrik Metzen, J. Zico Kolter
Scaling provable adversarial defenses. NeurIPS (2018)
Eric Wong, J. Zico Kolter
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope. ICML (2018)
Eric Wong, Frank R. Schmidt, Jan Hendrik Metzen, J. Zico Kolter
Scaling provable adversarial defenses. CoRR (2018)
J. Zico Kolter, Eric Wong
Provable defenses against adversarial examples via the convex outer adversarial polytope. CoRR (2017)
Alnur Ali, Eric Wong, J. Zico Kolter
A Semismooth Newton Method for Fast, Generic Convex Programming. ICML (2017)
Eric Wong, J. Zico Kolter
An SVD and Derivative Kernel Approach to Learning from Geometric Data. AAAI (2015)