Interpreting Interpretations: Organizing Attribution Methods by Criteria. - Zifan Wang 001; Piotr Mardziel; Anupam Datta; Matt Fredrikson (CVPR Workshops, 2020)

Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks. - Haofan Wang; Zifan Wang 001; Mengnan Du; Fan Yang 023; Zijian Zhang; Sirui Ding; Piotr Mardziel; Xia Hu 001 (CVPR Workshops, 2020)

Smoothed Geometry for Robust Attribution. - Zifan Wang 001; Haofan Wang; Shakul Ramkumar; Piotr Mardziel; Matt Fredrikson; Anupam Datta (NeurIPS, 2020)

Towards Behavior-Level Explanation for Deep Reinforcement Learning. - Xuan Chen; Zifan Wang 001; Yucai Fan; Bonan Jin; Piotr Mardziel; Carlee Joe-Wong; Anupam Datta (CoRR, 2020)

Abstracting Influence Paths for Explaining (Contextualization of) BERT Models. - Kaiji Lu; Zifan Wang 001; Piotr Mardziel; Anupam Datta (CoRR, 2020)

Globally-Robust Neural Networks. - Klas Leino; Zifan Wang 001; Matt Fredrikson (ICML, 2021)

Machine Learning Explainability and Robustness: Connected at the Hip. - Anupam Datta; Matt Fredrikson; Klas Leino; Kaiji Lu; Shayak Sen; Zifan Wang 001 (KDD, 2021)

Exploring Conceptual Soundness with TruLens. - Anupam Datta; Matt Fredrikson; Klas Leino; Kaiji Lu; Shayak Sen; Ricardo Shih; Zifan Wang 001 (NeurIPS (Competition and Demos), 2021)

Influence Patterns for Explaining Information Flow in BERT. - Kaiji Lu; Zifan Wang 001; Piotr Mardziel; Anupam Datta (NeurIPS, 2021)

Boundary Attributions Provide Normal (Vector) Explanations. - Zifan Wang 001; Matt Fredrikson; Anupam Datta (CoRR, 2021)

Consistent Counterfactuals for Deep Models. - Emily Black; Zifan Wang 001; Matt Fredrikson; Anupam Datta (CoRR, 2021)

Consistent Counterfactuals for Deep Models. - Emily Black; Zifan Wang 001; Matt Fredrikson (ICLR, 2022)

Robust Models Are More Interpretable Because Attributions Look Normal. - Zifan Wang 001; Matt Fredrikson; Anupam Datta (ICML, 2022)

Faithful Explanations for Deep Graph Models. - Zifan Wang 001; Yuhang Yao; Chaoran Zhang; Han Zhang 037; Youjie Kang; Carlee Joe-Wong; Matt Fredrikson; Anupam Datta (CoRR, 2022)

Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. - Zifan Wang 001; Nan Ding 002; Tomer Levinboim; Xi Chen 071; Radu Soricut (CVPR, 2023)

On the Perils of Cascading Robust Classifiers. - Ravi Mangal; Zifan Wang 001; Chi Zhang; Klas Leino; Corina S. Pasareanu; Matt Fredrikson (ICLR, 2023)

Unlocking Deterministic Robustness Certification on ImageNet. - Kai Hu; Andy Zou; Zifan Wang 001; Klas Leino; Matt Fredrikson (NeurIPS, 2023)

Grounding Neural Inference with Satisfiability Modulo Theories. - Zifan Wang 001; Saranya Vijayakumar; Kaiji Lu; Vijay Ganesh 001; Somesh Jha; Matt Fredrikson (NeurIPS, 2023)

Learning Modulo Theories. - Matt Fredrikson; Kaiji Lu; Saranya Vijayakumar; Somesh Jha; Vijay Ganesh 001; Zifan Wang 001 (CoRR, 2023)

Scaling in Depth: Unlocking Robustness Certification on ImageNet. - Kai Hu; Andy Zou; Zifan Wang 001; Klas Leino; Matt Fredrikson (CoRR, 2023)

Universal and Transferable Adversarial Attacks on Aligned Language Models. - Andy Zou; Zifan Wang 001; J. Zico Kolter; Matt Fredrikson (CoRR, 2023)

Representation Engineering: A Top-Down Approach to AI Transparency. - Andy Zou; Long Phan; Sarah Li Chen; James Campbell; Phillip Guo; Richard Ren; Alexander Pan; Xuwang Yin; Mantas Mazeika; Ann-Kathrin Dombrowski; Shashwat Goel; Nathaniel Li; et al. (CoRR, 2023)

A Recipe for Improved Certifiable Robustness: Capacity and Data. - Kai Hu; Klas Leino; Zifan Wang 001; Matt Fredrikson (CoRR, 2023)

Is Certifying 𝓁p Robustness Still Worthwhile? - Ravi Mangal; Klas Leino; Zifan Wang 001; Kai Hu; Weicheng Yu; Corina S. Pasareanu; Anupam Datta; Matt Fredrikson (CoRR, 2023)

Can LLMs Follow Simple Rules? - Norman Mu; Sarah Li Chen; Zifan Wang 001; Sizhe Chen; David Karamardian; Lulwa Aljeraisy; Dan Hendrycks; David A. Wagner 001 (CoRR, 2023)

Transfer Attacks and Defenses for Large Language Models on Coding Tasks. - Chi Zhang; Zifan Wang 001; Ravi Mangal; Matt Fredrikson; Limin Jia 001; Corina S. Pasareanu (CoRR, 2023)

On the Feature Alignment of Deep Vision Models: Explainability and Robustness Connected At Hip - Zifan Wang 001 (2023)

A Recipe for Improved Certifiable Robustness. - Kai Hu; Klas Leino; Zifan Wang 001; Matt Fredrikson (ICLR, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Gabriel Mukobi; Nathan Helm-Burger; Rassin Lababidi; et al. (ICML, 2024)

HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal. - Mantas Mazeika; Long Phan; Xuwang Yin; Andy Zou; Zifan Wang 001; Norman Mu; Elham Sakhaee; Nathaniel Li; Steven Basart; Bo Li 026; David A. Forsyth; Dan Hendrycks (ICML, 2024)

Attacks and Defenses for Large Language Models on Coding Tasks. - Chi Zhang; Zifan Wang 001; Ruoshi Zhao; Ravi Mangal; Matt Fredrikson; Limin Jia 001; Corina S. Pasareanu (ASE, 2024)

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. - Nathaniel Li; Alexander Pan; Anjali Gopal; Summer Yue; Daniel Berrios; Alice Gatti; Justin D. Li; Ann-Kathrin Dombrowski; Shashwat Goel; Long Phan; Gabriel Mukobi; Nathan Helm-Burger; et al. (CoRR, 2024)

VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices. - Han Zhang 037; Zifan Wang 001; Mihir Dhamankar; Matt Fredrikson; Yuvraj Agarwal (CoRR, 2024)

Sales Whisperer: A Human-Inconspicuous Attack on LLM Brand Recommendations. - Weiran Lin; Anna Gerchanovsky; Omer Akgul; Lujo Bauer; Matt Fredrikson; Zifan Wang 001 (CoRR, 2024)

Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach. - Nils Palumbo; Ravi Mangal; Zifan Wang 001; Saranya Vijayakumar; Corina S. Pasareanu; Somesh Jha (CoRR, 2024)

LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet. - Nathaniel Li; Ziwen Han; Ian Steneker; Willow Primack; Riley Goodside; Hugh Zhang; Zifan Wang 001; Cristina Menghini; Summer Yue (CoRR, 2024)

Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents. - Priyanshu Kumar; Elaine Lau; Saranya Vijayakumar; Tu Trinh; Scale Red Team; Elaine T. Chang; Vaughn Robinson; Sean Hendryx; Shuyan Zhou; Matt Fredrikson; Summer Yue; Zifan Wang 001 (CoRR, 2024)

LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses. - Weiran Lin; Anna Gerchanovsky; Omer Akgul; Lujo Bauer; Matt Fredrikson; Zifan Wang 001 (CHI, 2025)

Aligned LLMs Are Not Aligned Browser Agents. - Priyanshu Kumar; Elaine Lau; Saranya Vijayakumar; Tu Trinh; Elaine T. Chang; Vaughn Robinson; Shuyan Zhou; Matt Fredrikson; Sean M. Hendryx; Summer Yue; Zifan Wang 001 (ICLR, 2025)

Jailbreaking to Jailbreak. - Jeremy Kritz; Vaughn Robinson; Robert Vacareanu; Bijan Varjavand; Michael Choi; Bobby Gogov; Scale Red Team; Summer Yue; Willow Primack; Zifan Wang 001 (CoRR, 2025)

A Red Teaming Roadmap Towards System-Level Safety. - Zifan Wang 001; Christina Q. Knight; Jeremy Kritz; Willow Primack; Julian Michael (CoRR, 2025)

WebGuard: Building a Generalizable Guardrail for Web Agents. - Boyuan Zheng; Zeyi Liao; Scott Salisbury; Zeyuan Liu; Michael Lin; Qinyuan Zheng; Zifan Wang 001; Xiang Deng 001; Dawn Song; Huan Sun 001; Yu Su 001 (CoRR, 2025)