• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 106 matches

• 2024
• 
  Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson:
  A Recipe for Improved Certifiable Robustness. ICLR 2024
• 
  Kai Hu, Weichen Yu, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Yining Li, Kai Chen, Zhiqiang Shen, Matt Fredrikson:
  Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization. CoRR abs/2405.09113 (2024)
• 
  Han Zhang, Zifan Wang, Mihir Dhamankar, Matt Fredrikson, Yuvraj Agarwal:
  VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices. CoRR abs/2406.00586 (2024)
• 
  Andy Zou, Long Phan, Justin Wang, Derek Duenas, Maxwell Lin, Maksym Andriushchenko, Rowan Wang, Zico Kolter, Matt Fredrikson, Dan Hendrycks:
  Improving Alignment and Robustness with Circuit Breakers. CoRR abs/2406.04313 (2024)
• 
  Weiran Lin, Anna Gerchanovsky, Omer Akgul, Lujo Bauer, Matt Fredrikson, Zifan Wang:
  Sales Whisperer: A Human-Inconspicuous Attack on LLM Brand Recommendations. CoRR abs/2406.04755 (2024)
• 2023
• 
  Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson:
  On the Perils of Cascading Robust Classifiers. ICLR 2023
• 
  Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson:
  Unlocking Deterministic Robustness Certification on ImageNet. NeurIPS 2023
• 
  Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson:
  Grounding Neural Inference with Satisfiability Modulo Theories. NeurIPS 2023
• 
  Matt Fredrikson, Kaiji Lu, Saranya Vijayakumar, Somesh Jha, Vijay Ganesh, Zifan Wang:
  Learning Modulo Theories. CoRR abs/2301.11435 (2023)
• 
  Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson:
  Scaling in Depth: Unlocking Robustness Certification on ImageNet. CoRR abs/2301.12549 (2023)
• 
  Andy Zou, Zifan Wang, J. Zico Kolter, Matt Fredrikson:
  Universal and Transferable Adversarial Attacks on Aligned Language Models. CoRR abs/2307.15043 (2023)
• 
  Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J. Zico Kolter, Dan Hendrycks:
  Representation Engineering: A Top-Down Approach to AI Transparency. CoRR abs/2310.01405 (2023)
• 
  Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson:
  A Recipe for Improved Certifiable Robustness: Capacity and Data. CoRR abs/2310.02513 (2023)
• 
  Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson:
  Is Certifying 𝓁_p Robustness Still Worthwhile? CoRR abs/2310.09361 (2023)
• 
  Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu:
  Transfer Attacks and Defenses for Large Language Models on Coding Tasks. CoRR abs/2311.13445 (2023)
• 2022
• 
  Helena Montenegro, Wilson Silva, Alex Gaudio, Matt Fredrikson, Asim Smailagic, Jaime S. Cardoso:
  Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy. IEEE Access 10: 28333-28347 (2022)
• 
  Daniel Gibert, Matt Fredrikson, Carles Mateu, Jordi Planes, Quan Le:
  Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Comput. Secur. 113: 102543 (2022)
• 
  Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
  Degradation Attacks on Certifiably Robust Neural Networks. Trans. Mach. Learn. Res. 2022 (2022)
• 
  Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
  Self-correcting Neural Networks for Safe Classification. NSV/FoMLAS@CAV 2022: 96-130
• 
  Emily Black, Klas Leino, Matt Fredrikson:
  Selective Ensembles for Consistent Predictions. ICLR 2022
• 
  Emily Black, Zifan Wang, Matt Fredrikson:
  Consistent Counterfactuals for Deep Models. ICLR 2022
• 
  Zifan Wang, Matt Fredrikson, Anupam Datta:
  Robust Models Are More Interpretable Because Attributions Look Normal. ICML 2022: 22625-22651
• 
  Han Zhang, Yuvraj Agarwal, Matt Fredrikson:
  TEO: ephemeral ownership for IoT devices to provide granular data control. MobiSys 2022: 302-315
• 
  Han Zhang, Yuvraj Agarwal, Matt Fredrikson:
  Protecting user data through ephemeral ownership of IoT devices. MobiSys 2022: 620-621
• 
  Zifan Wang, Yuhang Yao, Chaoran Zhang, Han Zhang, Youjie Kang, Carlee Joe-Wong, Matt Fredrikson, Anupam Datta:
  Faithful Explanations for Deep Graph Models. CoRR abs/2205.11850 (2022)
• 
  Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson:
  On the Perils of Cascading Robust Classifiers. CoRR abs/2206.00278 (2022)
• 
  Marc Juarez, Samuel Yeom, Matt Fredrikson:
  Black-Box Audits for Group Distribution Shifts. CoRR abs/2209.03620 (2022)
• 2021
• 
  Abhishek Bichhawat, Matt Fredrikson, Jean Yang:
  Automating Audit with Policy Inference. CSF 2021: 1-16
• 
  Emily Black, Matt Fredrikson:
  Leave-one-out Unfairness. FAccT 2021: 285-295
• 
  Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
  Fast Geometric Projections for Local Robustness Certification. ICLR 2021

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