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Chawin Sitawarin
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2020 – today
- 2024
- [c15]Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, David A. Wagner:
Jatmo: Prompt Injection Defense by Task-Specific Finetuning. ESORICS (1) 2024: 105-124 - [c14]Kathan Shah, Chawin Sitawarin:
SPDER: Semiperiodic Damping-Enabled Object Representation. ICLR 2024 - [c13]Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David A. Wagner:
PubDef: Defending Against Transfer Attacks From Public Models. ICLR 2024 - [c12]Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling:
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. ICML 2024 - [i20]Sizhe Chen, Julien Piet, Chawin Sitawarin, David A. Wagner:
StruQ: Defending Against Prompt Injection with Structured Queries. CoRR abs/2402.06363 (2024) - [i19]Chawin Sitawarin, Norman Mu, David A. Wagner, Alexandre Araujo:
PAL: Proxy-Guided Black-Box Attack on Large Language Models. CoRR abs/2402.09674 (2024) - [i18]Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David A. Wagner, Baishakhi Ray, Yizheng Chen:
Vulnerability Detection with Code Language Models: How Far Are We? CoRR abs/2403.18624 (2024) - 2023
- [c11]Nabeel Hingun, Chawin Sitawarin, Jerry Li, David A. Wagner:
REAP: A Large-Scale Realistic Adversarial Patch Benchmark. ICCV 2023: 4617-4628 - [c10]Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David A. Wagner:
Part-Based Models Improve Adversarial Robustness. ICLR 2023 - [c9]Chawin Sitawarin, Florian Tramèr, Nicholas Carlini:
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems. ICML 2023: 32008-32032 - [i17]Kathan Shah, Chawin Sitawarin:
SPDER: Semiperiodic Damping-Enabled Object Representation. CoRR abs/2306.15242 (2023) - [i16]Lin Li, Yifei Wang, Chawin Sitawarin
, Michael W. Spratling
:
OODRobustBench: benchmarking and analyzing adversarial robustness under distribution shift. CoRR abs/2310.12793 (2023) - [i15]Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David A. Wagner:
Defending Against Transfer Attacks From Public Models. CoRR abs/2310.17645 (2023) - [i14]Julien Piet, Chawin Sitawarin, Vivian Fang, Norman Mu, David A. Wagner:
Mark My Words: Analyzing and Evaluating Language Model Watermarks. CoRR abs/2312.00273 (2023) - [i13]Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, David A. Wagner:
Jatmo: Prompt Injection Defense by Task-Specific Finetuning. CoRR abs/2312.17673 (2023) - 2022
- [c8]Chawin Sitawarin, Zachary J. Golan-Strieb, David A. Wagner:
Demystifying the Adversarial Robustness of Random Transformation Defenses. ICML 2022: 20232-20252 - [i12]Chawin Sitawarin
, Zachary J. Golan-Strieb, David A. Wagner:
Demystifying the Adversarial Robustness of Random Transformation Defenses. CoRR abs/2207.03574 (2022) - [i11]Chawin Sitawarin
, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David A. Wagner:
Part-Based Models Improve Adversarial Robustness. CoRR abs/2209.09117 (2022) - [i10]Chawin Sitawarin, Florian Tramèr, Nicholas Carlini:
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems. CoRR abs/2210.03297 (2022) - [i9]Nabeel Hingun, Chawin Sitawarin
, Jerry Li, David A. Wagner:
REAP: A Large-Scale Realistic Adversarial Patch Benchmark. CoRR abs/2212.05680 (2022) - 2021
- [c7]Chawin Sitawarin
, Supriyo Chakraborty, David A. Wagner:
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing. AISec@CCS 2021: 25-36 - [c6]Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song, David A. Wagner:
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams. NeurIPS 2021: 15486-15497 - 2020
- [c5]Chawin Sitawarin
, David A. Wagner:
Minimum-Norm Adversarial Examples on KNN and KNN based Models. SP (Workshops) 2020: 34-40 - [i8]Chawin Sitawarin, David A. Wagner:
Minimum-Norm Adversarial Examples on KNN and KNN-Based Models. CoRR abs/2003.06559 (2020) - [i7]Chawin Sitawarin, Supriyo Chakraborty, David A. Wagner:
Improving Adversarial Robustness Through Progressive Hardening. CoRR abs/2003.09347 (2020) - [i6]Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song, David A. Wagner:
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams. CoRR abs/2011.09719 (2020) - no results
2010 – 2019
- 2019
- [c4]Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina
, Mung Chiang, Prateek Mittal:
Analyzing the Robustness of Open-World Machine Learning. AISec@CCS 2019: 105-116 - [c3]Chawin Sitawarin
, David A. Wagner:
On the Robustness of Deep K-Nearest Neighbors. IEEE Symposium on Security and Privacy Workshops 2019: 1-7 - [i5]Chawin Sitawarin, David A. Wagner:
On the Robustness of Deep K-Nearest Neighbors. CoRR abs/1903.08333 (2019) - [i4]Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal:
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples. CoRR abs/1905.01726 (2019) - 2018
- [c2]Vikash Sehwag, Chawin Sitawarin
, Arjun Nitin Bhagoji
, Arsalan Mosenia, Mung Chiang, Prateek Mittal:
Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. CCS 2018: 2285-2287 - [c1]Arjun Nitin Bhagoji
, Daniel Cullina
, Chawin Sitawarin
, Prateek Mittal:
Enhancing robustness of machine learning systems via data transformations. CISS 2018: 1-5 - [i3]Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Prateek Mittal, Mung Chiang:
Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos. CoRR abs/1801.02780 (2018) - [i2]Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal:
DARTS: Deceiving Autonomous Cars with Toxic Signs. CoRR abs/1802.06430 (2018) - 2017
- [i1]Mark Martinez, Chawin Sitawarin, Kevin Finch, Lennart Meincke, Alex Yablonski, Alain L. Kornhauser:
Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Cars. CoRR abs/1712.01397 (2017) - no results

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