Chawin Sitawarin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
16
Venues
9
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
16 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICSE | Vulnerability Detection with Code Language Models: How Far are We? | Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David A. Wagner, Baishakhi Ray, Yizheng Chen |
| 2025 | NAACL | Stronger Universal and Transferable Attacks by Suppressing Refusals. | David Huang, Avidan Shah, Alexandre Araujo, David A. Wagner, Chawin Sitawarin |
| 2024 | ESORICS | Jatmo: Prompt Injection Defense by Task-Specific Finetuning. | Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, David A. Wagner |
| 2024 | ICLR | SPDER: Semiperiodic Damping-Enabled Object Representation. | Kathan Shah, Chawin Sitawarin |
| 2024 | ICLR | PubDef: Defending Against Transfer Attacks From Public Models. | Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David A. Wagner |
| 2024 | ICML | OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. | Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling |
| 2023 | ICCV | REAP: A Large-Scale Realistic Adversarial Patch Benchmark. | Nabeel Hingun, Chawin Sitawarin, Jerry Li, David A. Wagner |
| 2023 | ICLR | Part-Based Models Improve Adversarial Robustness. | Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David A. Wagner |
| 2023 | ICML | Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems. | Chawin Sitawarin, Florian Tramr, Nicholas Carlini |
| 2022 | ICML | Demystifying the Adversarial Robustness of Random Transformation Defenses. | Chawin Sitawarin, Zachary J. Golan-Strieb, David A. Wagner |
| 2021 | CCS | SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing. | Chawin Sitawarin, Supriyo Chakraborty, David A. Wagner |
| 2020 | SP | Minimum-Norm Adversarial Examples on KNN and KNN based Models. | Chawin Sitawarin, David A. Wagner |
| 2019 | CCS | Analyzing the Robustness of Open-World Machine Learning. | Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal |
| 2019 | SP | On the Robustness of Deep K-Nearest Neighbors. | Chawin Sitawarin, David A. Wagner |
| 2018 | CCS | Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. | Vikash Sehwag, Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal |
| 2018 | CISS | Enhancing robustness of machine learning systems via data transformations. | Arjun Nitin Bhagoji, Daniel Cullina, Chawin Sitawarin, Prateek Mittal |