Hong, Sanghyun

21 publications

TMLR 2026 Hessian-Aware Training for Enhancing DNN Resilience to Bitwise Corruptions in Their Parameters Tahmid Hasan Pranto, Seijoon Kim, Lizhong Chen, Sanghyun Hong

TMLR 2025 Hard Work Does Not Always Pay Off: On the Robustness of NAS to Data Poisoning Zachary Coalson, Huazheng Wang, Qingyun Wu, Sanghyun Hong

ICCV 2025 Harnessing Input-Adaptive Inference for Efficient VLN Dongwoo Kang, Akhil Perincherry, Zachary Coalson, Aiden Gabriel, Stefan Lee, Sanghyun Hong

NeurIPS 2025 IF-Guide: Influence Function-Guided Detoxification of LLMs Zachary Coalson, Juhan Bae, Nicholas Carlini, Sanghyun Hong

ICLRW 2024 Extension of Physics-Informed Neural Networks to Solving Parameterized PDEs Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

ICML 2024 LeaPformer: Enabling Linear Transformers for Autoregressive and Simultaneous Tasks via Learned Proportions Victor Agostinelli Iii, Sanghyun Hong, Lizhong Chen

AAAI 2024 Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations Woojin Cho, Seunghyeon Cho, Hyundong Jin, Jinsung Jeon, Kookjin Lee, Sanghyun Hong, Dongeun Lee, Jonghyun Choi, Noseong Park

ICLR 2024 PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee, Kookjin Lee, Noseong Park

ICML 2024 Parameterized Physics-Informed Neural Networks for Parameterized PDEs Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

NeurIPS 2024 Privacy Backdoors: Enhancing Membership Inference Through Poisoning Pre-Trained Models Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini

NeurIPSW 2024 You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Models Eric Slyman, Anirudh Kanneganti, Sanghyun Hong, Stefan Lee

NeurIPS 2023 BERT Lost Patience Won't Be Robust to Adversarial Slowdown Zachary Coalson, Gabriel Ritter, Rakesh Bobba, Sanghyun Hong

NeurIPSW 2023 HyperNetwork Approximating Future Parameters for Time Series Forecasting Under Temporal Drifts Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

ICML 2023 Learning Unforeseen Robustness from Out-of-Distribution Data Using Equivariant Domain Translator Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong

ICLRW 2023 Learning Unforeseen Robustness from Out-of-Distribution Data Using Equivariant Domain Translator Sicheng Zhu, Bang An, Furong Huang, Sanghyun Hong

ICLR 2022 Data Poisoning Won’t Save You from Facial Recognition Evani Radiya-Dixit, Sanghyun Hong, Nicholas Carlini, Florian Tramer

NeurIPS 2022 Handcrafted Backdoors in Deep Neural Networks Sanghyun Hong, Nicholas Carlini, Alexey Kurakin

ICLR 2021 A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference Sanghyun Hong, Yigitcan Kaya, Ionuț-Vlad Modoranu, Tudor Dumitras

NeurIPS 2021 Qu-ANTI-Zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Tudor Dumitras

ICLR 2020 How to 0wn the NAS in Your Spare Time Sanghyun Hong, Michael Davinroy, Yiǧitcan Kaya, Dana Dachman-Soled, Tudor Dumitraş

ICML 2019 Shallow-Deep Networks: Understanding and Mitigating Network Overthinking Yigitcan Kaya, Sanghyun Hong, Tudor Dumitras