A Lab-Based Investigation of Reaction Time and Reading Performance using Different In-Vehicle Reading Interfaces during Self-Driving. - Lei Hsiung; Yung-Ju Chang; Wei-Ko Li; Tsung-Yi Ho; Shan-Hung Wu (UI, 2022)

CARBEN: Composite Adversarial Robustness Benchmark. - Lei Hsiung; Yun-Yun Tsai; Pin-Yu Chen; Tsung-Yi Ho (IJCAI, 2022)

NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration. - Lei Hsiung; Yung-Chen Tang; Pin-Yu Chen; Tsung-Yi Ho (AAAI, 2023)

Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations. - Lei Hsiung; Yun-Yun Tsai; Pin-Yu Chen; Tsung-Yi Ho (CVPR, 2023)

NeuralFuse: Learning to Improve the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes. - Hao-Lun Sun; Lei Hsiung; Nandhini Chandramoorthy; Pin-Yu Chen; Tsung-Yi Ho (CoRR, 2023)

AutoVP: An Automated Visual Prompting Framework and Benchmark. - Hsi-Ai Tsao; Lei Hsiung; Pin-Yu Chen; Sijia Liu 001; Tsung-Yi Ho (CoRR, 2023)

AutoVP: An Automated Visual Prompting Framework and Benchmark. - Hsi-Ai Tsao; Lei Hsiung; Pin-Yu Chen; Si Liu 001; Tsung-Yi Ho (ICLR, 2024)

NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes. - Hao-Lun Sun; Lei Hsiung; Nandhini Chandramoorthy; Pin-Yu Chen; Tsung-Yi Ho (NeurIPS, 2024)

Spectral Insights into Data-Oblivious Critical Layers in Large Language Models. - Xuyuan Liu; Lei Hsiung; Yaoqing Yang; Yujun Yan (ACL (Findings), 2025)

When Does Visual Prompting Outperform Linear Probing for Vision-Language Models? A Likelihood Perspective. - Hsi-Ai Tsao; Lei Hsiung; Pin-Yu Chen; Tsung-Yi Ho (ICASSP, 2025)

Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets. - Lei Hsiung; Tianyu Pang; Yung-Chen Tang; Linyue Song; Tsung-Yi Ho; Pin-Yu Chen; Yaoqing Yang (CoRR, 2025)