An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes. - Hung-Yi Lo; Kai-Wei Chang; Shang-Tse Chen; Tsung-Hsien Chiang; Chun-Sung Ferng; Cho-Jui Hsieh; Yi-Kuang Ko; Tsung-Ting Kuo; Hung-Che Lai; Ken-Yi Lin; Chia-Hsuan Wang; Hsiang-Fu Yu; et al. (KDD Cup, 2009)

An Online Boosting Algorithm with Theoretical Justifications. - Shang-Tse Chen; Hsuan-Tien Lin; Chi-Jen Lu (ICML, 2012)

Boosting with Online Binary Learners for the Multiclass Bandit Problem. - Shang-Tse Chen; Hsuan-Tien Lin; Chi-Jen Lu (ICML, 2014)

TimeStitch: Interactive multi-focus cohort discovery and comparison. - Peter J. Polack Jr.; Shang-Tse Chen; Minsuk Kahng; Moushumi Sharmin; Duen Horng Chau (VAST, 2015)

Benchmarking renderscript: potential for energy efficient multi-core mobile devices. - Qianao Ju; Shang-Tse Chen; Ying Zhang 007 (SECON Workshops, 2015)

Spotting Suspicious Reviews via (Quasi-)clique Extraction. - Paras Jain 003; Shang-Tse Chen; Mozhgan Azimpourkivi; Duen Horng Chau; Bogdan Carbunar (CoRR, 2015)

Communication Efficient Distributed Agnostic Boosting. - Shang-Tse Chen; Maria-Florina Balcan; Duen Horng Chau (AISTATS, 2016)

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta. - Michael A. Madaio; Shang-Tse Chen; Oliver L. Haimson; Wenwen Zhang; Xiang Cheng 002; Matthew Hinds-Aldrich; Duen Horng Chau; Bistra Dilkina (KDD, 2016)

Chronodes: Interactive Multi-focus Exploration of Event Sequences. - Peter J. Polack Jr.; Shang-Tse Chen; Minsuk Kahng; Kaya de Barbaro; Moushumi Sharmin; Rahul C. Basole; Duen Horng Chau (CoRR, 2016)

Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities. - Peter J. Polack Jr.; Moushumi Sharmin; Kaya de Barbaro; Minsuk Kahng; Shang-Tse Chen; Duen Horng Chau (Mobile Health - Sensors, Analytic Methods, and Applications, 2017)

Predicting Cyber Threats with Virtual Security Products. - Shang-Tse Chen; Yufei Han 001; Duen Horng Chau; Christopher S. Gates; Michael Hart; Kevin A. Roundy (ACSAC, 2017)

Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression. - Nilaksh Das; Madhuri Shanbhogue; Shang-Tse Chen; Fred Hohman; Li Chen; Michael E. Kounavis; Duen Horng Chau (CoRR, 2017)

Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems. - Maria-Florina Balcan; Avrim Blum; Shang-Tse Chen (AAMAS, 2018)

SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression. - Nilaksh Das; Madhuri Shanbhogue; Shang-Tse Chen; Fred Hohman; Siwei Li; Li Chen; Michael E. Kounavis; Duen Horng Chau (KDD, 2018)

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector. - Shang-Tse Chen; Cory Cornelius; Jason Martin; Duen Horng (Polo) Chau (ECML/PKDD (1), 2018)

ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio. - Nilaksh Das; Madhuri Shanbhogue; Shang-Tse Chen; Li Chen; Michael E. Kounavis; Duen Horng Chau (ECML/PKDD (3), 2018)

Robust Physical Adversarial Attack on Faster R-CNN Object Detector. - Shang-Tse Chen; Cory Cornelius; Jason Martin; Duen Horng Chau (CoRR, 2018)

Chronodes: Interactive Multifocus Exploration of Event Sequences. - Peter J. Polack Jr.; Shang-Tse Chen; Minsuk Kahng; Kaya de Barbaro; Rahul C. Basole; Moushumi Sharmin; Duen Horng Chau (ACM Trans. Interact. Intell. Syst., 2018)

Talk Proposal: Towards the Realistic Evaluation of Evasion Attacks using CARLA. - Cory Cornelius; Shang-Tse Chen; Jason Martin; Duen Horng Chau (CoRR, 2019)

UnMask: Adversarial Detection and Defense Through Robust Feature Alignment. - Scott Freitas; Shang-Tse Chen; Zijie J. Wang; Duen Horng Chau (IEEE BigData, 2020)

AI-infused Security: Robust Defense by Bridging Theory and Practice. - Shang-Tse Chen (2020)

Few-shot Prompting Towards Controllable Response Generation. - Hsuan Su; Po-Han Chi; Shih-Cheng Huang; Ho-Lam Chung; Saurav Sahay; Shang-Tse Chen; Hung-Yi Lee (CoRR, 2022)

Fair Robust Active Learning by Joint Inconsistency. - Tsung-Han Wu; Shang-Tse Chen; Winston H. Hsu (CoRR, 2022)

Fair Robust Active Learning by Joint Inconsistency. - Tsung-Han Wu; Hung-Ting Su; Shang-Tse Chen; Winston H. Hsu (ICCV (Workshops), 2023)

QCRS: Improve Randomized Smoothing using Quasi-Concave Optimization. - Bo-Han Kung; Shang-Tse Chen (CoRR, 2023)

Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue. - Hsuan Su; Shachi H. Kumar; Sahisnu Mazumder; Wenda Chen; Ramesh Manuvinakurike; Eda Okur; Saurav Sahay; Lama Nachman; Shang-Tse Chen; Hung-yi Lee (CoRR, 2023)

Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models. - Hsuan Su; Cheng-Chu Cheng; Hua Farn; Shachi H. Kumar; Saurav Sahay; Shang-Tse Chen; Hung-yi Lee (CoRR, 2023)

Step by Step to Fairness: Attributing Societal Bias in Task-oriented Dialogue Systems. - Hsuan Su; Rebecca Qian; Chinnadhurai Sankar; Shahin Shayandeh; Shang-Tse Chen; Hung-yi Lee; Daniel M. Bikel (CoRR, 2023)

Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization. - Bo-Han Kung; Shang-Tse Chen (AAAI, 2024)

Enhancing Targeted Attack Transferability via Diversified Weight Pruning. - Hung-Jui Wang; Yu-Yu Wu; Shang-Tse Chen (CVPR Workshops, 2024)

Task Arithmetic can Mitigate Synthetic-to-Real Gap in Automatic Speech Recognition. - Hsuan Su; Hua Farn; Fan-Yun Sun; Shang-Tse Chen; Hung-yi Lee (EMNLP, 2024)

Annealing Self-Distillation Rectification Improves Adversarial Training. - Yu-Yu Wu; Hung-Jui Wang; Shang-Tse Chen (ICLR, 2024)

Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation. - Tsung-Han Wu; Hung-Ting Su; Shang-Tse Chen; Winston H. Hsu (CoRR, 2024)

Adversarial Robustness Overestimation and Instability in TRADES. - Jonathan Weiping Li; Ren-Wei Liang; Cheng-Han Yeh; Cheng-Chang Tsai; Kuanchun Yu; Chun-Shien Lu; Shang-Tse Chen (CoRR, 2024)

Trap-MID: Trapdoor-based Defense against Model Inversion Attacks. - Zhen-Ting Liu; Shang-Tse Chen (CoRR, 2024)

Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging. - Hua Farn; Hsuan Su; Shachi H. Kumar; Saurav Sahay; Shang-Tse Chen; Hung-yi Lee (CoRR, 2024)

Ensuring Bidirectional Privacy on Wireless Split Inference Systems. - Chia-Che Sa; Li-Chen Cheng; Hsing-Huan Chung; Te-Chuan Chiu; Chih-Yu Wang 001; Ai-Chun Pang; Shang-Tse Chen (IEEE Wirel. Commun., 2024)

Jailbreaking with Universal Multi-Prompts. - Yu-Ling Hsu; Hsuan Su; Shang-Tse Chen (NAACL (Findings), 2025)

Adaptive Helpfulness-Harmlessness Alignment with Preference Vectors. - Ren-Wei Liang; Chin-Ting Hsu; Chan-Hung Yu; Saransh Agrawal; Shih-Cheng Huang; Shang-Tse Chen; Kuan-Hao Huang; Shao-Hua Sun (CoRR, 2025)

Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss. - Bo-Han Lai; Pin-Han Huang; Bo-Han Kung; Shang-Tse Chen (CoRR, 2025)

DRAG: Data Reconstruction Attack using Guided Diffusion. - Wa-Kin Lei; Jun-Cheng Chen; Shang-Tse Chen (CoRR, 2025)

Pseudo2Real: Task Arithmetic for Pseudo-Label Correction in Automatic Speech Recognition. - Yi-Cheng Lin; Yu-Hsuan Li Liang; Hsuan Su; Tzu-Quan Lin; Shang-Tse Chen; Yun-Nung Chen; Hung-yi Lee (CoRR, 2025)