🚀 2026

Online Conformal Prediction with Adversarial Feedback via Regret Minimization
Junyoung Yang*, Kyungmin Kim*, Sangdon Park
The Fourteenth International Conference on Learning Representations (ICLR), 2026

🚀 2025

Ensuring Functional Correctness of Large Code Models with Selective Generation
Jaewoo Jeong, Taesoo Kim, Sangdon Park
Neural Information Processing Systems (NeurIPS DL4C Workshop), 2025
ChronoBias: A Benchmark for Evaluating Time-conditional Group Bias in the Time-sensitive Knowledge of Large Language Models
Kyungmin Kim, Youngbin Choi, Hyounghun Kim, Dongwoo Kim, Sangdon Park
Findings of the Association for Computational Linguistics: EMNLP (EMNLP Findings), 2025
Retrieval-Augmented Generation with Estimation of Source Reliability
Jeongyeon Hwang, Junyoung Park, Hyejin Park, Dongwoo Kim, Sangdon Park, Jungseul Ok
Empirical Methods in Natural Language Processing (EMNLP), 2025
Holistic Unlearning Benchmark: A Multi-Faceted Evaluation for Text-to-Image Diffusion Model Unlearning
Saemi Moon*, Minjong Lee*, Sangdon Park, Dongwoo Kim
International Conference on Computer Vision (ICCV), 2025
AI Kill Switch for Malicious Web-based LLM Agent
Sechan Lee, Sangdon Park
2025
ATLANTIS: AI-driven Threat Localization, Analysis, and Triage Intelligence System
Taesoo Kim, HyungSeok Han, Soyeon Park, Dae R. Jeong, Dohyeok Kim, Dongkwan Kim, Eunsoo Kim, Jiho Kim, Joshua Wang, Kangsu Kim, Sangwoo Ji, Woosun Song, Hanqing Zhao, Andrew Chin, Gyejin Lee, Kevin Stevens, Mansour Alharthi, Yizhuo Zhai, Cen Zhang, Joonun Jang, Yeongjin Jang, Ammar Askar, Dongju Kim, Fabian Fleischer, Jeongin Cho, Junsik Kim, Kyungjoon Ko, Insu Yun, Sangdon Park, Dowoo Baik, Haein Lee, Hyeon Heo, Minjae Gwon, Minjae Lee, Minwoo Baek, Seunggi Min, Wonyoung Kim, Yonghwi Jin, Younggi Park, Yunjae Choi, Jinho Jung, Gwanhyun Lee, Junyoung Jang, Kyuheon Kim, Yeonghyeon Cha, Youngjoon Kim
2025
🏆 DARPA AIxCC Winner – $4M Award
Online Selective Generation with Adversarial Bandit Feedback
Minjae Lee*, Yoonjae Jung*, Sangdon Park
2025
🏆 Best Paper Finalist from CKAIA
SOUNDBOOST: Effective RCA and Attack Detection for UAV via Acoustic Side-Channel
Haoran Wang, Zheng Yang, Sangdon Park, Yibin Yang, Seulbae Kim, Willian Lunardi, Martin Andreoni, Taesoo Kim, Wenke Lee
International Conference on Dependable Systems and Networks (DSN), 2025

🚀 2024

Selective Generation for Controllable Language Models
Minjae Lee*, Kyungmin Kim*, Taesoo Kim, Sangdon Park
Neural Information Processing Systems (NeurIPS), 2024
🏆 Spotlight – Top 2.08%, 🏆 POSTECH GSAI BK21 Best Paper Award
TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction
Shuo Li, Sangdon Park, Insup Lee, Osbert Bastani
North American Chapter of the Association for Computational Linguistics (NAACL), 2024
🏆 ICML’23 TEACH Workshop Best Paper Award
MedBN: Robust Test Time Adaptation against Malicious Test Samples
Hyejin Park*, Jeongyeon Hwang*, Sunung Mun, Sangdon Park, Jungseul Ok
Computer Vision and Pattern Recognition (CVPR), 2024
PAC Prediction Sets Under Label Shift
Wenwen Si, Sangdon Park, Insup Lee, Edgar Dobriban, Osbert Bastani
International Conference on Learning Representations (ICLR), 2024

🚀 2023

Angelic Patches for Improving Third-Party Object Detector Performance
Wenwen Si, Shuo Li, Sangdon Park, Insup Lee, Osbert Bastani
Computer Vision and Pattern Recognition (CVPR), 2023
ACon$^2$: Adaptive Conformal Consensus for Provable Blockchain Oracles
Sangdon Park, Osbert Bastani, Taesoo Kim
USENIX Security Symposium (Security), 2023
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems
Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Yahan Yang, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee
International Conference on Cyber-Physical Systems (ICCPS), 2023
🏆 ICCPS’23 Best Paper Award Finalist

🚀 2022

PAC Prediction Sets for Meta-Learning
Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani
Neural Information Processing Systems (NeurIPS), 2022
Unsafe's Betrayal: Abusing Unsafe Rust in Binary Reverse Engineering via Machine Learning
Sangdon Park, Xiang Cheng, Taesoo Kim
2022
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
Sooyong Jang, Sangdon Park, Insup Lee, Osbert Bastani
International Conference on Machine Learning (ICML), 2022
Towards PAC Multi-Object Detection and Tracking
Shuo Li, Sangdon Park, Xiayan Ji, Insup Lee, Osbert Bastani
2022
PAC Prediction Sets Under Covariate Shift
Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani
International Conference on Learning Representations (ICLR), 2022

🚀 2021

PAC Confidence Predictions for Deep Neural Network Classifiers
Sangdon Park, Shuo Li, Insup Lee, Osbert Bastani
International Conference on Learning Representations (ICLR), 2021
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
Ramneet Kaur, Susmit Jha, Anirban Roy, Sangdon Park, Edgar Dobriban, Oleg Sokolsky, Insup Lee
Association for the Advancement of Artificial Intelligence (AAAI), 2021

🚀 2020

Calibrated prediction with covariate shift via unsupervised domain adaptation
Sangdon Park, Osbert Bastani, James Weimer, Insup Lee
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee
International Conference on Learning Representations (ICLR), 2020

🚀 Before 2020

Resilient linear classification: an approach to deal with attacks on training data
Sangdon Park, James Weimer, Insup Lee
International Conference on Cyber-Physical Systems (ICCPS), 2017
Integrated intelligence for human-robot teams
Jean Oh, Thomas M Howard, Matthew R Walter, Daniel Barber, Menglong Zhu, Sangdon Park, Arne Suppe, Luis Navarro-Serment, Felix Duvallet, Abdeslam Boularias, Others
International Symposium on Experimental Robotics (ISER), 2016
Abnormal object detection by canonical scene-based contextual model
Sangdon Park, Wonsik Kim, Kyoung Mu Lee
European Conference on Computer Vision (ECCV), 2012