2026
The Interplay of Harness Design and Post-Training in LLM Agents
Kyungmin Kim*, Youngbin Choi*, Seoyeon Lee, Suhyeon Jun, Dongwoo Kim^, Sangdon Park^
The 2026 Conference on Empirical Methods in Natural Language Processing, 2026
EMNLP Findings ICML'26 RLxF Workshop
SAUL: Sharpness-Aware Augmented-Lagrangian Unlearning
Jaewan Choi*, Junyoung Yang*, Sangdon Park
The 2026 Conference on Empirical Methods in Natural Language Processing, 2026
EMNLP Findings 🏆 Best Paper Award from CKAIA
Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility
Sechan Lee, Hyounghun Kim, Sangdon Park
The 2026 Conference on Empirical Methods in Natural Language Processing, 2026
EMNLP Findings
MJ: Multi-turn LLM Jailbreaking via Decomposed Credit Assignment
Junyoung Park, Namgyu Park, Sechan Lee, Yoon-Chan Jhi, Jihoon Cho, Sangdon Park
2026
The Illusion of Rust Safety: Detecting Modular Unsafe Functions with LLMs
Xiang Cheng, Fan Sang, Yibin Yang, Hang Zhang, Sangdon Park, Xiaokuan Zhang, Taesoo Kim
The ACM Conference on Computer and Communications Security, 2026
CCS
Towards Functional Correctness of Large Code Models with Selective Generation
Jaewoo Jeong, Taesoo Kim, Sangdon Park
International Conference on Machine Learning, 2026
ICML NeurIPS'25 DL4C Workshop
LLM Watermark Evasion via Bias Inversion
Jeongyeon Hwang, Sangdon Park, Jungseul Ok
International Conference on Machine Learning, 2026
ICML
Ruby: Unmasking Unsafe Rust in Stripped Binaries via Machine Learning
Xiang Cheng*, Sangdon Park*, HyungSeok Han, Xiaokuan Zhang, Taesoo Kim
International Conference on Dependable Systems and Networks, 2026
DSN
Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization
Junyoung Yang*, Kyungmin Kim*, Sangdon Park
International Conference on Learning Representations, 2026
ICLR ICLR'26 Reliable Autonomy 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, 2025
EMNLP Findings
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, 2025
EMNLP
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, 2025
ICCV
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 - $(4+2)M Award
Online Conformal Abstention for Factuality Control Under Adversarial Bandit Feedback
Minjae Lee*, Yoonjae Jung*, Sangdon Park
2025
🏆 Best Paper Finalist from CKAIA ICLR'26 Reliable Autonomy Workshop
SOUNDBOOST: Effective RCA and Attack Detection for UAV via Acoustic Side-Channel
Haoran Wang, Zheng Yang, Sangdon Park, Yibin Yang, Seulbae Kim, Willian Lunardi, Martin Andreoni, Taesoo Kim, Wenke Lee
International Conference on Dependable Systems and Networks, 2025
DSN
2024
Selective Generation for Controllable Language Models
Minjae Lee*, Kyungmin Kim*, Taesoo Kim, Sangdon Park
Neural Information Processing Systems, 2024
NeurIPS 🏆 Spotlight (Top 2.08%)🏆 POSTECH GSAI BK21 Best Paper Award
TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction
Shuo Li, Sangdon Park, Insup Lee, Osbert Bastani
North American Chapter of the Association for Computational Linguistics, 2024
NAACL 🏆 ICML'23 TEACH Workshop Best Paper Award ICML'23 TEACH Workshop
MedBN: Robust Test Time Adaptation against Malicious Test Samples
Hyejin Park*, Jeongyeon Hwang*, Sunung Mun, Sangdon Park, Jungseul Ok
Computer Vision and Pattern Recognition, 2024
CVPR
PAC Prediction Sets Under Label Shift
Wenwen Si, Sangdon Park, Insup Lee, Edgar Dobriban, Osbert Bastani
International Conference on Learning Representations, 2024
ICLR
2023
Angelic Patches for Improving Third-Party Object Detector Performance
Wenwen Si, Shuo Li, Sangdon Park, Insup Lee, Osbert Bastani
Computer Vision and Pattern Recognition, 2023
CVPR
ACon$^2$: Adaptive Conformal Consensus for Provable Blockchain Oracles
Sangdon Park, Osbert Bastani, Taesoo Kim
USENIX Security Symposium, 2023
Security
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, 2023
ICCPS 🏆 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, 2022
NeurIPS
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
Sooyong Jang, Sangdon Park, Insup Lee, Osbert Bastani
International Conference on Machine Learning, 2022
ICML
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, 2022
ICLR
2021
PAC Confidence Predictions for Deep Neural Network Classifiers
Sangdon Park, Shuo Li, Insup Lee, Osbert Bastani
International Conference on Learning Representations, 2021
ICLR
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, 2021
AAAI
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, 2020
AISTATS
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee
International Conference on Learning Representations, 2020
ICLR
2019
and
Before
Resilient linear classification: an approach to deal with attacks on training data
Sangdon Park, James Weimer, Insup Lee
International Conference on Cyber-Physical Systems, 2017
ICCPS
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, 2016
ISER
Abnormal object detection by canonical scene-based contextual model
Sangdon Park, Wonsik Kim, Kyoung Mu Lee
European Conference on Computer Vision, 2012
ECCV 🏆 Distinguished MS Dissertation Award