Abnormal Object Detection by Canonical Scene-Based Contextual Model. - Sangdon Park 001; Wonsik Kim; Kyoung Mu Lee (ECCV (3), 2012)

Integrated Intelligence for Human-Robot Teams. - Jean Oh; Thomas M. Howard; Matthew R. Walter; Daniel Barber; Menglong Zhu; Sangdon Park 001; Arne Suppé; Luis E. Navarro-Serment; Felix Duvallet; Abdeslam Boularias; Oscar J. Romero; Jerry Vinokurov; et al. (ISER, 2016)

Resilient linear classification: an approach to deal with attacks on training data. - Sangdon Park 001; James Weimer; Insup Lee 001 (ICCPS, 2017)

Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation. - Sangdon Park 001; Osbert Bastani; James Weimer; Insup Lee 001 (AISTATS, 2020)

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction. - Sangdon Park 001; Osbert Bastani; Nikolai Matni; Insup Lee 001 (ICLR, 2020)

VisionGuard: Runtime Detection of Adversarial Inputs to Perception Systems. - Yiannis Kantaros; Taylor J. Carpenter; Sangdon Park 001; Radoslav Ivanov; Sooyong Jang; Insup Lee 001; James Weimer (CoRR, 2020)

PAC Confidence Predictions for Deep Neural Network Classifiers. - Sangdon Park 001; Shuo Li; Insup Lee 001; Osbert Bastani (ICLR, 2021)

Detecting OODs as datapoints with High Uncertainty. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Oleg Sokolsky; Insup Lee 001 (CoRR, 2021)

iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Edgar Dobriban; Oleg Sokolsky; Insup Lee 001 (AAAI, 2022)

PAC Prediction Sets Under Covariate Shift. - Sangdon Park 001; Edgar Dobriban; Insup Lee 001; Osbert Bastani (ICLR, 2022)

Sequential Covariate Shift Detection Using Classifier Two-Sample Tests. - Sooyong Jang; Sangdon Park 001; Insup Lee 001; Osbert Bastani (ICML, 2022)

PAC Prediction Sets for Meta-Learning. - Sangdon Park 001; Edgar Dobriban; Insup Lee 001; Osbert Bastani (NeurIPS, 2022)

Towards PAC Multi-Object Detection and Tracking. - Shuo Li; Sangdon Park 001; Xiayan Ji; Insup Lee 001; Osbert Bastani (CoRR, 2022)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (CoRR, 2022)

Unsafe's Betrayal: Abusing Unsafe Rust in Binary Reverse Engineering toward Finding Memory-safety Bugs via Machine Learning. - Sangdon Park 001; Xiang Cheng; Taesoo Kim (CoRR, 2022)

Angelic Patches for Improving Third-Party Object Detector Performance. - Wenwen Si; Shuo Li; Sangdon Park 001; Insup Lee 001; Osbert Bastani (CVPR, 2023)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Yahan Yang; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2023)

ACon2: Adaptive Conformal Consensus for Provable Blockchain Oracles. - Sangdon Park 001; Osbert Bastani; Taesoo Kim (USENIX Security Symposium, 2023)

TRAC: Trustworthy Retrieval Augmented Chatbot. - Shuo Li; Sangdon Park 001; Insup Lee 001; Osbert Bastani (CoRR, 2023)

PAC Neural Prediction Set Learning to Quantify the Uncertainty of Generative Language Models. - Sangdon Park 001; Taesoo Kim (CoRR, 2023)

PAC Prediction Sets Under Label Shift. - Wenwen Si; Sangdon Park 001; Insup Lee 001; Edgar Dobriban; Osbert Bastani (ICLR, 2024)

TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction. - Shuo Li; Sangdon Park 001; Insup Lee 001; Osbert Bastani (NAACL-HLT, 2024)

Selective Generation for Controllable Language Models. - Minjae Lee 008; Kyungmin Kim; Taesoo Kim; Sangdon Park 001 (NeurIPS, 2024)

Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction. - Ramya Ramalingam; Sangdon Park 001; Osbert Bastani (CoRR, 2024)