Publication

You can also find my papers listed in Google Scholar.

Conference

• Suyeon Kim, SeongKu Kang, Dongwoo Kim, Jungseul Ok, and Hwanjo Yu, "Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark", KDD 2025 Datasets and Benchmarks Track

• Minhyeon Oh, Seungjoon Lee, and Jungseul Ok, "Comparison-based Active Preference Learning for Multi-dimensional Personalization", ACL 2025 (main, long)

• Sungjae Lee, Hyejin Park, Jaechang Kim, and Jungseul Ok, "Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models", ACL 2025 (main, long)

• Jabin Koo, Minwoo Jang, and Jungseul Ok, "Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients", ACL 2025 (main, long)

• Solee Im, Wonjun Lee, Jinmyeong An, Yunsu Kim, Jungseul Ok, and Gary Lee, "DeRAGEC: Denoising Named Entity Candidates with Synthetic Rationale for ASR Error Correction", ACL 2025 (findings, short)

• Seungbeom Lee*, Munsun Jo*, Jungseul Ok, and Dongwoo Kim, "Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization", ICML, 2025

• Hyojin Ju , Jungeun Lee , Seungwon Yang , Jungseul Ok , Inseok Hwang, "Toward Affective Empathy via Personalized Analogy Generation: A Case Study on Microaggression", CHI 2025

• Jaechang Kim, Jinmin Goh, Inseok Hwang, Jaewoong Cho, Jungseul Ok, "Bridging the Gap between Expert and Language Models: Concept-guided Chess Commentary Generation and Evaluation", NAACL 2025 (main, long) 

• Jinmyeong An, Sangwon Ryu, Heejin Do, Yunsu Kim, Jungseul Ok, Gary Lee, "Revisiting Early Detection of Sexual Predators via Turn-level Optimization", NAACL 2025 (main, long)

• Wonjun Lee*, Solee Im*, Heejin Do, Yunsu Kim, Jungseul Ok, and Gary Lee, "DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognition", NAACL 2025 (main, long)

• Jinmyeong An, Wonjun Lee, Yejin Jeon, Jungseul Ok, Yunsu Kim, and Gary Geunbae Lee, "An Investigation Into Explainable Audio Hate Speech Detection", SIGDIAL 2024 

• Juwon Kang, Nayeong Kim, Jungseul Ok, and Suha Kwak, "MemBN: Robust Test-Time Adaptation via Batch Norm with Statistics Memory",  ECCV 2024

• Sangwon Ryu, Heejin Do, Yunsu Kim, Gary Geunbae Lee, and Jungseul Ok, "Key-Element-Informed sLLM Tuning for Document Summarization", INTERSPEECH 2024

• Sangwon Ryu*, Heejin Do*, Yunsu Kim, Gary Geunbae Lee, and Jungseul Ok, "Multi-Dimensional Optimization for Text Summarization via Reinforcement Learning", ACL 2024 (main, long)

• Hoyoung Kim, Sehyun Hwang, Suha Kwak, and Jungseul Ok, "Active Label Correction for Semantic Segmentation with Foundation Models", ICML 2024 

• Youngsik Yoon, Gangbok Lee, Sungsoo Ahn, and Jungseul Ok, "Breadth-First Exploration in Adaptive Grid-based Reinforcement Learning", ICML 2024

• Nayeong Kim, Juwon Kang, Sungsoo Ahn, Jungseul Ok, and Suha Kwak, "Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization", ICML 2024

• Youngsik Yoon*, Jinhwan Nam*, Hyojeong Yun, Jaeho Lee, Dongwoo Kim, and Jungseul Ok, "Few-shot Unlearning", IEEE Symposium on Security and Privacy (S&P) 2024

• Hyejin Park*, Jeongyeon Hwang*, Sunung Mun, Sangdon Park, Jungseul Ok, "MedBN: Robust Test Time Adaptation against Malicious Test Samples", CVPR 2024

• Hyeongmin Lee, Kyoungkook Kang, Jungseul Ok, and Sunghyun Cho, "CLIPtone: Unsupervised Learning for Text-based Image Tone Adjustment", CVPR 2024

• Sehyun Hwang, Sohyun Lee, Hoyoung Kim, Minhyeon Oh, Jungseul Ok, and Suha Kwak, "Active Learning for Semantic Segmentation with Multi-class Label Query", NeurIPS 2023

• Hoyoung Kim, Minhyeon Oh, Sehyun Hwang, Suha Kwak, and Jungseul Ok, "Adaptive Superpixel for Active Learning in Semantic Segmentation", ICCV 2023

• Juwon Kang, Nayeong Kim, Donghyeon Kwon, Jungseul Ok, and Suha Kwak, "Leveraging Proxy of Training Data for Test-Time Adaptation", ICML 2023

• Jaechang Kim, Yunjoo Lee, Hyun Mi Cho, Dong Woo Kim, Chi Hoon Song, and Jungseul Ok, "Activity-informed Industrial Audio Anomaly Detection via Source Separation", ICASSP 2023

• Byungchan Ko and Jungseul Ok, "Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning", NeurIPS 2022

• Minji Kim, Seungkwan Lee, Jungseul Ok, Bohyung Han, and Minsu Cho, "Towards Sequence-Level Training for Visual Tracking", ECCV 2022

• Sehyun Hwang, Sohyun Lee, Sungyeon Kim, Jungseul Ok, and Suha Kwak, "Combating Label Distribution Shift for Active Domain Adaptation", ECCV 2022

• Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon, and Dongwoo Kim, "MetaSSD: Meta-Learned Self-Supervised Detection", ISIT 2022

• Jaechang Kim*, Yunjoo Lee*, Seunghoon Hong, and Jungseul Ok, "Learning Continuous Representation of Audio for Arbitrary Scale Super-Resolution", ICASSP 2022

• Hoyoung Kim*, Seung Hyuk Cho*, Dongwoo Kim, and Jungseul Ok, "Robust Deep Learning from Crowds with Belief Propagation", AISTATS 2022

• Suho Shin, Seungjoon Lee, and Jungseul Ok, "Multi-armed Bandit Algorithm against Strategic Replication", AISTATS 2022

• Suho Shin, Hoyong Choi, Yung Yi, and  Jungseul Ok "Power of Bonus in Pricing for Crowdsourcing",  ACM SIGMETRICS 2022

• Jaechang Kim*, Jinwoo Jeon*, Kangwook Lee, Sewoong Oh, and Jungseul Ok, "Gradient Inversion with Generative Image Prior", NeurIPS 2021 (also ICML-FL 2021)

• Hyejin Park, Seiyun Shin, Kwang-Sung Jun, and Jungseul Ok, "Transfer Learning in Bandits with Latent Continuity",  ISIT 2021

• Jiin Woo, Jungseul Ok, and Yung Yi , "Iterative Learning of Graph Connectivity from Partially-Observed Cascade Samples", ACM MobiHoc 2020

• Jungseul Ok, Sewoong Oh, Yunhun Jang, Jinwoo Shin, and Yung Yi,  "Iterative Bayesian Learning for Crowdsourced Regression", AISTATS 2019, [code]

• Jungseul Ok, Alexandre Proutiere, and Damianos Tranos, "Exploration in Structured Reinforcement Learning",  NeurIPS 2018 (oral presentation), [slide] [poster]

• Weiran Huang, Jungseul Ok, Liang Li, Wei Chen "Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications" , IJCAI 2018 

• Jungseul Ok, Se-Young Yun, Alexandre Proutiere, and Rami Mochaourab, "Collaborative Clustering: Sample complexity and Efficient Algorithms", ALT 2017

• Jungseul Ok, Jinwoo Shin, and Yung Yi , "Incentivizing Strategic Users for Social Diffusion: Quantity or Quality?", IEEE INFOCOM 2017 [slide]

• Jungseul Ok, Sewoong Oh, Jinwoo Shin and Yung Yi,  "Optimality of Belief Propagation for Crowdsourced Classification", ICML 2016  [slide] [supp] [code]

• Jungseul Ok, Jinwoo Shin, and Yung Yi , "On the Progressive Spread over Strategic Diffusion: Asymptotic and Computation" , IEEE INFOCOM 2015 (Bronze Prize, 21st Samsung Humantech Thesis, Samsung Electronics, 2014) [slide]

• Jungseul Ok, Youngmi Jin, Jinwoo Shin and Yung Yi, "On Maximizing the Diffusion Speed in Social Networks: Impact of Random Seeding and Clustering", ACM SIGMETRICS 2014 [slide]

• Richard Combes, Alexandre Proutiere, Donggyu Yun, Jungseul Ok, and Yung Yi, "Optimal Rate Sampling in 802.11 Systems" , IEEE INFOCOM 2014 [code]

• Youngmi Jin, Jungseul Ok, Yung Yi, and Jinwoo Shin, "On the Impact of Global Information on Diffusion of Innovations over Social Networks", NetSciCom@IEEE INFOCOM 2013

• Seungje Woo, Sung G. Lee, Jungseul Ok, and Jong-Hwan Kim, "Development and Implementation of Break Falling System for a Biped Robot", RiTA 2012 [demo]

Journal

• Hyejin Park, Seiyun Shin, Kwang-Sung Jun, and Jungseul Ok, "Transfer Learning in Bandits with Latent Continuity", IEEE Transactions on Information Theory, Aug 2024

• Kaito Ariu, Jungseul Ok, Alexandre Proutiere, and Seyoung Yun, "Optimal Clustering from Noisy Binary Feedback", Machine Learning, 2024.

• Richard Combes, Jungseul Ok, Alexandre Proutiere, Donggyu Yun, and Yung Yi , “Optimal Rate Sampling in 802.11 systems: Theory, Design, and Implementation", IEEE Transactions on Mobile Computing, vol 18, no. 5, pp. 1145-1158, May 2019, doi: 10.1109/TMC.2018.2854758.[code]

• Jungseul Ok, Sewoong Oh, Jinwoo Shin, and Yung Yi, "Optimal Inference in Crowdsourced Classification via Belief Propagation" IEEE Transactions on Information Theory, vol. 64, no. 9, pp. 6127-6138, 2018

• Jungseul Ok, Youngmi Jin, Jinwoo Shin, and Yung Yi,  "On Maximizing Diffusion Speed over Social Network with Strategic Users"  IEEE/ACM Transactions of Networking, vol. 24, no. 6, pp. 3798-3811, Dec 2016, doi:10.1109/TNET.2016.2556719 [supp]

• Donggyu Yun, Jungseul Ok, Bongjhin Shin, Soobum Park, and Yung Yi, "Embedding of Virtual Network Requests over Static Wireless Multihop Networks"  Elsevier Computer Networks, vol.57, no.5, pp.1139-1152 , 2013. [code]

Invited Paper

• Jungseul Ok, Sewoong Oh, Jinwoo Shin, and Yung Yi,  "Optimality of Belief Propagation for Crowdsourced Classification", CrowdML@NIPS, 2016  [slide] [supp] [code]

• Jungseul Ok, Youngmi Jin, Jaeyoung Choi, Jinwoo Shin, and Yung Yi, "Influence Maximization over Strategic Diffusion in Social Networks" , IEEE CISS, 2014 (invited paper)