Development and Implementation of Break Falling System for a Biped Robot. - Seung Je Woo; Sung G. Lee; Jungseul Ok; Jong-Hwan Kim (RiTA, 2012)

On the impact of global information on diffusion of innovations over social networks. - Youngmi Jin; Jungseul Ok; Yung Yi; Jinwoo Shin (INFOCOM, 2013)

Embedding of virtual network requests over static wireless multihop networks. - Donggyu Yun; Jungseul Ok; Bongjhin Shin; Soobum Park; Yung Yi (Comput. Networks, 2013)

Influence maximization over strategic diffusion in social networks. - Jungseul Ok; Youngmi Jin; Jaeyoung Choi 001; Jinwoo Shin; Yung Yi (CISS, 2014)

Optimal Rate Sampling in 802.11 systems. - Richard Combes; Alexandre Proutière; Donggyu Yun; Jungseul Ok; Yung Yi (INFOCOM, 2014)

On maximizing diffusion speed in social networks: impact of random seeding and clustering. - Jungseul Ok; Youngmi Jin; Jinwoo Shin; Yung Yi (SIGMETRICS, 2014)

On the progressive spread over strategic diffusion: Asymptotic and computation. - Jungseul Ok; Jinwoo Shin; Yung Yi (INFOCOM, 2015)

Optimality of Belief Propagation for Crowdsourced Classification. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yung Yi (ICML, 2016)

On Maximizing Diffusion Speed Over Social Networks With Strategic Users. - Jungseul Ok; Youngmi Jin; Jinwoo Shin; Yung Yi (IEEE/ACM Trans. Netw., 2016)

Collaborative Clustering: Sample Complexity and Efficient Algorithms. - Jungseul Ok; Se-Young Yun; Alexandre Proutière; Rami Mochaourab (ALT, 2017)

Incentivizing strategic users for social diffusion: Quantity or quality? - Jungseul Ok; Jinwoo Shin; Yung Yi (INFOCOM, 2017)

Efficient Learning for Crowdsourced Regression. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yunhun Jang; Yung Yi (CoRR, 2017)

Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications. - Weiran Huang 001; Jungseul Ok; Liang Li; Wei Chen 013 (IJCAI, 2018)

Exploration in Structured Reinforcement Learning. - Jungseul Ok; Alexandre Proutière; Damianos Tranos (NeurIPS, 2018)

On the Posted Pricing in Crowdsourcing: Power of Bonus. - Suho Shin 001; Jungseul Ok; Hoyong Choi; Yung Yi (CoRR, 2018)

Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version). - Weiran Huang 001; Jungseul Ok; Liang Li; Wei Chen 013 (CoRR, 2018)

Optimal Inference in Crowdsourced Classification via Belief Propagation. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yung Yi (IEEE Trans. Inf. Theory, 2018)

Iterative Bayesian Learning for Crowdsourced Regression. - Jungseul Ok; Sewoong Oh; Yunhun Jang; Jinwoo Shin; Yung Yi (AISTATS, 2019)

Optimal Rate Sampling in 802.11 Systems: Theory, Design, and Implementation. - Richard Combes; Jungseul Ok; Alexandre Proutière; Donggyu Yun; Yung Yi (IEEE Trans. Mob. Comput., 2019)

Iterative learning of graph connectivity from partially-observed cascade samples. - Jiin Woo; Jungseul Ok; Yung Yi (MobiHoc, 2020)

Gradient Inversion with Generative Image Prior. - Jinwoo Jeon; Jaechang Kim 001; Kangwook Lee 001; Sewoong Oh; Jungseul Ok (NeurIPS, 2021)

Time Matters in Using Data Augmentation for Vision-based Deep Reinforcement Learning. - Byungchan Ko; Jungseul Ok (CoRR, 2021)

Power of Bonus in Pricing for Crowdsourcing. - Suho Shin 001; Hoyong Choi; Yung Yi; Jungseul Ok (Proc. ACM Meas. Anal. Comput. Syst., 2021)

Robust Deep Learning from Crowds with Belief Propagation. - Hoyoung Kim; Seunghyuk Cho; Dongwoo Kim 002; Jungseul Ok (AISTATS, 2022)

Multi-armed Bandit Algorithm against Strategic Replication. - Suho Shin 001; Seungjoon Lee; Jungseul Ok (AISTATS, 2022)

Combating Label Distribution Shift for Active Domain Adaptation. - Sehyun Hwang; Sohyun Lee; Sungyeon Kim; Jungseul Ok; Suha Kwak (ECCV (33), 2022)

Towards Sequence-Level Training for Visual Tracking. - Minji Kim 002; Seungkwan Lee; Jungseul Ok; Bohyung Han; Minsu Cho (ECCV (22), 2022)

Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution. - Jaechang Kim 001; Yunjoo Lee; Seunghoon Hong; Jungseul Ok (ICASSP, 2022)

MetaSSD: Meta-Learned Self-Supervised Detection. - Moon Jeong Park; Jungseul Ok; Yo-Seb Jeon; Dongwoo Kim 002 (ISIT, 2022)

Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning. - Byungchan Ko; Jungseul Ok (NeurIPS, 2022)

Few-Shot Unlearning by Model Inversion. - Youngsik Yoon; Jinhwan Nam; Hyojeong Yun; Dongwoo Kim 002; Jungseul Ok (CoRR, 2022)

Activity-Informed Industrial Audio Anomaly Detection Via Source Separation. - Jaechang Kim 001; Yunjoo Lee; Hyun Mi Cho; Dong Woo Kim 002; Chi Hoon Song; Jungseul Ok (ICASSP, 2023)

Adaptive Superpixel for Active Learning in Semantic Segmentation. - Hoyoung Kim; Minhyeon Oh; Sehyun Hwang; Suha Kwak; Jungseul Ok (ICCV, 2023)

Leveraging Proxy of Training Data for Test-Time Adaptation. - Juwon Kang; Nayeong Kim; Donghyeon Kwon; Jungseul Ok; Suha Kwak (ICML, 2023)

Active Learning for Semantic Segmentation with Multi-class Label Query. - Sehyun Hwang; Sohyun Lee; Hoyoung Kim; Minhyeon Oh; Jungseul Ok; Suha Kwak (NeurIPS, 2023)

Addressing Feature Imbalance in Sound Source Separation. - Jaechang Kim 001; Jeongyeon Hwang; Soheun Yi; Jaewoong Cho; Jungseul Ok (CoRR, 2023)

Multi-Dimensional Optimization for Text Summarization via Reinforcement Learning. - Sangwon Ryu; Heejin Do; Yunsu Kim 001; Gary Lee 001; Jungseul Ok (ACL (1), 2024)

CLIPtone: Unsupervised Learning for Text-Based Image Tone Adjustment. - Hyeongmin Lee; Kyoungkook Kang; Jungseul Ok; Sunghyun Cho (CVPR, 2024)

MedBN: Robust Test-Time Adaptation against Malicious Test Samples. - Hyejin Park 002; Jeongyeon Hwang; Sunung Mun; Sangdon Park; Jungseul Ok (CVPR, 2024)

MemBN: Robust Test-Time Adaptation via Batch Norm with Statistics Memory. - Juwon Kang; Nayeong Kim; Jungseul Ok; Suha Kwak (ECCV (28), 2024)

Active Label Correction for Semantic Segmentation with Foundation Models. - Hoyoung Kim; Sehyun Hwang; Suha Kwak; Jungseul Ok (ICML, 2024)

Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization. - Nayeong Kim; Juwon Kang; Sungsoo Ahn; Jungseul Ok; Suha Kwak (ICML, 2024)

Breadth-First Exploration on Adaptive Grid for Reinforcement Learning. - Youngsik Yoon; Gangbok Lee; Sungsoo Ahn; Jungseul Ok (ICML, 2024)

Key-Element-Informed sLLM Tuning for Document Summarization. - Sangwon Ryu; Heejin Do; Yunsu Kim 001; Gary Geunbae Lee; Jungseul Ok (INTERSPEECH, 2024)

An Investigation into Explainable Audio Hate Speech Detection. - Jinmyeong An; Wonjun Lee; Yejin Jeon; Jungseul Ok; Yunsu Kim 001; Gary Geunbae Lee (SIGDIAL, 2024)

Few-shot Unlearning. - Youngsik Yoon; Jinhwan Nam; Hyojeong Yun; Jaeho Lee; Dongwoo Kim 002; Jungseul Ok (SP, 2024)

Activity-Guided Industrial Anomalous Sound Detection against Interferences. - Yunjoo Lee; Jaechang Kim 001; Jungseul Ok (CoRR, 2024)

Retrieval-Augmented Generation with Estimation of Source Reliability. - Jeongyeon Hwang; Junyoung Park; Hyejin Park 002; Sangdon Park; Jungseul Ok (CoRR, 2024)

Active Preference-based Learning for Multi-dimensional Personalization. - Minhyeon Oh; Seungjoon Lee; Jungseul Ok (CoRR, 2024)

Guide-to-Explain for Controllable Summarization. - Sangwon Ryu; Heejin Do; Daehee Kim; Yunsu Kim 001; Gary Geunbae Lee; Jungseul Ok (CoRR, 2024)

Active Prompt Learning with Vision-Language Model Priors. - Hoyoung Kim; Seokhee Jin; Changhwan Sung; Jaechang Kim 001; Jungseul Ok (CoRR, 2024)

Combinatorial Rising Bandit. - Seockbean Song; Youngsik Yoon; Siwei Wang 002; Wei Chen 013; Jungseul Ok (CoRR, 2024)

Addressing Attribute Leakages in Diffusion-based Image Editing without Training. - Sunung Mun; Jinhwan Nam; Sunghyun Cho; Jungseul Ok (CoRR, 2024)

Optimal clustering from noisy binary feedback. - Kaito Ariu; Jungseul Ok; Alexandre Proutière; Seyoung Yun (Mach. Learn., 2024)

Transfer Learning in Bandits With Latent Continuity. - Hyejin Park 002; Seiyun Shin; Kwang-Sung Jun; Jungseul Ok (IEEE Trans. Inf. Theory, 2024)

DeRAGEC: Denoising Named Entity Candidates with Synthetic Rationale for ASR Error Correction. - Solee Im; Wonjun Lee; Jinmyeong An; Yunsu Kim 001; Jungseul Ok; Gary Geunbae Lee (ACL (Findings), 2025)

Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients. - Jabin Koo; Minwoo Jang; Jungseul Ok (ACL (1), 2025)

Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models. - Sungjae Lee; Hyejin Park 002; Jaechang Kim 001; Jungseul Ok (ACL (1), 2025)

Comparison-based Active Preference Learning for Multi-dimensional Personalization. - Minhyeon Oh; Seungjoon Lee; Jungseul Ok (ACL (1), 2025)

Toward Affective Empathy via Personalized Analogy Generation: A Case Study on Microaggression. - Hyojin Ju; Jungeun Lee; Seungwon Yang; Jungseul Ok; Inseok Hwang 001 (CHI, 2025)

Revisiting Early Detection of Sexual Predators via Turn-level Optimization. - Jinmyeong An; Sangwon Ryu; Heejin Do; Yunsu Kim 001; Jungseul Ok; Gary Lee 001 (NAACL (Long Papers), 2025)

Bridging the Gap between Expert and Language Models: Concept-guided Chess Commentary Generation and Evaluation. - Jaechang Kim 001; Jinmin Goh; Inseok Hwang 001; Jaewoong Cho; Jungseul Ok (NAACL (Long Papers), 2025)

DyPCL: Dynamic Phoneme-level Contrastive Learning for Dysarthric Speech Recognition. - Wonjun Lee; Solee Im; Heejin Do; Yunsu Kim 001; Jungseul Ok; Gary Lee 001 (NAACL (Long Papers), 2025)

Enhancing Cost Efficiency in Active Learning with Candidate Set Query. - Yeho Gwon; Sehyun Hwang; Hoyoung Kim; Jungseul Ok; Suha Kwak (Trans. Mach. Learn. Res., 2025)

CoPL: Collaborative Preference Learning for Personalizing LLMs. - Youngbin Choi; Seunghyuk Cho; Minjong Lee; Moon Jeong Park; Yesong Ko; Jungseul Ok; Dongwoo Kim 002 (CoRR, 2025)

MiLQ: Benchmarking IR Models for Bilingual Web Search with Mixed Language Queries. - Jonghwi Kim; Deokhyung Kang; Seonjeong Hwang; Yunsu Kim 001; Jungseul Ok; Gary Lee 001 (CoRR, 2025)

Self-Training Large Language Models with Confident Reasoning. - Hyosoon Jang; Yunhui Jang; Sungjae Lee; Jungseul Ok; Sungsoo Ahn (CoRR, 2025)

Don't Just Follow MLLM Plans: Robust and Efficient Planning for Open-world Agents. - Seungjoon Lee; Suhwan Kim; Minhyeon Oh; Youngsik Yoon; Jungseul Ok (CoRR, 2025)

Efficient Latent Semantic Clustering for Scaling Test-Time Computation of LLMs. - Sungjae Lee; Hoyoung Kim; Jeongyeon Hwang; Eunhyeok Park; Jungseul Ok (CoRR, 2025)

Influence Functions for Edge Edits in Non-Convex Graph Neural Networks. - Jaeseung Heo; Kyeongheung Yun; Seokwon Yoon; Moonjeong Park; Jungseul Ok; Dongwoo Kim 002 (CoRR, 2025)

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark. - Suyeon Kim; SeongKu Kang; Dongwoo Kim; Jungseul Ok; Hwanjo Yu (CoRR, 2025)