Yun, Se-Young

89 publications

NeurIPS 2025 AdaSTaR: Adaptive Data Sampling for Training Self-Taught Reasoners Woosung Koh, Wonbeen Oh, Jaein Jang, MinHyung Lee, Hyeongjin Kim, Ah Yeon Kim, Joonkee Kim, Junghyun Lee, Taehyeon Kim, Se-Young Yun

TMLR 2025 Adversarial Bandits Against Arbitrary Strategies Jung-hun Kim, Se-Young Yun

ICLR 2025 Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models Yongjin Yang, Sihyeon Kim, Hojung Jung, Sangmin Bae, SangMook Kim, Se-Young Yun, Kimin Lee

ICML 2025 DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun

NeurIPS 2025 Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems Minchan Jeong, Jongha Jon Ryu, Se-Young Yun, Gregory W. Wornell

TMLR 2025 FedDr+: Stabilizing Dot-Regression with Global Feature Distillation for Federated Learning Seongyoon Kim, Minchan Jeong, Sungnyun Kim, Sungwoo Cho, Sumyeong Ahn, Se-Young Yun

NeurIPS 2025 Flex-Judge: Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators Jongwoo Ko, Sungnyun Kim, Sungwoo Cho, Se-Young Yun

ICLR 2025 FlickerFusion: Intra-Trajectory Domain Generalizing Multi-Agent Reinforcement Learning Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun

NeurIPS 2025 KLASS: KL-Guided Fast Inference in Masked Diffusion Models Seo Hyun Kim, Sunwoo Hong, Hojung Jung, Youngrok Park, Se-Young Yun

ICLR 2025 MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder Sehyeok Kang, Yongsik Lee, Gahee Kim, Song Chong, Se-Young Yun

ICCV 2025 MAVFlow: Preserving Paralinguistic Elements with Conditional Flow Matching for Zero-Shot AV2AV Multilingual Translation Sungwoo Cho, Jeongsoo Choi, Sungnyun Kim, Se-Young Yun

NeurIPS 2025 Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation Sangmin Bae, Yujin Kim, Reza Bayat, Sungnyun Kim, Jiyoun Ha, Tal Schuster, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Aaron Courville, Se-Young Yun

ICML 2025 MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition Sungnyun Kim, Kangwook Jang, Sangmin Bae, Sungwoo Cho, Se-Young Yun

ICLR 2025 Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation Sungnyun Kim, Sungwoo Cho, Sangmin Bae, Kangwook Jang, Se-Young Yun

ICLRW 2025 Probability-Flow ODE in Infinite-Dimensional Function Spaces Kunwoo Na, Junghyun Lee, Se-Young Yun, Sungbin Lim

ICML 2025 QuRe: Query-Relevant Retrieval Through Hard Negative Sampling in Composed Image Retrieval Jaehyun Kwak, Ramahdani Muhammad Izaaz Inhar, Se-Young Yun, Sung-Ju Lee

ICML 2025 Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model Kaito Ariu, Alexandre Proutiere, Se-Young Yun

TMLR 2025 VSCoDe: Visual-Augmentation Selection for Contrastive Decoding Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, Se-Young Yun

ICLRW 2025 When Debate Fails: Bias Reinforcement in Large Language Models Jihwan Oh, Minchan Jeong, Jongwoo Ko, Se-Young Yun

NeurIPS 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Jungyhun Lee, Se-Young Yun, Kwang-Sung Jun

ICMLW 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee, Se-Young Yun, Kwang-Sung Jun

NeurIPS 2024 An Adaptive Approach for Infinitely Many-Armed Bandits Under Generalized Rotting Constraints Jung-hun Kim, Milan Vojnović, Se-Young Yun

NeurIPS 2024 Block Transformer: Global-to-Local Language Modeling for Fast Inference Namgyu Ho, Sangmin Bae, Taehyeon Kim, Hyunjik Jo, Yireun Kim, Tal Schuster, Adam Fisch, James Thorne, Se-Young Yun

NeurIPS 2024 Conditional Synthesis of 3D Molecules with Time Correction Sampler Hojung Jung, Youngrok Park, Laura Schmid, Jaehyeong Jo, Dongkyu Lee, Bongsang Kim, Se-Young Yun, Jinwoo Shin

ICMLW 2024 DPM: Dual Preferences-Based Multi-Agent Reinforcement Learning Sehyeok Kang, Yongsik Lee, Se-Young Yun

ICMLW 2024 Diffusion-Based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning Jihwan Oh, Sungnyun Kim, Gahee Kim, SeongHwan Kim, Se-Young Yun

ICML 2024 DistiLLM: Towards Streamlined Distillation for Large Language Models Jongwoo Ko, Sungnyun Kim, Tianyi Chen, Se-Young Yun

TMLR 2024 FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels Taehyeon Kim, Donggyu Kim, Se-Young Yun

CVPR 2024 FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning Gihun Lee, Minchan Jeong, Sangmook Kim, Jaehoon Oh, Se-Young Yun

IJCAI 2024 Fine-Tuning Pre-Trained Models for Robustness Under Noisy Labels Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun

NeurIPSW 2024 FlickerFusion: Intra-Trajectory Domain Generalizing Multi-Agent RL Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun

AISTATS 2024 Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion Junghyun Lee, Se-Young Yun, Kwang-Sung Jun

ICLR 2024 Instructive Decoding: Instruction-Tuned Large Language Models Are Self-Refiner from Noisy Instructions Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun

AAAI 2024 Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning Yongjin Yang, Taehyeon Kim, Se-Young Yun

TMLR 2024 Non-Backtracking Graph Neural Networks Seonghyun Park, Narae Ryu, Gahee Kim, Dongyeop Woo, Se-Young Yun, Sungsoo Ahn

NeurIPS 2024 Preference Alignment with Flow Matching Minu Kim, Yongsik Lee, Sehyeok Kang, Jihwan Oh, Song Chong, Se-Young Yun

ICML 2024 Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs Mingyu Kim, Kim Jun-Seong, Se-Young Yun, Jin-Hwa Kim

ICLRW 2024 Towards Unbiased Evaluation of Detecting Unanswerable Questions in EHRSQL Yongjin Yang, Sihyeon Kim, SangMook Kim, Gyubok Lee, Se-Young Yun, Edward Choi

ICMLW 2024 VACoDe: Visual Augmented Contrastive Decoding Sihyeon Kim, Boryeong Cho, Sangmin Bae, Sumyeong Ahn, Se-Young Yun

AAAI 2023 A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier Under Label Noise Jongwoo Ko, Bongsoo Yi, Se-Young Yun

ICMLW 2023 An Optimal Clustering Algorithm for the Labeled Stochastic Block Model Kaito Ariu, Se-Young Yun, Alexandre Proutiere

ICLR 2023 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

NeurIPSW 2023 Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models Yujin Kim, Jaehong Yoon, Seonghyeon Ye, Sung Ju Hwang, Se-Young Yun

AISTATS 2023 Contextual Linear Bandits Under Noisy Features: Towards Bayesian Oracles Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes

CVPR 2023 Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning Sungnyun Kim, Sangmin Bae, Se-Young Yun

AAAI 2023 Denoising After Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels Sumyeong Ahn, Se-Young Yun

NeurIPSW 2023 Distort, Distract, Decode: Instruction-Tuned Model Can Refine Its Response from Noisy Instructions Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun

ICLRW 2023 Efficient Utilization of Pre-Trained Model for Learning with Noisy Labels Jongwoo Ko, Sumyeong Ahn, Se-Young Yun

NeurIPS 2023 Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint Junghyun Lee, Hanseul Cho, Se-Young Yun, Chulhee Yun

NeurIPSW 2023 FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning Seongyoon Kim, Gihun Lee, Jaehoon Oh, Se-Young Yun

NeurIPSW 2023 FedSoL: Bridging Global Alignment and Local Generality in Federated Learning Gihun Lee, Minchan Jeong, SangMook Kim, Jaehoon Oh, Se-Young Yun

NeurIPSW 2023 Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning Felix den Breejen, Sangmin Bae, Stephen Cha, Tae-Young Kim, Seoung Hyun Koh, Se-Young Yun

ICLR 2023 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

AISTATS 2023 Nearly Optimal Latent State Decoding in Block MDPs Yassir Jedra, Junghyun Lee, Alexandre Proutiere, Se-Young Yun

NeurIPSW 2023 Node Mutual Information: Enhancing Graph Neural Networks for Heterophily Seongjin Choi, Gahee Kim, Se-Young Yun

NeurIPSW 2023 Non-Backtracking Graph Neural Networks Seonghyun Park, Narae Ryu, Gahee Kim, Dongyeop Woo, Se-Young Yun, Sungsoo Ahn

NeurIPS 2023 PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning Hojoon Lee, Hanseul Cho, Hyunseung Kim, Daehoon Gwak, Joonkee Kim, Jaegul Choo, Se-Young Yun, Chulhee Yun

NeurIPSW 2023 Parameter Averaging Laws for Multitask Language Models Woojin Chung, Hyowon Cho, James Thorne, Se-Young Yun

CVPR 2023 Re-Thinking Federated Active Learning Based on Inter-Class Diversity SangMook Kim, Sangmin Bae, Hwanjun Song, Se-Young Yun

NeurIPSW 2023 Refined Tensorial Radiance Field: Harnessing Coordinate-Based Networks for Novel View Synthesis from Sparse Inputs Mingyu Kim, Kim Jun-Seong, Se-Young Yun, Jin-Hwa Kim

AAAI 2023 Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-Network Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun

NeurIPSW 2022 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

NeurIPSW 2022 CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

ICLR 2022 FedBABU: Toward Enhanced Representation for Federated Image Classification Jaehoon Oh, SangMook Kim, Se-Young Yun

NeurIPSW 2022 Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning Seongha Eom, Taehyeon Kim, Se-Young Yun

NeurIPSW 2022 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

NeurIPSW 2022 Mitigating Dataset Bias by Using Per-Sample Gradient Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

ICLR 2022 Neural Processes with Stochastic Attention: Paying More Attention to the Context Dataset Mingyu Kim, Kyeong Ryeol Go, Se-Young Yun

NeurIPS 2022 Preservation of the Global Knowledge by Not-True Distillation in Federated Learning Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun

NeurIPSW 2022 Revisiting the Activation Function for Federated Image Classification Jaewoo Shin, Taehyeon Kim, Se-Young Yun

ICMLW 2022 Risk Perspective Exploration in Distributional Reinforcement Learning Jihwan Oh, Joonkee Kim, Se-Young Yun

NeurIPS 2022 Robust Streaming PCA Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun

ICML 2022 Rotting Infinitely Many-Armed Bandits Jung-Hun Kim, Milan Vojnovic, Se-Young Yun

ICMLW 2022 The StarCraft Multi-Agent Challenges+ : Learning of Sub-Tasks and Environmental Benefits Without Precise Reward Functions Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong, Se-Young Yun

NeurIPS 2022 Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song, Se-Young Yun

ICLR 2021 BOIL: Towards Representation Change for Few-Shot Learning Jaehoon Oh, Hyungjun Yoo, ChangHwan Kim, Se-Young Yun

IJCAI 2021 Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation Taehyeon Kim, Jaehoon Oh, Nakyil Kim, Sangwook Cho, Se-Young Yun

NeurIPS 2021 FINE Samples for Learning with Noisy Labels Taehyeon Kim, Jongwoo Ko, Sangwook Cho, JinHwan Choi, Se-Young Yun

ICML 2021 Improved Regret Bounds of Bilinear Bandits Using Action Space Analysis Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang

NeurIPSW 2021 Neural Processes with Stochastic Attention: Paying More Attention to the Context Dataset Mingyu Kim, Kyeong Ryeol Go, Se-Young Yun

AISTATS 2020 Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models Milan Vojnovic, Se-Young Yun, Kaifang Zhou

NeurIPS 2020 Regret in Online Recommendation Systems Kaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutiere

NeurIPS 2019 Optimal Sampling and Clustering in the Stochastic Block Model Se-Young Yun, Alexandre Proutiere

ICML 2019 Spectral Approximate Inference Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin

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

NeurIPS 2016 Optimal Cluster Recovery in the Labeled Stochastic Block Model Se-Young Yun, Alexandre Proutiere

NeurIPS 2015 Fast and Memory Optimal Low-Rank Matrix Approximation Se-Young Yun, Marc Lelarge, Alexandre Proutiere

COLT 2014 Community Detection via Random and Adaptive Sampling Se-Young Yun, Alexandre Proutière

NeurIPS 2014 Streaming, Memory Limited Algorithms for Community Detection Se-Young Yun, Marc Lelarge, Alexandre Proutiere