Decentralized power control scheme in femtocell networks: A game theoretic approach. - Eun Jin Hong; Seyoung Yun; Dong-Ho Cho (PIMRC, 2009)

On the pricing of femtocell services. - Seyoung Yun; Yung Yi; Dong-Ho Cho; Jeonghoon Mo (CFI, 2010)

Traffic density based power control scheme for femto AP. - Seyoung Yun; Dong-Ho Cho (PIMRC, 2010)

Multi-channel MAC protocol for QoS support in ad-hoc network. - Kyung-Seop Shin; Se-Young Yun; Dong-Ho Cho (CCNC, 2011)

Open or close: On the sharing of femtocells. - Se-Young Yun; Yung Yi; Dong-Ho Cho; Jeonghoon Mo (INFOCOM, 2011)

Optimal CSMA: A survey. - Se-Young Yun; Yung Yi; Jinwoo Shin; Do Young Eun (ICCS, 2012)

From Glauber dynamics to Metropolis algorithm: Smaller delay in optimal CSMA. - Chul-Ho Lee; Do Young Eun; Se-Young Yun; Yung Yi (ISIT, 2012)

The Economic Effects of Sharing Femtocells. - Se-Young Yun; Yung Yi; Dong-Ho Cho; Jeonghoon Mo (IEEE J. Sel. Areas Commun., 2012)

CSMA using the Bethe approximation for utility maximization. - Se-Young Yun; Jinwoo Shin; Yung Yi (ISIT, 2013)

CSMA over time-varying channels: optimality, uniqueness and limited backoff rate. - Se-Young Yun; Jinwoo Shin; Yung Yi (MobiHoc, 2013)

CSMA using Statistical Physics toward Throughput and Utility Optimal CSMA. - Se-Young Yun; Jinwoo Shin; Yung Yi (CoRR, 2013)

Distributed load balancing in heterogenous systems. - Se-Young Yun; Alexandre Proutière (CISS, 2014)

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

Distributed learning for utility maximization over CSMA-based wireless multihop networks. - Hyeryung Jang; Se-Young Yun; Jinwoo Shin; Yung Yi (INFOCOM, 2014)

Provable per-link delay-optimal CSMA for general wireless network topology. - Dongmyung Lee; Donggyu Yun; Jinwoo Shin; Yung Yi; Se-Young Yun (INFOCOM, 2014)

Streaming, Memory Limited Algorithms for Community Detection. - Se-Young Yun; Marc Lelarge; Alexandre Proutière (NIPS, 2014)

Accurate Community Detection in the Stochastic Block Model via Spectral Algorithms. - Se-Young Yun; Alexandre Proutière (CoRR, 2014)

Fast and Memory Optimal Low-Rank Matrix Approximation. - Se-Young Yun; Marc Lelarge; Alexandre Proutière (NIPS, 2015)

Distributed Proportional Fair Load Balancing in Heterogenous Systems. - Se-Young Yun; Alexandre Proutière (SIGMETRICS, 2015)

Optimality of Spectral Algorithms for Community Detection in the Labeled Stochastic Block Model. - Se-Young Yun; Alexandre Proutière (CoRR, 2015)

CSMA Using the Bethe Approximation: Scheduling and Utility Maximization. - Se-Young Yun; Jinwoo Shin; Yung Yi (IEEE Trans. Inf. Theory, 2015)

Parameter Estimation for Generalized Thurstone Choice Models. - Milan Vojnovic; Se-Young Yun (ICML, 2016)

Distributed coordination maximization over networks: a stochastic approximation approach. - Hyeryung Jang; Se-Young Yun; Jinwoo Shin; Yung Yi (MobiHoc, 2016)

Optimal Cluster Recovery in the Labeled Stochastic Block Model. - Se-Young Yun; Alexandre Proutière (NIPS, 2016)

Sketching with Test Scores and Submodular Maximization. - Shreyas Sekar; Milan Vojnovic; Se-Young Yun (CoRR, 2016)

Delay Optimal CSMA With Linear Virtual Channels Under a General Topology. - Donggyu Yun; Dongmyung Lee; Se-Young Yun; Jinwoo Shin; Yung Yi (IEEE/ACM Trans. Netw., 2016)

Distributed Medium Access Over Time-Varying Channels. - Se-Young Yun; 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)

On the Delay Scaling Laws of Cache Networks. - Boram Jin; Daewoo Kim; Se-Young Yun; Jinwoo Shin; Seongik Hong; Byoung-Joon Lee; Yung Yi (CFI, 2017)

Contextual Multi-armed Bandits under Feature Uncertainty. - Se-Young Yun; Jun Hyun Nam; Sangwoo Mo; Jinwoo Shin (CoRR, 2017)

Clustering in Block Markov Chains. - Jaron Sanders; Alexandre Proutière; Se-Young Yun (CoRR, 2017)

Noisy Power Method with Grassmann Average. - Se-Young Yun (BigComp, 2018)

Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each source. - Jaehoon Oh; Duyeon Kim; Se-Young Yun (CoRR, 2018)

Game Theoretic Perspective of Optimal CSMA. - Hyeryung Jang; Se-Young Yun; Jinwoo Shin; Yung Yi (IEEE Trans. Wirel. Commun., 2018)

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

Efficient Model for Image Classification With Regularization Tricks. - Taehyeon Kim 001; Jonghyup Kim; Seyoung Yun (NeurIPS (Competition and Demos), 2019)

Optimal Sampling and Clustering in the Stochastic Block Model. - Se-Young Yun; Alexandre Proutière (NeurIPS, 2019)

A pipelined hybrid recommender system for ranking the items on the display. - Jaehoon Oh; Sangmook Kim; Se-Young Yun; Seungwoo Choi; Mun Yong Yi (RecSys Challenge, 2019)

Convergence Rates of Gradient Descent and MM Algorithms for Generalized Bradley-Terry Models. - Milan Vojnovic; Seyoung Yun; Kaifang Zhou (CoRR, 2019)

Non-Stationary Streaming PCA. - Daniel Bienstock; Apurv Shukla 001; Seyoung Yun (CoRR, 2019)

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

Accelerating Randomly Projected Gradient with Variance Reduction. - Seongyoon Kim; SeYoung Yun (BigComp, 2020)

FEWER: Federated Weight Recovery. - Yongjin Shin; Gihun Lee; Seungjae Shin; Seyoung Yun; Il-Chul Moon (DistributedML@CoNEXT, 2020)

Precipitation Nowcasting Using Grid-based Data in South Korea Region. - ChangHwan Kim; Se-Young Yun (ICDM (Workshops), 2020)

SIPA: A Simple Framework for Efficient Networks. - Gihun Lee; Sangmin Bae; Jaehoon Oh; Se-Young Yun (ICDM (Workshops), 2020)

Regret in Online Recommendation Systems. - Kaito Ariu; Narae Ryu; Se-Young Yun; Alexandre Proutière (NeurIPS, 2020)

Does MAML really want feature reuse only? - Jaehoon Oh; Hyungjun Yoo; ChangHwan Kim; Se-Young Yun (CoRR, 2020)

MixCo: Mix-up Contrastive Learning for Visual Representation. - Sungnyun Kim; Gihun Lee; Sangmin Bae; Se-Young Yun (CoRR, 2020)

TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture. - Jin-Woo Lee; Jaehoon Oh; Sungsu Lim; Se-Young Yun; Jae-Gil Lee 001 (CoRR, 2020)

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits. - Taehyeon Kim 001; Sangmin Bae; Jin-Woo Lee; Seyoung Yun (CoRR, 2020)

Adaptive Local Bayesian Optimization Over Multiple Discrete Variables. - Taehyeon Kim 001; Jaeyeon Ahn; Nakyil Kim; Seyoung Yun (CoRR, 2020)

Reinforcement with Fading Memories. - Kuang Xu; Se-Young Yun (Math. Oper. Res., 2020)

BOIL: Towards Representation Change for Few-shot Learning. - Jaehoon Oh; Hyungjun Yoo; ChangHwan Kim; Se-Young Yun (ICLR, 2021)

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis. - Kyoungseok Jang; Kwang-Sung Jun; Se-Young Yun; Wanmo Kang (ICML, 2021)

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation. - Taehyeon Kim 001; Jaehoon Oh; Nakyil Kim; Sangwook Cho; Se-Young Yun (IJCAI, 2021)

Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. - Aleksandra Gruca; Federico Serva; Llorenç Lliso; Pilar Rípodas; Xavier Calbet; Pedro Herruzo; Jirí Pihrt; Rudolf Raevskiy; Petr Simánek; Matej Choma; Yang Li; Haiyu Dong; et al. (NeurIPS (Competition and Demos), 2021)

FINE Samples for Learning with Noisy Labels. - Taehyeon Kim 001; Jongwoo Ko; Sangwook Cho; Jinhwan Choi; Se-Young Yun (NeurIPS, 2021)

Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning. - Gihun Lee; Yongjin Shin; Minchan Jeong; Se-Young Yun (CoRR, 2021)

FedBABU: Towards Enhanced Representation for Federated Image Classification. - Jaehoon Oh; Sangmook Kim; Se-Young Yun (CoRR, 2021)

Self-Contrastive Learning. - Sangmin Bae; Sungnyun Kim; Jongwoo Ko; Gihun Lee; Seungjong Noh; Se-Young Yun (CoRR, 2021)

Meta-learning Amidst Heterogeneity and Ambiguity. - Kyeongryeol Go; Seyoung Yun (CoRR, 2021)

A Test Score-Based Approach to Stochastic Submodular Optimization. - Shreyas Sekar; Milan Vojnovic; Se-Young Yun (Manag. Sci., 2021)

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning. - Sangmook Kim; Wonyoung Shin; Soohyuk Jang; Hwanjun Song; Se-Young Yun (CIKM, 2022)

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CIKM, 2022)

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks. - Jaehoon Oh; Jongwoo Ko; Se-Young Yun (EMNLP, 2022)

Neural Processes with Stochastic Attention: Paying more attention to the context dataset. - Mingyu Kim 002; Kyeongryeol Go; Se-Young Yun (ICLR, 2022)

FedBABU: Toward Enhanced Representation for Federated Image Classification. - Jaehoon Oh; Sangmook Kim; Se-Young Yun (ICLR, 2022)

Real-time and Explainable Detection of Epidemics with Global News Data. - Sungnyun Kim; Jaewoo Shin; Seongha Eom; Jihwan Oh; Se-Young Yun (Healthcare AI and COVID-19 Workshop, 2022)

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

Robust Streaming PCA. - Daniel Bienstock; Minchan Jeong; Apurv Shukla 001; 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 (NeurIPS, 2022)

MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy. - Gihun Lee; SangMook Kim; Joonkee Kim; Se-Young Yun (Cell Segmentation Challenge @ 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 (NeurIPS, 2022)

Calibration of Few-Shot Classification Tasks: Mitigating Misconfidence From Distribution Mismatch. - Sungnyun Kim; Se-Young Yun (IEEE Access, 2022)

Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification. - Taehyeon Kim 001; Se-Young Yun (IEEE Access, 2022)

Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces. - Jaeyeon Ahn; Taehyeon Kim 001; Seyoung Yun (CoRR, 2022)

Understanding Cross-Domain Few-Shot Learning: An Experimental Study. - Jaehoon Oh; Sungnyun Kim; Namgyu Ho; Jin-Hwa Kim; Hwanjun Song; Se-Young Yun (CoRR, 2022)

SuperNet in Neural Architecture Search: A Taxonomic Survey. - Stephen Cha; Taehyeon Kim 001; Hayeon Lee; Se-Young Yun (CoRR, 2022)

Revisiting the Updates of a Pre-trained Model for Few-shot Learning. - Yujin Kim; Jaehoon Oh; Sungnyun Kim; Se-Young Yun (CoRR, 2022)

Adversarial Bandits Robust to S-Switch Regret. - Jung-Hun Kim; Se-Young Yun (CoRR, 2022)

Supernet Training for Federated Image Classification under System Heterogeneity. - Taehyeon Kim 001; Se-Young Yun (CoRR, 2022)

ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise. - Jongwoo Ko; Bongsoo Yi; Se-Young Yun (CoRR, 2022)

Demystifying the Base and Novel Performances for Few-shot Class-incremental Learning. - Jaehoon Oh; Se-Young Yun (CoRR, 2022)

Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search. - Taehyeon Kim 001; Heesoo Myeong; Se-Young Yun (CoRR, 2022)

Risk Perspective Exploration in Distributional Reinforcement Learning. - Jihwan Oh; Joonkee Kim; Se-Young Yun (CoRR, 2022)

Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction. - Taehyeon Kim 001; Namgyu Ho; Donggyu Kim; Se-Young Yun (CoRR, 2022)

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions. - Mingyu Kim 002; Jihwan Oh; Yongsik Lee; Joonkee Kim; Seonghwan Kim 004; Song Chong; Se-Young Yun (CoRR, 2022)

Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition. - Taehyeon Kim 001; Shinhwan Kang; Hyeonjeong Shin; Deukryeol Yoon; Seongha Eom; Kijung Shin; Se-Young Yun (CoRR, 2022)

Denoising after Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels. - Sumyeong Ahn; Se-Young Yun (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 (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 (AAAI, 2023)

Large Language Models Are Reasoning Teachers. - Namgyu Ho; Laura Schmid; Se-Young Yun (ACL (1), 2023)

Nearly Optimal Latent State Decoding in Block MDPs. - Yassir Jedra; Junghyun Lee; Alexandre Proutière; 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 (AISTATS, 2023)

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning. - Jihwan Oh; Joonkee Kim; Minchan Jeong; Se-Young Yun (AAMAS, 2023)

Re-Thinking Federated Active Learning Based on Inter-Class Diversity. - Sangmook Kim; Sangmin Bae; Hwanjun Song; Se-Young Yun (CVPR, 2023)

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

Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. - Jongwoo Ko; Seungjoon Park; Minchan Jeong; Sukjin Hong; Euijai Ahn; Du-Seong Chang; Se-Young Yun (EACL (Findings), 2023)

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. - Sangmin Bae; Jongwoo Ko; Hwanjun Song; Se-Young Yun (EMNLP, 2023)

NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models. - Jongwoo Ko; Seungjoon Park; Yujin Kim; Sumyeong Ahn; Du-Seong Chang; Euijai Ahn; Se-Young Yun (EMNLP (Findings), 2023)

Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. - Haeju Lee; Minchan Jeong; Se-Young Yun; Kee-Eung Kim (EMNLP (Findings), 2023)

HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning. - Yongjin Yang; Joonkee Kim; Yujin Kim; Namgyu Ho; James Thorne; Se-Young Yun (EMNLP (Findings), 2023)

CUDA: Curriculum of Data Augmentation for Long-tailed Recognition. - Sumyeong Ahn; Jongwoo Ko; Se-Young Yun (ICLR, 2023)

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

Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification. - Sangmin Bae; June-Woo Kim; Won-Yang Cho; Hyerim Baek; Soyoun Son; Byungjo Lee; Changwan Ha; Kyongpil Tae; Sungnyun Kim; Se-Young Yun (INTERSPEECH, 2023)

Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation. - Kangwook Jang; Sungnyun Kim; Se-Young Yun; Hoirin Kim (INTERSPEECH, 2023)

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning. - Hojoon Lee; Hanseul Cho 002; Hyunseung Kim; Daehoon Gwak; Joonkee Kim; Jaegul Choo; Se-Young Yun; Chulhee Yun (NeurIPS, 2023)

Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint. - Junghyun Lee; Hanseul Cho 002; Se-Young Yun; Chulhee Yun (NeurIPS, 2023)

Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks. - Junghyun Lee; Laura Schmid; Se-Young Yun (OPODIS, 2023)

Meta-Learning Amidst Heterogeneity and Ambiguity. - Kyeongryeol Go; Mingyu Kim 002; Seyoung Yun (IEEE Access, 2023)

The StarCraft Multi-Agent Exploration Challenges: Learning Multi-Stage Tasks and Environmental Factors Without Precise Reward Functions. - Mingyu Kim 002; Jihwan Oh; Yongsik Lee; Joonkee Kim; Seonghwan Kim 004; Song Chong; Seyoung Yun (IEEE Access, 2023)

Communication-Efficient Collaborative Heterogeneous Bandits in Networks. - Junghyun Lee; Laura Schmid; Se-Young Yun (CoRR, 2023)

Enhancing Generalization and Plasticity for Sample Efficient Reinforcement Learning. - Hojoon Lee; Hanseul Cho 002; Hyunseung Kim; Daehoon Gwak; Joonkee Kim; Jaegul Choo; Se-Young Yun; Chulhee Yun (CoRR, 2023)

Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model. - Kaito Ariu; Alexandre Proutière; Se-Young Yun (CoRR, 2023)

FedSoL: Bridging Global Alignment and Local Generality in Federated Learning. - Gihun Lee; Minchan Jeong; Sangmook Kim; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Cross-Modal Retrieval Meets Inference: Improving Zero-Shot Classification with Cross-Modal Retrieval. - Seongha Eom; Namgyu Ho; Jaehoon Oh; Se-Young Yun (CoRR, 2023)

Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; Se-Young Yun (CoRR, 2023)

Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning. - Felix den Breejen; Sangmin Bae; Stephen Cha; Tae-Young Kim; Seounghyun Koh; Se-Young Yun (CoRR, 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 (CoRR, 2023)

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

Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models. - Yongjin Yang; Jongwoo Ko; Se-Young Yun (CoRR, 2023)

Test Score Algorithms for Budgeted Stochastic Utility Maximization. - Dabeen Lee; Milan Vojnovic; Se-Young Yun (INFORMS J. Optim., 2023)

Accelerated MM Algorithms for Inference of Ranking Scores from Comparison Data. - Milan Vojnovic; Se-Young Yun; Kaifang Zhou (Oper. Res., 2023)

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning. - Yongjin Yang; Taehyeon Kim 001; Se-Young Yun (AAAI, 2024)

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

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

Stable Language Model Pre-training by Reducing Embedding Variability. - Woojin Chung; Jiwoo Hong; Na Min An; James Thorne; Se-Young Yun (EMNLP, 2024)

BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; SangMook Kim; Se-Young Yun (EMNLP (Findings), 2024)

Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models. - Yongjin Yang; Jongwoo Ko; Se-Young Yun (EMNLP, 2024)

Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters. - Euiin Yi; Taehyeon Kim 001; Hongseok Jeung; Du-Seong Chang; Se-Young Yun (EMNLP, 2024)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions. - Taehyeon Kim 001; Joonkee Kim; Gihun Lee; Se-Young Yun (ICLR, 2024)

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs. - Mingyu Kim 002; Jun-Seong Kim; Se-Young Yun; Jin-Hwa Kim (ICML, 2024)

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

Fine-tuning Pre-trained Models for Robustness under Noisy Labels. - Sumyeong Ahn; Sihyeon Kim; Jongwoo Ko; Se-Young Yun (IJCAI, 2024)

Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models. - Yujin Kim; Jaehong Yoon; Seonghyeon Ye; Sangmin Bae; Namgyu Ho; Sung Ju Hwang; Se-Young Yun (NAACL-HLT, 2024)

Block Transformer: Global-to-Local Language Modeling for Fast Inference. - Namgyu Ho; Sangmin Bae; Taehyeon Kim 001; 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 (NeurIPS, 2024)

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

An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints. - Jung-Hun Kim; Milan Vojnovic; Se-Young Yun (NeurIPS, 2024)

A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits. - Junghyun Lee; Se-Young Yun; Kwang-Sung Jun (NeurIPS, 2024)

Learning Video Temporal Dynamics With Cross-Modal Attention For Robust Audio-Visual Speech Recognition. - Sungnyun Kim; Kangwook Jang; Sangmin Bae; Hoirin Kim; Se-Young Yun (SLT, 2024)

Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels. - Taehyeon Kim 001; Donggyu Kim; Se-Young Yun (CoRR, 2024)

Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization. - Marc Bartholet; Taehyeon Kim 001; Ami Beuret; Se-Young Yun; Joachim M. Buhmann (CoRR, 2024)

Rotting Infinitely Many-armed Bandits beyond the Worst-case Rotting: An Adaptive Approach. - Jung-Hun Kim; Milan Vojnovic; Se-Young Yun (CoRR, 2024)

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

Why In-Context Learning Transformers are Tabular Data Classifiers. - Felix den Breejen; Sangmin Bae; Stephen Cha; Se-Young Yun (CoRR, 2024)

BAPO: Base-Anchored Preference Optimization for Personalized Alignment in Large Language Models. - Gihun Lee; Minchan Jeong; Yujin Kim; Hojung Jung; Jaehoon Oh; Sangmook Kim; Se-Young Yun (CoRR, 2024)

VACoDe: Visual Augmented Contrastive Decoding. - Sihyeon Kim; Boryeong Cho; Sangmin Bae; Sumyeong Ahn; Se-Young Yun (CoRR, 2024)

Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning. - Jihwan Oh; Sungnyun Kim; Gahee Kim; Sunghwan Kim; Se-Young Yun (CoRR, 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 (CoRR, 2024)

C2: Scalable Auto-Feedback for LLM-based Chart Generation. - Woosung Koh; Jang Han Yoon; Minhyung Lee; Youngjin Song; Jaegwan Cho; Jaehyun Kang; Taehyeon Kim 001; Se-young Yun; Youngjae Yu; Bongshin Lee (CoRR, 2024)

FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels. - Taehyeon Kim 001; Donggyu Kim; Se-Young Yun (Trans. Mach. Learn. Res., 2024)

Non-backtracking Graph Neural Networks. - Seonghyun Park 004; Narae Ryu; Gahee Kim; Dongyeop Woo; Se-Young Yun; Sungsoo Ahn (Trans. Mach. Learn. Res., 2024)

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

Self-Training Elicits Concise Reasoning in Large Language Models. - Tergel Munkhbat; Namgyu Ho; Seo Hyun Kim; Yongjin Yang; Yujin Kim; Se-Young Yun (ACL (Findings), 2025)

MA2E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder. - Sehyeok Kang; Yongsik Lee; Gahee Kim; Song Chong; 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 (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 (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 (ICLR, 2025)

C²: Scalable Auto-Feedback for LLM-based Chart Generation. - Woosung Koh; Jang Han Yoon; Minhyung Lee; Youngjin Song; Jaegwan Cho; Jaehyun Kang; Taehyeon Kim 001; Se-Young Yun; Youngjae Yu; Bongshin Lee (NAACL (Long Papers), 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 (Trans. Mach. Learn. Res., 2025)

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

What is the Alignment Objective of GRPO? - Milan Vojnovic; Se-Young Yun (CoRR, 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 (CoRR, 2025)

Probability-Flow ODE in Infinite-Dimensional Function Spaces. - Kunwoo Na; Junghyun Lee; Se-Young Yun; Sungbin Lim (CoRR, 2025)

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

When Debate Fails: Bias Reinforcement in Large Language Models. - Jihwan Oh; Minchan Jeong; Jongwoo Ko; Se-Young Yun (CoRR, 2025)

Guiding Reasoning in Small Language Models with LLM Assistance. - Yujin Kim; Euiin Yi; Minu Kim; Se-Young Yun; Taehyeon Kim 001 (CoRR, 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 001; Se-Young Yun (CoRR, 2025)

Flex-Judge: Think Once, Judge Anywhere. - Jongwoo Ko; Sungnyun Kim; Sungwoo Cho; Se-Young Yun (CoRR, 2025)

Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness. - Yongjin Yang; Euiin Yi; Jongwoo Ko; Kimin Lee; Zhijing Jin 001; Se-Young Yun (CoRR, 2025)

LLM Agents for Bargaining with Utility-based Feedback. - Jihwan Oh; Murad Aghazada; Se-Young Yun; Taehyeon Kim 001 (CoRR, 2025)

Near-Optimal Clustering in Mixture of Markov Chains. - Junghyun Lee; Yassir Jedra; Alexandre Proutière; Se-Young Yun (CoRR, 2025)

GL-LowPopArt: A Nearly Instance-Wise Minimax-Optimal Estimator for Generalized Low-Rank Trace Regression. - Junghyun Lee; Kyoungseok Jang; Kwang-Sung Jun; Milan Vojnovic; Se-Young Yun (CoRR, 2025)

Automated Skill Discovery for Language Agents through Exploration and Iterative Feedback. - Yongjin Yang; Sinjae Kang; Juyong Lee; Dongjun Lee; Se-Young Yun; Kimin Lee (CoRR, 2025)

Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems. - Minchan Jeong; J. Jon Ryu; Se-Young Yun; Gregory W. Wornell (CoRR, 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 (CoRR, 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 (CoRR, 2025)