Accounting for the Relative Importance of Objects in Image Retrieval. - Sung Ju Hwang; Kristen Grauman (BMVC, 2010)

Sharing features between objects and their attributes. - Sung Ju Hwang; Fei Sha; Kristen Grauman (CVPR, 2011)

Learning a Tree of Metrics with Disjoint Visual Features. - Sung Ju Hwang; Kristen Grauman; Fei Sha (NIPS, 2011)

Context-Based Automatic Local Image Enhancement. - Sung Ju Hwang; Ashish Kapoor; Sing Bing Kang (ECCV (1), 2012)

Semantic Kernel Forests from Multiple Taxonomies. - Sung Ju Hwang; Kristen Grauman; Fei Sha (NIPS, 2012)

Learning the Relative Importance of Objects from Tagged Images for Retrieval and Cross-Modal Search. - Sung Ju Hwang; Kristen Grauman (Int. J. Comput. Vis., 2012)

Reading between the Lines: Object Localization Using Implicit Cues from Image Tags. - Sung Ju Hwang; Kristen Grauman (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Analogy-preserving Semantic Embedding for Visual Object Categorization. - Sung Ju Hwang; Kristen Grauman; Fei Sha (ICML (3), 2013)

A Unified Semantic Embedding: Relating Taxonomies and Attributes. - Sung Ju Hwang; Leonid Sigal (AAAI Spring Symposia, 2015)

Expanding object detector's Horizon: Incremental learning framework for object detection in videos. - Alina Kuznetsova; Sung Ju Hwang; Bodo Rosenhahn; Leonid Sigal (CVPR, 2015)

Hierarchical Maximum-Margin Clustering. - Guang-Tong Zhou; Sung Ju Hwang; Mark Schmidt 001; Leonid Sigal; Greg Mori (CoRR, 2015)

Knowledge Transfer with Interactive Learning of Semantic Relationships. - Jonghyun Choi; Sung Ju Hwang; Leonid Sigal; Larry S. Davis (AAAI, 2016)

Exploiting View-Specific Appearance Similarities Across Classes for Zero-Shot Pose Prediction: A Metric Learning Approach. - Alina Kuznetsova; Sung Ju Hwang; Bodo Rosenhahn; Leonid Sigal (AAAI, 2016)

Taxonomy-Regularized Semantic Deep Convolutional Neural Networks. - Wonjoon Goo; Juyong Kim 002; Gunhee Kim; Sung Ju Hwang (ECCV (2), 2016)

Asymmetric Multi-task Learning based on Task Relatedness and Confidence. - Giwoong Lee; Eunho Yang; Sung Ju Hwang (ICML, 2016)

SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization. - Juyong Kim 002; Yookoon Park; Gunhee Kim; Sung Ju Hwang (ICML, 2017)

Combined Group and Exclusive Sparsity for Deep Neural Networks. - Jaehong Yoon; Sung Ju Hwang (ICML, 2017)

Why Pay More When You Can Pay Less: A Joint Learning Framework for Active Feature Acquisition and Classification. - Hajin Shim; Sung Ju Hwang; Eunho Yang (CoRR, 2017)

DropMax: Adaptive Stochastic Softmax. - Haebeom Lee; Juho Lee 001; Eunho Yang; Sung Ju Hwang (CoRR, 2017)

Lifelong Learning with Dynamically Expandable Networks. - Jaehong Yoon; Eunho Yang; Jeongtae Lee; Sung Ju Hwang (ICLR (Poster), 2018)

Deep Asymmetric Multi-task Feature Learning. - Haebeom Lee; Eunho Yang; Sung Ju Hwang (ICML, 2018)

Dynamic Detection-Tracking Switching. - Andries Bruno; Junhyeon Park; Sung Ju Hwang; Minwoo Kim (ICUFN, 2018)

Uncertainty-Aware Attention for Reliable Interpretation and Prediction. - Jay Heo; Haebeom Lee; Saehoon Kim; Juho Lee 001; Kwang Joon Kim; Eunho Yang; Sung Ju Hwang (NeurIPS, 2018)

DropMax: Adaptive Variational Softmax. - Haebeom Lee; Juho Lee 001; Saehoon Kim; Eunho Yang; Sung Ju Hwang (NeurIPS, 2018)

Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding. - Hajin Shim; Sung Ju Hwang; Eunho Yang (NeurIPS, 2018)

Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout. - Juho Lee 001; Saehoon Kim; Jaehong Yoon; Haebeom Lee; Eunho Yang; Sung Ju Hwang (CoRR, 2018)

Mixed Effect Composite RNN-GP: A Personalized and Reliable Prediction Model for Healthcare. - Ingyo Chung; Saehoon Kim; Juho Lee 001; Sung Ju Hwang; Eunho Yang (CoRR, 2018)

Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective. - Hanze Dong; Yanwei Fu 001; Leonid Sigal; Sung Ju Hwang; Yu-Gang Jiang 001; Xiangyang Xue 001 (CoRR, 2018)

Learning What to Remember: Long-term Episodic Memory Networks for Learning from Streaming Data. - Hyunwoo Jung; Moonsu Han; Minki Kang; Sung Ju Hwang (CoRR, 2018)

Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data. - Moonsu Han; Minki Kang; Hyunwoo Jung; Sung Ju Hwang (ACL (1), 2019)

Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss. - Sangil Jung; Changyong Son; Seohyung Lee; JinWoo Son; Jae-Joon Han; Youngjun Kwak; Sung Ju Hwang; Changkyu Choi (CVPR, 2019)

Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning. - Yanbin Liu; Juho Lee 001; Minseop Park; Saehoon Kim; Eunho Yang; Sung Ju Hwang; Yi Yang 001 (ICLR (Poster), 2019)

Learning What and Where to Transfer. - Yunhun Jang; Hankook Lee; Sung Ju Hwang; Jinwoo Shin (ICML, 2019)

ORACLE: Order Robust Adaptive Continual LEarning. - Jaehong Yoon; Saehoon Kim; Eunho Yang; Sung Ju Hwang (CoRR, 2019)

Meta Dropout: Learning to Perturb Features for Generalization. - Haebeom Lee; Taewook Nam; Eunho Yang; Sung Ju Hwang (CoRR, 2019)

Sparsity Normalization: Stabilizing the Expected Outputs of Deep Networks. - Joonyoung Yi; Juhyuk Lee; Sung Ju Hwang; Eunho Yang (CoRR, 2019)

Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck. - Sungyub Kim; Yongsu Baek; Sung Ju Hwang; Eunho Yang (CoRR, 2019)

Learning to Generalize to Unseen Tasks with Bilevel Optimization. - Hayeon Lee; Donghyun Na; Haebeom Lee; Sung Ju Hwang (CoRR, 2019)

Adversarial Neural Pruning. - Divyam Madaan; Sung Ju Hwang (CoRR, 2019)

Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection. - Byunggill Joe; Sung Ju Hwang; Insik Shin (CoRR, 2019)

Rethinking Data Augmentation: Self-Supervision and Self-Distillation. - Hankook Lee; Sung Ju Hwang; Jinwoo Shin (CoRR, 2019)

Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare. - Ingyo Chung; Saehoon Kim; Juho Lee 001; Kwang Joon Kim; Sung Ju Hwang; Eunho Yang (AAAI, 2020)

Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs. - Dong Bok Lee; Seanie Lee; Woo Tae Jeong; Donghwan Kim; Sung Ju Hwang (ACL, 2020)

Neural Mask Generator: Learning to Generate Adaptive Word Maskings for Language Model Adaptation. - Minki Kang; Moonsu Han; Sung Ju Hwang (EMNLP (1), 2020)

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. - Haebeom Lee; Hayeon Lee; Donghyun Na; Saehoon Kim; Minseop Park; Eunho Yang; Sung Ju Hwang (ICLR, 2020)

Meta Dropout: Learning to Perturb Latent Features for Generalization. - Haebeom Lee; Taewook Nam; Eunho Yang; Sung Ju Hwang (ICLR, 2020)

Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks. - Joonyoung Yi; Juhyuk Lee; Kwang Joon Kim; Sung Ju Hwang; Eunho Yang (ICLR, 2020)

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. - Jaehong Yoon; Saehoon Kim; Eunho Yang; Sung Ju Hwang (ICLR, 2020)

Cost-Effective Interactive Attention Learning with Neural Attention Processes. - Jay Heo; Junhyeon Park; Hyewon Jeong; Kwang Joon Kim; Juho Lee 001; Eunho Yang; Sung Ju Hwang (ICML, 2020)

Self-supervised Label Augmentation via Input Transformations. - Hankook Lee; Sung Ju Hwang; Jinwoo Shin (ICML, 2020)

Adversarial Neural Pruning with Latent Vulnerability Suppression. - Divyam Madaan; Jinwoo Shin; Sung Ju Hwang (ICML, 2020)

Meta Variance Transfer: Learning to Augment from the Others. - Seong-Jin Park; Seungju Han 001; Ji-Won Baek; Insoo Kim; Juhwan Song; Haebeom Lee; Jae-Joon Han; Sung Ju Hwang (ICML, 2020)

Segmenting 2K-Videos at 36.5 FPS with 24.3 GFLOPs: Accurate and Lightweight Realtime Semantic Segmentation Network. - Dokwan Oh; Daehyun Ji; Cheolhun Jang; Yoonsuk Hyun; Hong S. Bae; Sung Ju Hwang (ICRA, 2020)

Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs. - Seong Min Kye; Youngmoon Jung; Haebeom Lee; Sung Ju Hwang; Hoirin Kim (INTERSPEECH, 2020)

Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction. - Jinheon Baek; Dong Bok Lee; Sung Ju Hwang (NeurIPS, 2020)

Time-Reversal Symmetric ODE Network. - In Huh; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (NeurIPS, 2020)

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. - Jaehyung Kim 001; Youngbum Hur; Sejun Park; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (NeurIPS, 2020)

Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning. - Youngsung Kim; Jinwoo Shin; Eunho Yang; Sung Ju Hwang (NeurIPS, 2020)

Adversarial Self-Supervised Contrastive Learning. - Minseon Kim; Jihoon Tack; Sung Ju Hwang (NeurIPS, 2020)

Neural Complexity Measures. - Yoonho Lee 001; Juho Lee 001; Sung Ju Hwang; Eunho Yang; Seungjin Choi (NeurIPS, 2020)

Bootstrapping neural processes. - Juho Lee 001; Yoonho Lee 001; Jungtaek Kim 001; Eunho Yang; Sung Ju Hwang; Yee Whye Teh (NeurIPS, 2020)

Attribution Preservation in Network Compression for Reliable Network Interpretation. - Geondo Park; June Yong Yang; Sung Ju Hwang; Eunho Yang (NeurIPS, 2020)

MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures. - Jeongun Ryu; Jaewoong Shin; Haebeom Lee; Sung Ju Hwang (NeurIPS, 2020)

Transductive Few-shot Learning with Meta-Learned Confidence. - Seong Min Kye; Haebeom Lee; Hoirin Kim; Sung Ju Hwang (CoRR, 2020)

Federated Continual Learning with Adaptive Parameter Communication. - Jaehong Yoon; Wonyong Jeong; Giwoong Lee; Eunho Yang; Sung Ju Hwang (CoRR, 2020)

Federated Semi-Supervised Learning with Inter-Client Consistency. - Wonyong Jeong; Jaehong Yoon; Eunho Yang; Sung Ju Hwang (CoRR, 2020)

Learning to Generate Noise for Robustness against Multiple Perturbations. - Divyam Madaan; Jinwoo Shin; Sung Ju Hwang (CoRR, 2020)

Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning. - Minyoung Song; Jaehong Yoon; Eunho Yang; Sung Ju Hwang (CoRR, 2020)

Stochastic Subset Selection. - Tuan A. Nguyen; Andreis Bruno; Juho Lee 001; Eunho Yang; Sung Ju Hwang (CoRR, 2020)

Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection. - Byunggill Joe; Jihun Hamm; Sung Ju Hwang; Sooel Son; Insik Shin (CoRR, 2020)

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning. - Tuan A. Nguyen; Hyewon Jeong; Eunho Yang; Sung Ju Hwang (AAAI, 2021)

GTA: Graph Truncated Attention for Retrosynthesis. - Seung-Woo Seo; You Young Song; June Yong Yang; Seohui Bae; Hankook Lee; Jinwoo Shin; Sung Ju Hwang; Eunho Yang (AAAI, 2021)

Learning to Perturb Word Embeddings for Out-of-distribution QA. - Seanie Lee; Minki Kang; Juho Lee 001; Sung Ju Hwang (ACL/IJCNLP (1), 2021)

Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss. - Jung Hyun Lee; Jihun Yun; Sung Ju Hwang; Eunho Yang (ICCV, 2021)

Accurate Learning of Graph Representations with Graph Multiset Pooling. - Jinheon Baek; Minki Kang; Sung Ju Hwang (ICLR, 2021)

Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning. - Wonyong Jeong; Jaehong Yoon; Eunho Yang; Sung Ju Hwang (ICLR, 2021)

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets. - Hayeon Lee; Eunyoung Hyung; Sung Ju Hwang (ICLR, 2021)

Contrastive Learning with Adversarial Perturbations for Conditional Text Generation. - Seanie Lee; Dong Bok Lee; Sung Ju Hwang (ICLR, 2021)

Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning. - Dong Bok Lee; Dongchan Min; Seanie Lee; Sung Ju Hwang (ICLR, 2021)

Learning to Sample with Local and Global Contexts in Experience Replay Buffer. - Youngmin Oh; Kimin Lee; Jinwoo Shin; Eunho Yang; Sung Ju Hwang (ICLR, 2021)

FedMix: Approximation of Mixup under Mean Augmented Federated Learning. - Tehrim Yoon; Sumin Shin; Sung Ju Hwang; Eunho Yang (ICLR, 2021)

Learning to Generate Noise for Multi-Attack Robustness. - Divyam Madaan; Jinwoo Shin; Sung Ju Hwang (ICML, 2021)

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. - Dongchan Min; Dong Bok Lee; Eunho Yang; Sung Ju Hwang (ICML, 2021)

Large-Scale Meta-Learning with Continual Trajectory Shifting. - Jaewoong Shin; Haebeom Lee; Boqing Gong; Sung Ju Hwang (ICML, 2021)

Adversarial Purification with Score-based Generative Models. - Jongmin Yoon; Sung Ju Hwang; Juho Lee 001 (ICML, 2021)

Federated Continual Learning with Weighted Inter-client Transfer. - Jaehong Yoon; Wonyong Jeong; Giwoong Lee; Eunho Yang; Sung Ju Hwang (ICML, 2021)

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning. - Hankook Lee; Sungsoo Ahn; Seung-Woo Seo; You Young Song; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (IJCAI, 2021)

Multi-Domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models. - Ho-Gyeong Kim; Min-Joong Lee; Hoshik Lee; Tae Gyoon Kang; Jihyun Lee; Eunho Yang; Sung Ju Hwang (Interspeech, 2021)

Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding. - Andreis Bruno; Jeffrey Willette; Juho Lee 001; Sung Ju Hwang (NeurIPS, 2021)

Task-Adaptive Neural Network Search with Meta-Contrastive Learning. - Wonyong Jeong; Hayeon Lee; Geon Park; Eunyoung Hyung; Jinheon Baek; Sung Ju Hwang (NeurIPS, 2021)

Edge Representation Learning with Hypergraphs. - Jaehyeong Jo; Jinheon Baek; Seul Lee; Dongki Kim; Minki Kang; Sung Ju Hwang (NeurIPS, 2021)

Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning. - Hayeon Lee; Sewoong Lee; Song Chong; Sung Ju Hwang (NeurIPS, 2021)

Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation. - Soojung Yang; Doyeong Hwang; Seul Lee; Seongok Ryu; Sung Ju Hwang (NeurIPS, 2021)

Model-Augmented Q-learning. - Youngmin Oh; Jinwoo Shin; Eunho Yang; Sung Ju Hwang (CoRR, 2021)

Improving Uncertainty Calibration via Prior Augmented Data. - Jeffrey Willette; Juho Lee 001; Sung Ju Hwang (CoRR, 2021)

Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning. - Wonyong Jeong; Hayeon Lee; Gun Park; Eunyoung Hyung; Jinheon Baek; Sung Ju Hwang (CoRR, 2021)

HELP: Hardware-Adaptive Efficient Latency Predictor for NAS via Meta-Learning. - Hayeon Lee; Sewoong Lee; Song Chong; Sung Ju Hwang (CoRR, 2021)

Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic Uncertainty. - Jeffrey Ryan Willette; Haebeom Lee; Juho Lee 001; Sung Ju Hwang (CoRR, 2021)

Rethinking the Representational Continuity: Towards Unsupervised Continual Learning. - Divyam Madaan; Jaehong Yoon; Yuanchun Li; Yunxin Liu 001; Sung Ju Hwang (CoRR, 2021)

DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing. - Taesik Gong; Yewon Kim; Adiba Orzikulova; Yunxin Liu 001; Sung Ju Hwang; Jinwoo Shin; Sung-Ju Lee (CoRR, 2021)

Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing. - Joonhyung Park; June Yong Yang; Jinwoo Shin; Sung Ju Hwang; Eunho Yang (AAAI, 2022)

Consistency Regularization for Adversarial Robustness. - Jihoon Tack; Sihyun Yu; Jongheon Jeong; Minseon Kim; Sung Ju Hwang; Jinwoo Shin (AAAI, 2022)

Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong C. Park (ACL (2), 2022)

MPViT: Multi-Path Vision Transformer for Dense Prediction. - Youngwan Lee; Jonghee Kim; Jeffrey Willette; Sung Ju Hwang (CVPR, 2022)

Object Detection in Aerial Images with Uncertainty-Aware Graph Network. - Jongha Kim; Jinheon Baek; Sung Ju Hwang (ECCV Workshops (4), 2022)

Localization Uncertainty Estimation for Anchor-Free Object Detection. - Youngwan Lee; Joong-Won Hwang; Hyung-Il Kim; Kimin Yun; Yongjin Kwon; Yuseok Bae; Sung Ju Hwang (ECCV Workshops (8), 2022)

BiTAT: Neural Network Binarization with Task-Dependent Aggregated Transformation. - Geon Park; Jaehong Yoon; Haiyang Zhang 001; Xing Zhang 005; Sung Ju Hwang; Yonina C. Eldar (ECCV Workshops (7), 2022)

Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. - Seanie Lee; Haebeom Lee; Juho Lee 001; Sung Ju Hwang (ICLR, 2022)

Online Hyperparameter Meta-Learning with Hypergradient Distillation. - Haebeom Lee; Hayeon Lee; Jaewoong Shin; Eunho Yang; Timothy M. Hospedales; Sung Ju Hwang (ICLR, 2022)

Representational Continuity for Unsupervised Continual Learning. - Divyam Madaan; Jaehong Yoon; Yuanchun Li; Yunxin Liu 001; Sung Ju Hwang (ICLR, 2022)

Skill-based Meta-Reinforcement Learning. - Taewook Nam; Shao-Hua Sun; Karl Pertsch; Sung Ju Hwang; Joseph J. Lim (ICLR, 2022)

Model-augmented Prioritized Experience Replay. - Youngmin Oh; Jinwoo Shin; Eunho Yang; Sung Ju Hwang (ICLR, 2022)

Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty. - Jeffrey Ryan Willette; Hae Beom Lee; Juho Lee 001; Sung Ju Hwang (ICLR, 2022)

Online Coreset Selection for Rehearsal-based Continual Learning. - Jaehong Yoon; Divyam Madaan; Eunho Yang; Sung Ju Hwang (ICLR, 2022)

Set Based Stochastic Subsampling. - Bruno Andreis; Seanie Lee; Tuan A. Nguyen; Juho Lee 001; Eunho Yang; Sung Ju Hwang (ICML, 2022)

Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations. - Jaehyeong Jo; Seul Lee; Sung Ju Hwang (ICML, 2022)

Forget-free Continual Learning with Winning Subnetworks. - Haeyong Kang; Rusty John Lloyd Mina; Sultan Rizky Hikmawan Madjid; Jaehong Yoon; Mark Hasegawa-Johnson; Sung Ju Hwang; Chang D. Yoo (ICML, 2022)

Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization. - Jaehong Yoon; Geon Park; Wonyong Jeong; Sung Ju Hwang (ICML, 2022)

KALA: Knowledge-Augmented Language Model Adaptation. - Minki Kang; Jinheon Baek; Sung Ju Hwang (NAACL-HLT, 2022)

Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching. - Wonyong Jeong; Sung Ju Hwang (NeurIPS, 2022)

Learning to Generate Inversion-Resistant Model Explanations. - Hoyong Jeong; Suyoung Lee; Sung Ju Hwang; Sooel Son (NeurIPS, 2022)

Graph Self-supervised Learning with Accurate Discrepancy Learning. - Dongki Kim; Jinheon Baek; Sung Ju Hwang (NeurIPS, 2022)

Set-based Meta-Interpolation for Few-Task Meta-Learning. - Seanie Lee; Bruno Andreis; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (NeurIPS, 2022)

A Simple Framework for Robust Out-of-Distribution Detection. - Youngbum Hur; Eunho Yang; Sung Ju Hwang (IEEE Access, 2022)

Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching. - Wonyong Jeong; Sung Ju Hwang (CoRR, 2022)

Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation. - Hyunsu Rhee; Dongchan Min; Sunil Hwang; Bruno Andreis; Sung Ju Hwang (CoRR, 2022)

Dataset Condensation with Latent Space Knowledge Factorization and Sharing. - Hae Beom Lee; Dong Bok Lee; Sung Ju Hwang (CoRR, 2022)

StyleTalker: One-shot Style-based Audio-driven Talking Head Video Generation. - Dongchan Min; Minyoung Song; Sung Ju Hwang (CoRR, 2022)

Universal Mini-Batch Consistency for Set Encoding Functions. - Jeffrey Willette; Andreis Bruno; Juho Lee 001; Sung Ju Hwang (CoRR, 2022)

Targeted Adversarial Self-Supervised Learning. - Minseon Kim; Hyeonjeong Ha; Sooel Son; Sung Ju Hwang (CoRR, 2022)

Few-shot Transferable Robust Representation Learning via Bilevel Attacks. - Minseon Kim; Hyeonjeong Ha; Sung Ju Hwang (CoRR, 2022)

Any-speaker Adaptive Text-To-Speech Synthesis with Diffusion Models. - Minki Kang; Dongchan Min; Sung Ju Hwang (CoRR, 2022)

Efficient Video Representation Learning via Masked Video Modeling with Motion-centric Token Selection. - Sunil Hwang; Jaehong Yoon; Youngwan Lee; Sung Ju Hwang (CoRR, 2022)

Learning the Compositional Domains for Generalized Zero-shot Learning. - Hanze Dong; Yanwei Fu 001; Sung Ju Hwang; Leonid Sigal; Xiangyang Xue 001 (Comput. Vis. Image Underst., 2022)

Direct Fact Retrieval from Knowledge Graphs without Entity Linking. - Jinheon Baek; Alham Fikri Aji; Jens Lehmann 001; Sung Ju Hwang (ACL (1), 2023)

Phrase Retrieval for Open Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning. - Soyeong Jeong; Jinheon Baek; Sung Ju Hwang; Jong Park (ACL (Findings), 2023)

Language Detoxification with Attribute-Discriminative Latent Space. - Jin Myung Kwak; Minseon Kim; Sung Ju Hwang (ACL (1), 2023)

A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models. - Hayeon Lee; Rui Hou 007; Jongpil Kim; Davis Liang; Sung Ju Hwang; Alexander Min (ACL (Findings), 2023)

The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation. - Beomyoung Kim; Joonhyun Jeong; Dongyoon Han; Sung Ju Hwang (CVPR, 2023)

Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement. - Soyeong Jeong; Jinheon Baek; Sung Ju Hwang; Jong Park (EACL, 2023)

Knowledge-Augmented Language Model Verification. - Jinheon Baek; Soyeong Jeong; Minki Kang; Jong C. Park; Sung Ju Hwang (EMNLP, 2023)

Test-Time Self-Adaptive Small Language Models for Question Answering. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong Park (EMNLP (Findings), 2023)

Co-training and Co-distillation for Quality Improvement and Compression of Language Models. - Hayeon Lee; Rui Hou 007; Jongpil Kim; Davis Liang; Hongbo Zhang; Sung Ju Hwang; Alexander Min (EMNLP (Findings), 2023)

Grad-StyleSpeech: Any-Speaker Adaptive Text-to-Speech Synthesis with Diffusion Models. - Minki Kang; Dongchan Min; Sung Ju Hwang (ICASSP, 2023)

Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models. - Jaewoong Lee; Sangwon Jang; Jaehyeong Jo; Jaehong Yoon; Yunji Kim; Jin-Hwa Kim; Jung-Woo Ha 001; Sung Ju Hwang (ICCV, 2023)

On the Soft-Subnetwork for Few-Shot Class Incremental Learning. - Haeyong Kang; Jaehong Yoon; Sultan Rizky Hikmawan Madjid; Sung Ju Hwang; Chang D. Yoo (ICLR, 2023)

Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets. - Hayeon Lee; Sohyun An; Minseon Kim; Sung Ju Hwang (ICLR, 2023)

Self-Distillation for Further Pre-training of Transformers. - Seanie Lee; Minki Kang; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi (ICLR, 2023)

Sparse Token Transformer with Attention Back Tracking. - Heejun Lee; Minki Kang; Youngwan Lee; Sung Ju Hwang (ICLR, 2023)

Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. - Dong Bok Lee; Seanie Lee; Kenji Kawaguchi; Yunji Kim; Jihwan Bang; Jung-Woo Ha 001; Sung Ju Hwang (ICLR, 2023)

Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders. - Youngwan Lee; Jeffrey Ryan Willette; Jonghee Kim; Juho Lee 001; Sung Ju Hwang (ICLR, 2023)

Personalized Subgraph Federated Learning. - Jinheon Baek; Wonyong Jeong; Jiongdao Jin; Jaehong Yoon; Sung Ju Hwang (ICML, 2023)

Margin-based Neural Network Watermarking. - Byungjoo Kim; Suyoung Lee; Seanie Lee; Sooel Son; Sung Ju Hwang (ICML, 2023)

Exploring Chemical Space with Score-based Out-of-distribution Generation. - Seul Lee; Jaehyeong Jo; Sung Ju Hwang (ICML, 2023)

Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. - Jeffrey Willette; Seanie Lee; Bruno Andreis; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (ICML, 2023)

Continual Learners are Incremental Model Generalizers. - Jaehong Yoon; Sung Ju Hwang; Yue Cao (ICML, 2023)

ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models. - Minki Kang; Wooseok Han; Sung Ju Hwang; Eunho Yang (INTERSPEECH, 2023)

Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations. - Hyeonjeong Ha; Minseon Kim; Sung Ju Hwang (NeurIPS, 2023)

STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection. - Sujin Jang; Dae Ung Jo; Sung Ju Hwang; Dongwook Lee; Daehyun Ji (NeurIPS, 2023)

Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. - Minki Kang; Seanie Lee; Jinheon Baek; Kenji Kawaguchi; Sung Ju Hwang (NeurIPS, 2023)

Effective Targeted Attacks for Adversarial Self-Supervised Learning. - Minseon Kim; Hyeonjeong Ha; Sooel Son; Sung Ju Hwang (NeurIPS, 2023)

Rethinking the Entropy of Instance in Adversarial Training. - Minseon Kim; Jihoon Tack; Jinwoo Shin; Sung Ju Hwang (SaTML, 2023)

Deep Self-Supervised Diversity Promoting Learning on Hierarchical Hyperspheres for Regularization. - Youngsung Kim; Yoonsuk Hyun; Jae-Joon Han; Eunho Yang; Sung Ju Hwang; Jinwoo Shin (IEEE Access, 2023)

Graph Generation with Destination-Driven Diffusion Mixture. - Jaehyeong Jo; Dongki Kim; Sung Ju Hwang (CoRR, 2023)

Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement. - Soyeong Jeong; Jinheon Baek; Sung Ju Hwang; Jong C. Park (CoRR, 2023)

Forget-free Continual Learning with Soft-Winning SubNetworks. - Haeyong Kang; Jaehong Yoon; Sultan Rizky Hikmawan Madjid; Sung Ju Hwang; Chang D. Yoo (CoRR, 2023)

Set-based Neural Network Encoding. - Bruno Andreis; Bedionita Soro; Sung Ju Hwang (CoRR, 2023)

DiffusionNAG: Task-guided Neural Architecture Generation with Diffusion Models. - Sohyun An; Hayeon Lee; Jaehyeong Jo; Seanie Lee; Sung Ju Hwang (CoRR, 2023)

Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation. - Minki Kang; Jin Myung Kwak; Jinheon Baek; Sung Ju Hwang (CoRR, 2023)

Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization. - Doyeon Kim; Eunji Ko; Hyunsu Kim; Yunji Kim; Junho Kim; Dongchan Min; Junmo Kim 002; Sung Ju Hwang (CoRR, 2023)

Phrase Retrieval for Open-Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning. - Soyeong Jeong; Jinheon Baek; Sung Ju Hwang; Jong C. Park (CoRR, 2023)

Progressive Neural Representation for Sequential Video Compilation. - Haeyong Kang; Dahyun Kim 002; Jaehong Yoon; Sung Ju Hwang; Chang D. Yoo (CoRR, 2023)

Drug Discovery with Dynamic Goal-aware Fragments. - Seul Lee; Seanie Lee; Sung Ju Hwang (CoRR, 2023)

STELLA: Continual Audio-Video Pre-training with Spatio-Temporal Localized Alignment. - Jaewoo Lee; Jaehong Yoon; Wonjae Kim; Yunji Kim; Sung Ju Hwang (CoRR, 2023)

Test-Time Self-Adaptive Small Language Models for Question Answering. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong C. Park (CoRR, 2023)

Context-dependent Instruction Tuning for Dialogue Response Generation. - Jin Myung Kwak; Minseon Kim; Sung Ju Hwang (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)

KOALA: Self-Attention Matters in Knowledge Distillation of Latent Diffusion Models for Memory-Efficient and Fast Image Synthesis. - Youngwan Lee; Kwanyong Park; Yoorhim Cho; Yong-Ju Lee; Sung Ju Hwang (CoRR, 2023)

LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers. - Taewook Nam; Juyong Lee; Jesse Zhang; Sung Ju Hwang; Joseph J. Lim; Karl Pertsch (CoRR, 2023)

DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing. - Taesik Gong; Yewon Kim; Adiba Orzikulova; Yunxin Liu 001; Sung Ju Hwang; Jinwoo Shin; Sung-Ju Lee (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2023)

LG AI Research & KAIST at EHRSQL 2024: Self-Training Large Language Models with Pseudo-Labeled Unanswerable Questions for a Reliable Text-to-SQL System on EHRs. - Yongrae Jo; Seongyun Lee; Minju Seo; Sung Ju Hwang; Moontae Lee (ClinicalNLP@NAACL, 2024)

ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning. - Beomyoung Kim; Joonsang Yu; Sung Ju Hwang (CVPR, 2024)

Concept-skill Transferability-based Data Selection for Large Vision-Language Models. - Jaewoo Lee; Boyang Li; Sung Ju Hwang (EMNLP, 2024)

Rethinking Code Refinement: Learning to Judge Code Efficiency. - Minju Seo; Jinheon Baek; Sung Ju Hwang (EMNLP (Findings), 2024)

DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models. - Sohyun An; Hayeon Lee; Jaehyeong Jo; Seanie Lee; Sung Ju Hwang (ICLR, 2024)

Progressive Fourier Neural Representation for Sequential Video Compilation. - Haeyong Kang; Jaehong Yoon; Dahyun Kim 002; Sung Ju Hwang; Chang D. Yoo (ICLR, 2024)

SEA: Sparse Linear Attention with Estimated Attention Mask. - Heejun Lee; Jina Kim; Jeffrey Willette; Sung Ju Hwang (ICLR, 2024)

Self-Supervised Dataset Distillation for Transfer Learning. - Dong Bok Lee; Seanie Lee; Joonho Ko; Kenji Kawaguchi; Juho Lee 001; Sung Ju Hwang (ICLR, 2024)

EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens. - Sunil Hwang; Jaehong Yoon; Youngwan Lee; Sung Ju Hwang (ICML, 2024)

Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes. - Jaehyeong Jo; Sung Ju Hwang (ICML, 2024)

Graph Generation with Diffusion Mixture. - Jaehyeong Jo; Dongki Kim; Sung Ju Hwang (ICML, 2024)

Drug Discovery with Dynamic Goal-aware Fragments. - Seul Lee; Seanie Lee; Kenji Kawaguchi; Sung Ju Hwang (ICML, 2024)

BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation. - Daeun Lee; Jaehong Yoon; Sung Ju Hwang (ICML, 2024)

STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment. - Jaewoo Lee; Jaehong Yoon; Wonjae Kim; Yunji Kim; Sung Ju Hwang (ICML, 2024)

One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. - Ruochen Wang; Sohyun An; Minhao Cheng; Tianyi Zhou 001; Sung Ju Hwang; Cho-Jui Hsieh (ICML, 2024)

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong Park (NAACL-HLT, 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)

Set-based Neural Network Encoding Without Weight Tying. - Bruno Andreis; Bedionita Soro; Philip H. S. Torr; Sung Ju Hwang (NeurIPS, 2024)

Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models. - Sangwon Jang; Jaehyeong Jo; Kimin Lee; Sung Ju Hwang (NeurIPS, 2024)

Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models. - Minki Kang; Sung Ju Hwang; Gibbeum Lee; Jaewoong Cho (NeurIPS, 2024)

KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis. - Youngwan Lee; Kwanyong Park; Yoorhim Cho; Yong-Ju Lee; Sung Ju Hwang (NeurIPS, 2024)

Targeted Model Inversion: Distilling style encoded in predictions. - Hoyong Jeong; Kiwon Chung; Sung Ju Hwang; Sooel Son (Comput. Secur., 2024)

Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks. - Minju Seo; Jinheon Baek; James Thorne; Sung Ju Hwang (CoRR, 2024)

Diffusion-based Neural Network Weights Generation. - Bedionita Soro; Bruno Andreis; Hayeon Lee; Song Chong; Frank Hutter; Sung Ju Hwang (CoRR, 2024)

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong C. Park (CoRR, 2024)

Rethinking Saliency-Guided Weakly-Supervised Semantic Segmentation. - Beomyoung Kim; Donghyun Kim; Sung Ju Hwang (CoRR, 2024)

Towards Label-Efficient Human Matting: A Simple Baseline for Weakly Semi-Supervised Trimap-Free Human Matting. - Beomyoung Kim; Myeong-Yeon Yi; Joonsang Yu; Young Joon Yoo; Sung Ju Hwang (CoRR, 2024)

Automatic Jailbreaking of the Text-to-Image Generative AI Systems. - Minseon Kim; Hyomin Lee; Boqing Gong; Huishuai Zhang; Sung Ju Hwang (CoRR, 2024)

Cost-Sensitive Multi-Fidelity Bayesian Optimization with Transfer of Learning Curve Extrapolation. - Dong Bok Lee; Aoxuan Silvia Zhang; Byungjoo Kim; Junhyeon Park; Juho Lee 001; Sung Ju Hwang; Hae Beom Lee (CoRR, 2024)

Visualizing the loss landscape of Self-supervised Vision Transformer. - Youngwan Lee; Jeffrey Ryan Willette; Jonghee Kim; Sung Ju Hwang (CoRR, 2024)

HiP Attention: Sparse Sub-Quadratic Attention with Hierarchical Attention Pruning. - Heejun Lee; Geon Park; Youngwan Lee; Jina Kim; Wonyoung Jeong; Myeongjae Jeon; Sung Ju Hwang (CoRR, 2024)

Database-Augmented Query Representation for Information Retrieval. - Soyeong Jeong; Jinheon Baek; Sukmin Cho; Sung Ju Hwang; Jong C. Park (CoRR, 2024)

Training-Free Exponential Extension of Sliding Window Context with Cascading KV Cache. - Jeffrey Willette; Heejun Lee; Youngwan Lee; Myeongjae Jeon; Sung Ju Hwang (CoRR, 2024)

Optimizing Query Generation for Enhanced Document Retrieval in RAG. - Hamin Koo; Minseon Kim; Sung Ju Hwang (CoRR, 2024)

Unified Multi-Modal Interleaved Document Representation for Information Retrieval. - Jaewoo Lee; Joonho Ko; Jinheon Baek; Soyeong Jeong; Sung Ju Hwang (CoRR, 2024)

AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML. - Patara Trirat; Wonyong Jeong; Sung Ju Hwang (CoRR, 2024)

VideoRAG: Retrieval-Augmented Generation over Video Corpus. - Soyeong Jeong; Kangsan Kim; Jinheon Baek; Sung Ju Hwang (ACL (Findings), 2025)

SafeRoute: Adaptive Model Selection for Efficient and Accurate Safety Guardrails in Large Language Models. - Seanie Lee; Dong Bok Lee; Dominik Wagner 002; Minki Kang; Haebin Seong; Tobias Bocklet; Juho Lee 001; Sung Ju Hwang (ACL (Findings), 2025)

Efficient Long Context Language Model Retrieval with Compression. - Minju Seo; Jinheon Baek; Seongyun Lee; Sung Ju Hwang (ACL (1), 2025)

Silent Branding Attack: Trigger-free Data Poisoning Attack on Text-to-Image Diffusion Models. - Sangwon Jang; June Suk Choi; Jaehyeong Jo; Kimin Lee; Sung Ju Hwang (CVPR, 2025)

VideoICL: Confidence-based Iterative In-context Learning for Out-of-Distribution Video Understanding. - Kangsan Kim; Geon Park; Youngwan Lee; Woongyeong Yeo; Sung Ju Hwang (CVPR, 2025)

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. - Seanie Lee; Minsu Kim 004; Lynn Cherif; David Dobre; Juho Lee 001; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (ICLR, 2025)

A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention. - Heejun Lee; Geon Park; Youngwan Lee; Jaduk Suh; Jina Kim; Wonyong Jeong; Bumsik Kim; Hyemin Lee; Myeongjae Jeon; Sung Ju Hwang (ICLR, 2025)

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. - Seanie Lee; Haebin Seong; Dong Bok Lee; Minki Kang; Xiaoyin Chen; Dominik Wagner 002; Yoshua Bengio; Juho Lee 001; Sung Ju Hwang (ICLR, 2025)

Diffusion-based Neural Network Weights Generation. - Bedionita Soro; Bruno Andreis; Hayeon Lee; Wonyong Jeong; Song Chong; Frank Hutter; Sung Ju Hwang (ICLR, 2025)

Training Free Exponential Context Extension via Cascading KV Cache. - Jeffrey Willette; Heejun Lee; Youngwan Lee; Myeongjae Jeon; Sung Ju Hwang (ICLR, 2025)

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models. - Jinheon Baek; Sujay Kumar Jauhar; Silviu Cucerzan; Sung Ju Hwang (NAACL (Long Papers), 2025)

Real-time Verification and Refinement of Language Model Text Generation. - Joonho Ko; Jinheon Baek; Sung Ju Hwang (CoRR, 2025)

InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU. - Heejun Lee; Geon Park; Jaduk Suh; Sung Ju Hwang (CoRR, 2025)

Continuous Diffusion Model for Language Modeling. - Jaehyeong Jo; Sung Ju Hwang (CoRR, 2025)

Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model. - Dongki Kim; Wonbin Lee; Sung Ju Hwang (CoRR, 2025)

Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching. - Simon A. Aytes; Jinheon Baek; Sung Ju Hwang (CoRR, 2025)

FedRand: Enhancing Privacy in Federated Learning with Randomized LoRA Subparameter Updates. - Sangwoo Park; Seanie Lee; Byungjoo Kim; Sung Ju Hwang (CoRR, 2025)

Continual Learning: Forget-Free Winning Subnetworks for Video Representations. - Haeyong Kang; Jaehong Yoon; Sung Ju Hwang; Chang D. Yoo (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Instruction-Guided Autoregressive Neural Network Parameter Generation. - Bedionita Soro; Bruno Andreis; Song Chong; Sung Ju Hwang (CoRR, 2025)

Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning. - Minju Seo; Jinheon Baek; Seongyun Lee; Sung Ju Hwang (CoRR, 2025)

Enhancing Variational Autoencoders with Smooth Robust Latent Encoding. - Hyomin Lee; Minseon Kim; Sangwon Jang; Jongheon Jeong; Sung Ju Hwang (CoRR, 2025)

UniversalRAG: Retrieval-Augmented Generation over Multiple Corpora with Diverse Modalities and Granularities. - Woongyeong Yeo; Kangsan Kim; Soyeong Jeong; Jinheon Baek; Sung Ju Hwang (CoRR, 2025)

Simple Semi-supervised Knowledge Distillation from Vision-Language Models via Dual-Head Optimization. - Seongjae Kang; Dong Bok Lee; Hyungjoon Jang; Sung Ju Hwang (CoRR, 2025)

System Prompt Optimization with Meta-Learning. - Yumin Choi; Jinheon Baek; Sung Ju Hwang (CoRR, 2025)

Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction. - Jeffrey Willette; Heejun Lee; Sung Ju Hwang (CoRR, 2025)

FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA. - Seanie Lee; Sangwoo Park; Dong Bok Lee; Dominik Wagner 002; Haebin Seong; Tobias Bocklet; Juho Lee 001; Sung Ju Hwang (CoRR, 2025)

Distilling LLM Agent into Small Models with Retrieval and Code Tools. - Minki Kang; Jongwon Jeong; Seanie Lee; Jaewoong Cho; Sung Ju Hwang (CoRR, 2025)

Agentic Predictor: Performance Prediction for Agentic Workflows via Multi-View Encoding. - Patara Trirat; Wonyong Jeong; Sung Ju Hwang (CoRR, 2025)

Bayesian Neural Scaling Laws Extrapolation with Prior-Fitted Networks. - Dongwoo Lee; Dong Bok Lee; Steven Adriaensen; Juho Lee; Sung Ju Hwang; Frank Hutter; Seon Joo Kim; Hae Beom Lee (CoRR, 2025)

PCoreSet: Effective Active Learning through Knowledge Distillation from Vision-Language Models. - Seongjae Kang; Dong Bok Lee; Hyungjoon Jang; Dongseop Kim; Sung Ju Hwang (CoRR, 2025)

HoliSafe: Holistic Safety Benchmarking and Modeling with Safety Meta Token for Vision-Language Model. - Youngwan Lee; Kangsan Kim; Kwanyong Park; Ilcahe Jung; Soojin Jang; Seanie Lee; Yong-Ju Lee; Sung Ju Hwang (CoRR, 2025)

Frame Guidance: Training-Free Guidance for Frame-Level Control in Video Diffusion Models. - Sangwon Jang; Taekyung Ki; Jaehyeong Jo; Jaehong Yoon; Soo Ye Kim; Zhe Lin; Sung Ju Hwang (CoRR, 2025)

Robust Molecular Property Prediction via Densifying Scarce Labeled Data. - Jina Kim; Jeffrey Willette; Bruno Andreis; Sung Ju Hwang (CoRR, 2025)

PRISM: Fine-Grained Paper-to-Paper Retrieval with Multi-Aspect-Aware Query Optimization. - Sangwoo Park; Jinheon Baek; Soyeong Jeong; Sung Ju Hwang (CoRR, 2025)