| 2026 | ACL | When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs. | Soyeong Jeong, Taehee Jung, Sung Ju Hwang, Joo-Kyung Kim, Dongyeop Kang |
| 2026 | ACL | UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities. | Woongyeong Yeo, Kangsan Kim, Soyeong Jeong, Jinheon Baek, Sung Ju Hwang |
| 2026 | EACL | Unified Multimodal Interleaved Document Representation for Retrieval. | Jaewoo Lee, Joonho Ko, Jinheon Baek, Soyeong Jeong, Sung Ju Hwang |
| 2025 | ACL | VideoRAG: Retrieval-Augmented Generation over Video Corpus. | Soyeong Jeong, Kangsan Kim, Jinheon Baek, Sung Ju Hwang |
| 2025 | ACL | SafeRoute: Adaptive Model Selection for Efficient and Accurate Safety Guardrails in Large Language Models. | Seanie Lee, Dong Bok Lee, Dominik Wagner, Minki Kang, Haebin Seong, Tobias Bocklet, Juho Lee, Sung Ju Hwang |
| 2025 | ACL | Efficient Long Context Language Model Retrieval with Compression. | Minju Seo, Jinheon Baek, Seongyun Lee, Sung Ju Hwang |
| 2025 | CVPR | 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 |
| 2025 | CVPR | VideoICL: Confidence-based Iterative In-context Learning for Out-of-Distribution Video Understanding. | Kangsan Kim, Geon Park, Youngwan Lee, Woongyeong Yeo, Sung Ju Hwang |
| 2025 | EMNLP | Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching. | Simon A. Aytes, Jinheon Baek, Sung Ju Hwang |
| 2025 | EMNLP | Database-Augmented Query Representation for Information Retrieval. | Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park |
| 2025 | EMNLP | Efficient Real-time Refinement of Language Model Text Generation. | Joonho Ko, Jinheon Baek, Sung Ju Hwang |
| 2025 | ICLR | Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. | Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain |
| 2025 | ICLR | 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 |
| 2025 | ICLR | HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. | Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang |
| 2025 | ICLR | Diffusion-based Neural Network Weights Generation. | Bedionita Soro, Bruno Andreis, Hayeon Lee, Wonyong Jeong, Song Chong, Frank Hutter, Sung Ju Hwang |
| 2025 | ICLR | Training Free Exponential Context Extension via Cascading KV Cache. | Jeffrey Willette, Heejun Lee, Youngwan Lee, Myeongjae Jeon, Sung Ju Hwang |
| 2025 | ICML | Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks. | Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee |
| 2025 | ICML | AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML. | Patara Trirat, Wonyong Jeong, Sung Ju Hwang |
| 2025 | NAACL | ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models. | Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, Sung Ju Hwang |
| 2024 | CVPR | ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning. | Beomyoung Kim, Joonsang Yu, Sung Ju Hwang |
| 2024 | EMNLP | Concept-skill Transferability-based Data Selection for Large Vision-Language Models. | Jaewoo Lee, Boyang Li, Sung Ju Hwang |
| 2024 | EMNLP | Rethinking Code Refinement: Learning to Judge Code Efficiency. | Minju Seo, Jinheon Baek, Sung Ju Hwang |
| 2024 | ICLR | DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models. | Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang |
| 2024 | ICLR | Progressive Fourier Neural Representation for Sequential Video Compilation. | Haeyong Kang, Jaehong Yoon, Dahyun Kim, Sung Ju Hwang, Chang D. Yoo |
| 2024 | ICLR | SEA: Sparse Linear Attention with Estimated Attention Mask. | Heejun Lee, Jina Kim, Jeffrey Willette, Sung Ju Hwang |
| 2024 | ICLR | Self-Supervised Dataset Distillation for Transfer Learning. | Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang |
| 2024 | ICML | EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens. | Sunil Hwang, Jaehong Yoon, Youngwan Lee, Sung Ju Hwang |
| 2024 | ICML | Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes. | Jaehyeong Jo, Sung Ju Hwang |
| 2024 | ICML | Graph Generation with Diffusion Mixture. | Jaehyeong Jo, Dongki Kim, Sung Ju Hwang |
| 2024 | ICML | Drug Discovery with Dynamic Goal-aware Fragments. | Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang |
| 2024 | ICML | BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation. | Daeun Lee, Jaehong Yoon, Sung Ju Hwang |
| 2024 | ICML | STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment. | Jaewoo Lee, Jaehong Yoon, Wonjae Kim, Yunji Kim, Sung Ju Hwang |
| 2024 | ICML | One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. | Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh |
| 2024 | NAACL | Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity. | Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong Park |
| 2024 | NAACL | 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 |
| 2023 | ACL | Direct Fact Retrieval from Knowledge Graphs without Entity Linking. | Jinheon Baek, Alham Fikri Aji, Jens Lehmann, Sung Ju Hwang |
| 2023 | ACL | Phrase Retrieval for Open Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning. | Soyeong Jeong, Jinheon Baek, Sung Ju Hwang, Jong Park |
| 2023 | ACL | Language Detoxification with Attribute-Discriminative Latent Space. | Jin Myung Kwak, Minseon Kim, Sung Ju Hwang |
| 2023 | ACL | A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models. | Hayeon Lee, Rui Hou, Jongpil Kim, Davis Liang, Sung Ju Hwang, Alexander Min |
| 2023 | CVPR | 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 |
| 2023 | EACL | Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement. | Soyeong Jeong, Jinheon Baek, Sung Ju Hwang, Jong Park |
| 2023 | EMNLP | Knowledge-Augmented Language Model Verification. | Jinheon Baek, Soyeong Jeong, Minki Kang, Jong C. Park, Sung Ju Hwang |
| 2023 | EMNLP | Test-Time Self-Adaptive Small Language Models for Question Answering. | Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong Park |
| 2023 | EMNLP | Co-training and Co-distillation for Quality Improvement and Compression of Language Models. | Hayeon Lee, Rui Hou, Jongpil Kim, Davis Liang, Hongbo Zhang, Sung Ju Hwang, Alexander Min |
| 2023 | ICASSP | Grad-StyleSpeech: Any-Speaker Adaptive Text-to-Speech Synthesis with Diffusion Models. | Minki Kang, Dongchan Min, Sung Ju Hwang |
| 2023 | ICCV | 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, Sung Ju Hwang |
| 2023 | ICLR | On the Soft-Subnetwork for Few-Shot Class Incremental Learning. | Haeyong Kang, Jaehong Yoon, Sultan Rizky Hikmawan Madjid, Sung Ju Hwang, Chang D. Yoo |
| 2023 | ICLR | Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets. | Hayeon Lee, Sohyun An, Minseon Kim, Sung Ju Hwang |
| 2023 | ICLR | Self-Distillation for Further Pre-training of Transformers. | Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi |
| 2023 | ICLR | Sparse Token Transformer with Attention Back Tracking. | Heejun Lee, Minki Kang, Youngwan Lee, Sung Ju Hwang |
| 2023 | ICLR | Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. | Dong Bok Lee, Seanie Lee, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang |
| 2023 | ICLR | Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders. | Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim, Juho Lee, Sung Ju Hwang |
| 2023 | ICML | Personalized Subgraph Federated Learning. | Jinheon Baek, Wonyong Jeong, Jiongdao Jin, Jaehong Yoon, Sung Ju Hwang |
| 2023 | ICML | Margin-based Neural Network Watermarking. | Byungjoo Kim, Suyoung Lee, Seanie Lee, Sooel Son, Sung Ju Hwang |
| 2023 | ICML | Exploring Chemical Space with Score-based Out-of-distribution Generation. | Seul Lee, Jaehyeong Jo, Sung Ju Hwang |
| 2023 | ICML | Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. | Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang |
| 2023 | ICML | Continual Learners are Incremental Model Generalizers. | Jaehong Yoon, Sung Ju Hwang, Yue Cao |
| 2023 | Interspeech | 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 |
| 2022 | AAAI | Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing. | Joonhyung Park, June Yong Yang, Jinwoo Shin, Sung Ju Hwang, Eunho Yang |
| 2022 | AAAI | Consistency Regularization for Adversarial Robustness. | Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, Jinwoo Shin |
| 2022 | ACL | Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation. | Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park |
| 2022 | CVPR | MPViT: Multi-Path Vision Transformer for Dense Prediction. | Youngwan Lee, Jonghee Kim, Jeffrey Willette, Sung Ju Hwang |
| 2022 | ECCV | Object Detection in Aerial Images with Uncertainty-Aware Graph Network. | Jongha Kim, Jinheon Baek, Sung Ju Hwang |
| 2022 | ECCV | 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 |
| 2022 | ECCV | BiTAT: Neural Network Binarization with Task-Dependent Aggregated Transformation. | Geon Park, Jaehong Yoon, Haiyang Zhang, Xing Zhang, Sung Ju Hwang, Yonina C. Eldar |
| 2022 | ICLR | Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. | Seanie Lee, Haebeom Lee, Juho Lee, Sung Ju Hwang |
| 2022 | ICLR | Online Hyperparameter Meta-Learning with Hypergradient Distillation. | Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang |
| 2022 | ICLR | Representational Continuity for Unsupervised Continual Learning. | Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang |
| 2022 | ICLR | Skill-based Meta-Reinforcement Learning. | Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J. Lim |
| 2022 | ICLR | Model-augmented Prioritized Experience Replay. | Youngmin Oh, Jinwoo Shin, Eunho Yang, Sung Ju Hwang |
| 2022 | ICLR | Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty. | Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang |
| 2022 | ICLR | Online Coreset Selection for Rehearsal-based Continual Learning. | Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang |
| 2022 | ICML | Set Based Stochastic Subsampling. | Bruno Andreis, Seanie Lee, Tuan A. Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang |
| 2022 | ICML | Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations. | Jaehyeong Jo, Seul Lee, Sung Ju Hwang |
| 2022 | ICML | 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 |
| 2022 | ICML | Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization. | Jaehong Yoon, Geon Park, Wonyong Jeong, Sung Ju Hwang |
| 2022 | NAACL | KALA: Knowledge-Augmented Language Model Adaptation. | Minki Kang, Jinheon Baek, Sung Ju Hwang |
| 2021 | AAAI | Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning. | Tuan A. Nguyen, Hyewon Jeong, Eunho Yang, Sung Ju Hwang |
| 2021 | AAAI | 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 |
| 2021 | ACL | Learning to Perturb Word Embeddings for Out-of-distribution QA. | Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang |
| 2021 | ICCV | Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss. | Jung Hyun Lee, Jihun Yun, Sung Ju Hwang, Eunho Yang |
| 2021 | ICLR | Accurate Learning of Graph Representations with Graph Multiset Pooling. | Jinheon Baek, Minki Kang, Sung Ju Hwang |
| 2021 | ICLR | Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning. | Wonyong Jeong, Jaehong Yoon, Eunho Yang, Sung Ju Hwang |
| 2021 | ICLR | Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets. | Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang |
| 2021 | ICLR | Contrastive Learning with Adversarial Perturbations for Conditional Text Generation. | Seanie Lee, Dong Bok Lee, Sung Ju Hwang |
| 2021 | ICLR | Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning. | Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang |
| 2021 | ICLR | Learning to Sample with Local and Global Contexts in Experience Replay Buffer. | Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang |
| 2021 | ICLR | FedMix: Approximation of Mixup under Mean Augmented Federated Learning. | Tehrim Yoon, Sumin Shin, Sung Ju Hwang, Eunho Yang |
| 2021 | ICML | Learning to Generate Noise for Multi-Attack Robustness. | Divyam Madaan, Jinwoo Shin, Sung Ju Hwang |
| 2021 | ICML | Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. | Dongchan Min, Dong Bok Lee, Eunho Yang, Sung Ju Hwang |
| 2021 | ICML | Large-Scale Meta-Learning with Continual Trajectory Shifting. | Jaewoong Shin, Haebeom Lee, Boqing Gong, Sung Ju Hwang |
| 2021 | ICML | Adversarial Purification with Score-based Generative Models. | Jongmin Yoon, Sung Ju Hwang, Juho Lee |
| 2021 | ICML | Federated Continual Learning with Weighted Inter-client Transfer. | Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang |
| 2021 | IJCAI | 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 |
| 2021 | Interspeech | 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 |
| 2020 | AAAI | Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare. | Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang |
| 2020 | ACL | 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 |
| 2020 | EMNLP | Neural Mask Generator: Learning to Generate Adaptive Word Maskings for Language Model Adaptation. | Minki Kang, Moonsu Han, Sung Ju Hwang |
| 2020 | ICLR | 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 |
| 2020 | ICLR | Meta Dropout: Learning to Perturb Latent Features for Generalization. | Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang |
| 2020 | ICLR | 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 |
| 2020 | ICLR | Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. | Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang |
| 2020 | ICML | Cost-Effective Interactive Attention Learning with Neural Attention Processes. | Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang |
| 2020 | ICML | Self-supervised Label Augmentation via Input Transformations. | Hankook Lee, Sung Ju Hwang, Jinwoo Shin |
| 2020 | ICML | Adversarial Neural Pruning with Latent Vulnerability Suppression. | Divyam Madaan, Jinwoo Shin, Sung Ju Hwang |
| 2020 | ICML | Meta Variance Transfer: Learning to Augment from the Others. | Seong-Jin Park, Seungju Han, Ji-Won Baek, Insoo Kim, Juhwan Song, Haebeom Lee, Jae-Joon Han, Sung Ju Hwang |
| 2020 | ICRA | 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 |
| 2020 | Interspeech | Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs. | Seong Min Kye, Youngmoon Jung, Haebeom Lee, Sung Ju Hwang, Hoirin Kim |
| 2019 | ACL | Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data. | Moonsu Han, Minki Kang, Hyunwoo Jung, Sung Ju Hwang |
| 2019 | CVPR | 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 |
| 2019 | ICLR | Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning. | Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang |
| 2019 | ICML | Learning What and Where to Transfer. | Yunhun Jang, Hankook Lee, Sung Ju Hwang, Jinwoo Shin |
| 2018 | ICLR | Lifelong Learning with Dynamically Expandable Networks. | Jaehong Yoon, Eunho Yang, Jeongtae Lee, Sung Ju Hwang |
| 2018 | ICML | Deep Asymmetric Multi-task Feature Learning. | Haebeom Lee, Eunho Yang, Sung Ju Hwang |
| 2017 | ICML | SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization. | Juyong Kim, Yookoon Park, Gunhee Kim, Sung Ju Hwang |
| 2017 | ICML | Combined Group and Exclusive Sparsity for Deep Neural Networks. | Jaehong Yoon, Sung Ju Hwang |
| 2016 | AAAI | Knowledge Transfer with Interactive Learning of Semantic Relationships. | Jonghyun Choi, Sung Ju Hwang, Leonid Sigal, Larry S. Davis |
| 2016 | AAAI | 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 |
| 2016 | ECCV | Taxonomy-Regularized Semantic Deep Convolutional Neural Networks. | Wonjoon Goo, Juyong Kim, Gunhee Kim, Sung Ju Hwang |
| 2016 | ICML | Asymmetric Multi-task Learning based on Task Relatedness and Confidence. | Giwoong Lee, Eunho Yang, Sung Ju Hwang |
| 2015 | CVPR | Expanding object detector's Horizon: Incremental learning framework for object detection in videos. | Alina Kuznetsova, Sung Ju Hwang, Bodo Rosenhahn, Leonid Sigal |
| 2013 | ICML | Analogy-preserving Semantic Embedding for Visual Object Categorization. | Sung Ju Hwang, Kristen Grauman, Fei Sha |
| 2012 | ECCV | Context-Based Automatic Local Image Enhancement. | Sung Ju Hwang, Ashish Kapoor, Sing Bing Kang |
| 2011 | CVPR | Sharing features between objects and their attributes. | Sung Ju Hwang, Fei Sha, Kristen Grauman |
| 2010 | BMVC | Accounting for the Relative Importance of Objects in Image Retrieval. | Sung Ju Hwang, Kristen Grauman |
| 2010 | CVPR | Reading between the lines: Object localization using implicit cues from image tags. | Sung Ju Hwang, Kristen Grauman |