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

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

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network. - Jaehong Yoon; Jungnyun Lee; Mincheol Whang (Comput. Intell. Neurosci., 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)

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

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

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

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

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

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

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)

Representational Continuity for Unsupervised Continual Learning. - Divyam Madaan; Jaehong Yoon; Yuanchun Li; Yunxin Liu 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)

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)

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

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)

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

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

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

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)

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. - Xiyao Wang; Yuhang Zhou; Xiaoyu Liu 003; Hongjin Lu; Yuancheng Xu; Feihong He; Jaehong Yoon; Taixi Lu; Fuxiao Liu; Gedas Bertasius; Mohit Bansal; Huaxiu Yao; et al. (ACL (1), 2024)

Multimodal Representation Learning by Alternating Unimodal Adaptation. - Xiaohui Zhang 006; Jaehong Yoon; Mohit Bansal; Huaxiu Yao (CVPR, 2024)

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

ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models. - Yi-Lin Sung; Jaehong Yoon; Mohit Bansal (ICLR, 2024)

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. - Yiyang Zhou; Chenhang Cui; Jaehong Yoon; Linjun Zhang; Zhun Deng; Chelsea Finn; Mohit Bansal; Huaxiu Yao (ICLR, 2024)

EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal Tokens. - Sunil Hwang; Jaehong Yoon; Youngwan Lee; 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)

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)

SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data. - Jialu Li 001; Jaemin Cho 001; Yi-Lin Sung; Jaehong Yoon; Mohit Bansal (NeurIPS, 2024)

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. - Xiyao Wang; Yuhang Zhou; Xiaoyu Liu 003; Hongjin Lu; Yuancheng Xu; Feihong He; Jaehong Yoon; Taixi Lu; Gedas Bertasius; Mohit Bansal; Huaxiu Yao; Furong Huang (CoRR, 2024)

CREMA: Multimodal Compositional Video Reasoning via Efficient Modular Adaptation and Fusion. - Shoubin Yu; Jaehong Yoon; Mohit Bansal (CoRR, 2024)

EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents. - Abhay Zala; Jaemin Cho 001; Han Lin; Jaehong Yoon; Mohit Bansal (CoRR, 2024)

RACCooN: Remove, Add, and Change Video Content with Auto-Generated Narratives. - Jaehong Yoon; Shoubin Yu; Mohit Bansal (CoRR, 2024)

Glider: Global and Local Instruction-Driven Expert Router. - Pingzhi Li; Prateek Yadav; Jaehong Yoon; Jie Peng 002; Yi-Lin Sung; Mohit Bansal; Tianlong Chen 001 (CoRR, 2024)

Adapt-∞: Scalable Lifelong Multimodal Instruction Tuning via Dynamic Data Selection. - Adyasha Maharana; Jaehong Yoon; Tianlong Chen 001; Mohit Bansal (CoRR, 2024)

VideoRepair: Improving Text-to-Video Generation via Misalignment Evaluation and Localized Refinement. - Daeun Lee; Jaehong Yoon; Jaemin Cho 001; Mohit Bansal (CoRR, 2024)

DreamRunner: Fine-Grained Storytelling Video Generation with Retrieval-Augmented Motion Adaptation. - Zun Wang; Jialu Li 001; Han Lin; Jaehong Yoon; Mohit Bansal (CoRR, 2024)

VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos. - Ziyang Wang; Shoubin Yu; Elias Stengel-Eskin; Jaehong Yoon; Feng Cheng; Gedas Bertasius; Mohit Bansal (CVPR, 2025)

Enhancing Thermal Infrared Object Detection Using SimAM-Integrated YOLOX for Improved Feature Representation. - Jaehong Yoon; Heegwang Kim; Chanyeong Park; Junbo Jang; Jiyoon Lee; Joonki Paik (ICCE, 2025)

Adapt-∞: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection. - Adyasha Maharana; Jaehong Yoon; Tianlong Chen 001; Mohit Bansal (ICLR, 2025)

SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation. - Jaehong Yoon; Shoubin Yu; Vaidehi Patil; Huaxiu Yao; Mohit Bansal (ICLR, 2025)

CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular Fusion. - Shoubin Yu; Jaehong Yoon; Mohit Bansal (ICLR, 2025)

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective. - Yue Huang 001; Chujie Gao; Siyuan Wu 001; Haoran Wang 005; Xiangqi Wang; Yujun Zhou 010; Yanbo Wang 005; Jiayi Ye; Jiawen Shi; Qihui Zhang; Yuan Li 032; Han Bao 003; et al. (CoRR, 2025)

RSQ: Learning from Important Tokens Leads to Better Quantized LLMs. - Yi-Lin Sung; Prateek Yadav; Jialu Li 001; Jaehong Yoon; Mohit Bansal (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)

Training-free Guidance in Text-to-Video Generation via Multimodal Planning and Structured Noise Initialization. - Jialu Li 001; Shoubin Yu; Han Lin; Jaemin Cho 001; Jaehong Yoon; Mohit Bansal (CoRR, 2025)

EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance. - Zun Wang; Jaemin Cho 001; Jialu Li 001; Han Lin; Jaehong Yoon; Yue Zhang 004; Mohit Bansal (CoRR, 2025)

Video-Skill-CoT: Skill-based Chain-of-Thoughts for Domain-Adaptive Video Reasoning. - Daeun Lee; Jaehong Yoon; Jaemin Cho 001; Mohit Bansal (CoRR, 2025)

Movie Facts and Fibs (MF2): A Benchmark for Long Movie Understanding. - Emmanouil Zaranis; António Farinhas; Saul José Rodrigues dos Santos; Beatriz Canaverde; Miguel Moura Ramos; Aditya K. Surikuchi; André Viveiros; Baohao Liao; Elena Belén Bueno-Benito; Nithin Sivakumaran; Pavlo Vasylenko; Shoubin Yu; et al. (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)

MEXA: Towards General Multimodal Reasoning with Dynamic Multi-Expert Aggregation. - Shoubin Yu; Yue Zhang; Ziyang Wang; Jaehong Yoon; Mohit Bansal (CoRR, 2025)

Video-RTS: Rethinking Reinforcement Learning and Test-Time Scaling for Efficient and Enhanced Video Reasoning. - Ziyang Wang; Jaehong Yoon; Shoubin Yu; Md Mohaiminul Islam; Gedas Bertasius; Mohit Bansal (CoRR, 2025)