179 citations · 382 across the 62 of their papers we have counts for
10 papers · 1 filter
Continual Learning: Forget-free Winning Subnetworks for Video Representations
Haeyong Kang, Jaehong Yoon, Sung Ju Hwang +1
Inspired by the Lottery Ticket Hypothesis (LTH), which highlights the existence of efficient subnetworks within larger, dense networks, a high-performing Winning Subnetwork (WSN) i…
Multimodal Representation Learning by Alternating Unimodal Adaptation
Xiaohui Zhang, Jaehong Yoon, Mohit Bansal +1
Multimodal learning, which integrates data from diverse sensory modes, plays a pivotal role in artificial intelligence. However, existing multimodal learning methods often struggle…
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
Yujin Kim, Jaehong Yoon, Seonghyeon Ye +4
The dynamic nature of knowledge in an ever-changing world presents challenges for language models trained on static data; the model in the real world often requires not only acquir…
STELLA: Continual Audio-Video Pre-training with Spatio-Temporal Localized Alignment
Jaewoo Lee, Jaehong Yoon, Wonjae Kim +2
Continuously learning a variety of audio-video semantics over time is crucial for audio-related reasoning tasks in our ever-evolving world. However, this is a nontrivial problem an…
ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models
Yi-Lin Sung, Jaehong Yoon, Mohit Bansal
Large Vision-Language Models (LVLMs) can understand the world comprehensively by integrating rich information from different modalities, achieving remarkable advancements on variou…
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
Yiyang Zhou, Chenhang Cui, Jaehong Yoon +5
Large vision-language models (LVLMs) have shown remarkable abilities in understanding visual information with human languages. However, LVLMs still suffer from object hallucination…
Continual Learners are Incremental Model Generalizers
Jaehong Yoon, Sung Ju Hwang, Yue Cao
Motivated by the efficiency and rapid convergence of pre-trained models for solving downstream tasks, this paper extensively studies the impact of Continual Learning (CL) models as…
Progressive Fourier Neural Representation for Sequential Video Compilation
Haeyong Kang, Jaehong Yoon, DaHyun Kim +2
Neural Implicit Representation (NIR) has recently gained significant attention due to its remarkable ability to encode complex and high-dimensional data into representation space a…
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models
Jaewoong Lee, Sangwon Jang, Jaehyeong Jo +5
Token-based masked generative models are gaining popularity for their fast inference time with parallel decoding. While recent token-based approaches achieve competitive performanc…
Forget-free Continual Learning with Soft-Winning SubNetworks
Haeyong Kang, Jaehong Yoon, Sultan Rizky Madjid +2
Inspired by Regularized Lottery Ticket Hypothesis (RLTH), which states that competitive smooth (non-binary) subnetworks exist within a dense network in continual learning tasks, we…