2 citations · 3 across the 9 of their papers we have counts for
9 papers
Continual Distillation of Teachers from Different Domains
Nicolas Michel, Maorong Wang, Jiangpeng He +1
Deep learning models continue to scale, with some requiring more storage than many large-scale datasets. Thus, we introduce a new paradigm: Continual Distillation (CD), where a stu…
EvoGuard: An Extensible Agentic RL-based Framework for Practical and Evolving AI-Generated Image Detection
Chenyang Zhu, Maorong Wang, Jun Liu +2
The rapid proliferation of AI-Generated Images (AIGIs) poses severe misinformation risks, making AIGI detection critical yet challenging. Traditional detection paradigms mainly rel…
From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients
Nicolas Michel, Maorong Wang, Jiangpeng He +1
Continual Learning (CL) aims to learn from a non-stationary data stream where the underlying distribution changes over time. While recent advances have produced efficient memory-fr…
Reward Incremental Learning in Text-to-Image Generation
Maorong Wang, Jiafeng Mao, Xueting Wang +1
The recent success of denoising diffusion models has significantly advanced text-to-image generation. While these large-scale pretrained models show excellent performance in genera…
Dealing with Synthetic Data Contamination in Online Continual Learning
Maorong Wang, Nicolas Michel, Jiafeng Mao +1
Image generation has shown remarkable results in generating high-fidelity realistic images, in particular with the advancement of diffusion-based models. However, the prevalence of…
Improving Plasticity in Online Continual Learning via Collaborative Learning
Maorong Wang, Nicolas Michel, Ling Xiao +1
Online Continual Learning (CL) solves the problem of learning the ever-emerging new classification tasks from a continuous data stream. Unlike its offline counterpart, in online CL…
Rethinking Momentum Knowledge Distillation in Online Continual Learning
Nicolas Michel, Maorong Wang, Ling Xiao +1
Online Continual Learning (OCL) addresses the problem of training neural networks on a continuous data stream where multiple classification tasks emerge in sequence. In contrast to…
MetaMixer: A Regularization Strategy for Online Knowledge Distillation
Maorong Wang, Ling Xiao, Toshihiko Yamasaki
Online knowledge distillation (KD) has received increasing attention in recent years. However, while most existing online KD methods focus on developing complicated model structure…
Otaku: Intelligent Management System for Student-Intensive Dormitory
Yuanzhe Jin, Chenrui Zhang, Maorong Wang
In most student dorms in developing countries, a large number of people live in single-function dorm units. The division of the dormitory is too fixed, resulting in the dormitory o…