4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2024
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning
Takuma Fukuda, Hiroshi Kera, Kazuhiko Kawamoto
We propose Adapter Merging with Centroid Prototype Mapping (ACMap), an exemplar-free framework for class-incremental learning (CIL) that addresses both catastrophic forgetting and…
cs.AI2023★ 4 cited
On the Limitation of Diffusion Models for Synthesizing Training Datasets
Shin'ya Yamaguchi, Takuma Fukuda
Synthetic samples from diffusion models are promising for leveraging in training discriminative models as replications of real training datasets. However, we found that the synthet…