3 citations · 3 across the 5 of their papers we have counts for
4 papers
Magic for the Age of Quantized DNNs
Yoshihide Sawada, Ryuji Saiin, Kazuma Suetake
Recently, the number of parameters in DNNs has explosively increased, as exemplified by LLMs (Large Language Models), making inference on small-scale computers more difficult. Mode…
Upper Bound of Bayesian Generalization Error in Partial Concept Bottleneck Model (CBM): Partial CBM outperforms naive CBM
Naoki Hayashi, Yoshihide Sawada
Concept Bottleneck Model (CBM) is a methods for explaining neural networks. In CBM, concepts which correspond to reasons of outputs are inserted in the last intermediate layer as o…
Bayesian Generalization Error in Linear Neural Networks with Concept Bottleneck Structure and Multitask Formulation
Naoki Hayashi, Yoshihide Sawada
Concept bottleneck model (CBM) is a ubiquitous method that can interpret neural networks using concepts. In CBM, concepts are inserted between the output layer and the last interme…
C-SENN: Contrastive Self-Explaining Neural Network
Yoshihide Sawada, Keigo Nakamura
In this study, we use a self-explaining neural network (SENN), which learns unsupervised concepts, to acquire concepts that are easy for people to understand automatically. In conc…