6 citations · 7 across the 4 of their papers we have counts for
4 papers
TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices
Wataru Kawabe, Hiroto Fukuda, Akihisa Shitara +2
We introduce TofuML, an interactive system designed to make machine learning (ML) concepts more accessible and engaging for non-expert users. Unlike conventional GUI-based systems,…
DuetML: Human-LLM Collaborative Machine Learning Framework for Non-Expert Users
Wataru Kawabe, Yusuke Sugano
Machine learning (ML) models have significantly impacted various domains in our everyday lives. While large language models (LLMs) offer intuitive interfaces and versatility, task-…
Technical Understanding from IML Hands-on Experience: A Study through a Public Event for Science Museum Visitors
Wataru Kawabe, Yuri Nakao, Akihisa Shitara +1
While AI technology is becoming increasingly prevalent in our daily lives, the comprehension of machine learning (ML) among non-experts remains limited. Interactive machine learnin…
Image-to-Text Translation for Interactive Image Recognition: A Comparative User Study with Non-Expert Users
Wataru Kawabe, Yusuke Sugano
Interactive machine learning (IML) allows users to build their custom machine learning models without expert knowledge. While most existing IML systems are designed with classifica…