Guest Lectures

Overview:

Human-in-the-Loop machine learning is a technology that leverages humans in the learning and inference process of machine learning models. A wide range of research has been conducted in this area, including not only the use of crowdsourcing to generate large-scale training data, but also the use of human feedback for efficient learning and the division of labor between humans and machines in the inference process. In this talk, We will describe recent developments in human-in-the-loop machine learning and discuss challenges in human utilization, such as quality and bias, as well as future prospects for human-machine collaboration with the development of large-scale language models.