Juyong Lee

I am a PhD(/MS int.) student at KAIST, advised by Kimin Lee. I received a B.S. degree with a double major in both Mathematics and Computer Science/Engineering at POSTECH. I have an experience as an exchange student at Stanford.

I am currently interested in building practical AI agents.

CV  /  Google Scholar  /  Github

We propose a new benchmark for evaluating the safety and helpfulness of agents, with extensive analysis of the shortcomings of frontier LLM agents in mobile device control.

A novel benchmark that can serve as a unified testbed for mobile device control agents on performing practical daily tasks across diverse device configurations.

Reinforcement learning agents discover semantically meaningful skills with tasks proposed by a large language model and rewards from a vision-language model.

A newly proposed distribution (over a Riemannian manifold of the diagonal Gaussians equipped with Fisher information metric) empowers learning a hyperbolic world model.

Reinforcement learning agents become robust to the changes in the style of the image (e.g., background color) by adapting to adversarially generated styles.

The source code is from here