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

Research Highlights

(*: equal contribution)

	B-MoCA: Benchmarking Mobile Device Control Agents across Diverse Configurations Juyong Lee, Taywon Min, Minyong An, Dongyoon Hahm, Haeone Lee, Changyeon Kim, Kimin Lee ICLR 2024 workshop GenAI4DM (spotlight presentation) project / paper (ICLR version) / code A novel benchmark that can serve as a unified testbed for mobile device control agents on performing practical daily tasks across diverse device configurations.
	LiFT: Unsupervised Reinforcement Learning with Foundation Models as Teachers Taewook Nam, Juyong Lee, Jesse Zhang, Sung Ju Hwang, Joseph J Lim, Karl Pertsch NeurIPS 2023 workshop ALOE project / paper / code Reinforcement learning agents discover semantically meaningful skills with tasks proposed by a large language model and rewards from a vision-language model.
	Hyperbolic VAE via Latent Gaussian Distributions Seunghyuk Cho, Juyong Lee, Dongwoo Kim NeurIPS 2023, ICML 2023 workshop TAGML, KAIA 2022 (best paper) paper A newly proposed distribution (over a Riemannian manifold of the diagonal Gaussians equipped with Fisher information metric) empowers learning a hyperbolic world model.
	Style-Agnostic Reinforcement Learning Juyong Lee, Seokjun Ahn, Jaesik Park ECCV 2022 paper / code 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