982 citations · 2.8k across the 47 of their papers we have counts for
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Guide Your Agent with Adaptive Multimodal Rewards
Changyeon Kim, Younggyo Seo, Hao Liu +4
Developing an agent capable of adapting to unseen environments remains a difficult challenge in imitation learning. This work presents Adaptive Return-conditioned Policy (ARP), an…
StyleDrop: Text-to-Image Generation in Any Style
Kihyuk Sohn, Nataniel Ruiz, Kimin Lee +11
Pre-trained large text-to-image models synthesize impressive images with an appropriate use of text prompts. However, ambiguities inherent in natural language and out-of-distributi…
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Ying Fan, Olivia Watkins, Yuqing Du +7
Learning from human feedback has been shown to improve text-to-image models. These techniques first learn a reward function that captures what humans care about in the task and the…
Preference Transformer: Modeling Human Preferences using Transformers for RL
Changyeon Kim, Jongjin Park, Jinwoo Shin +3
Preference-based reinforcement learning (RL) provides a framework to train agents using human preferences between two behaviors. However, preference-based RL has been challenging t…
Aligning Text-to-Image Models using Human Feedback
Kimin Lee, Hao Liu, Moonkyung Ryu +6
Deep generative models have shown impressive results in text-to-image synthesis. However, current text-to-image models often generate images that are inadequately aligned with text…
Controllability-Aware Unsupervised Skill Discovery
Seohong Park, Kimin Lee, Youngwoon Lee +1
One of the key capabilities of intelligent agents is the ability to discover useful skills without external supervision. However, the current unsupervised skill discovery methods a…
Multi-View Masked World Models for Visual Robotic Manipulation
Younggyo Seo, Junsu Kim, Stephen James +3
Visual robotic manipulation research and applications often use multiple cameras, or views, to better perceive the world. How else can we utilize the richness of multi-view data? I…