251 citations · 478 across the 17 of their papers we have counts for
10 papers · 1 filter
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie +3
Predicting and executing a sequence of actions without intermediate replanning, known as action chunking, is increasingly used in robot learning from human demonstrations. Yet, its…
Affordance-Guided Reinforcement Learning via Visual Prompting
Olivia Y. Lee, Annie Xie, Kuan Fang +2
Robots equipped with reinforcement learning (RL) have the potential to learn a wide range of skills solely from a reward signal. However, obtaining a robust and dense reward signal…
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair +98
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…
Efficient Data Collection for Robotic Manipulation via Compositional Generalization
Jensen Gao, Annie Xie, Ted Xiao +2
Data collection has become an increasingly important problem in robotic manipulation, yet there still lacks much understanding of how to effectively collect data to facilitate broa…
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu +20
Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interactio…
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation
Annie Xie, Lisa Lee, Ted Xiao +1
What makes generalization hard for imitation learning in visual robotic manipulation? This question is difficult to approach at face value, but the environment from the perspective…
Influencing Towards Stable Multi-Agent Interactions
Woodrow Z. Wang, Andy Shih, Annie Xie +1
Learning in multi-agent environments is difficult due to the non-stationarity introduced by an opponent's or partner's changing behaviors. Instead of reactively adapting to the oth…
Learning Latent Representations to Influence Multi-Agent Interaction
Annie Xie, Dylan P. Losey, Ryan Tolsma +2
Seamlessly interacting with humans or robots is hard because these agents are non-stationary. They update their policy in response to the ego agent's behavior, and the ego agent mu…
Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight
Annie Xie, Frederik Ebert, Sergey Levine +1
Machine learning techniques have enabled robots to learn narrow, yet complex tasks and also perform broad, yet simple skills with a wide variety of objects. However, learning a mod…
Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control
Frederik Ebert, Chelsea Finn, Sudeep Dasari +3
Deep reinforcement learning (RL) algorithms can learn complex robotic skills from raw sensory inputs, but have yet to achieve the kind of broad generalization and applicability dem…