research
∙
04/29/2023
Synthetic Cross-language Information Retrieval Training Data
A key stumbling block for neural cross-language information retrieval (C...
share
research
∙
04/18/2023
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets
Enabling robots to learn novel visuomotor skills in a data-efficient man...
research
∙
02/24/2023
Language-Driven Representation Learning for Robotics
Recent work in visual representation learning for robotics demonstrates ...
research
∙
12/20/2022
Parameter-efficient Zero-shot Transfer for Cross-Language Dense Retrieval with Adapters
A popular approach to creating a zero-shot cross-language retrieval mode...
research
∙
05/30/2022
Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning
Humans are capable of completing a range of challenging manipulation tas...
research
∙
04/25/2022
C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval
Pretrained language models have improved effectiveness on numerous tasks...
research
∙
01/20/2022
Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
The advent of transformer-based models such as BERT has led to the rise ...
research
∙
12/07/2021
MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance
Safe exploration is critical for using reinforcement learning (RL) in ri...
research
∙
11/10/2021
Cross-language Information Retrieval
Two key assumptions shape the usual view of ranked retrieval: (1) that t...
research
∙
09/21/2021
Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
In this paper, we study the problem of learning a repertoire of low-leve...
research
∙
09/02/2021
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation
We study the problem of learning a range of vision-based manipulation ta...
research
∙
06/24/2021
FitVid: Overfitting in Pixel-Level Video Prediction
An agent that is capable of predicting what happens next can perform a v...
research
∙
03/31/2021
Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos
We are motivated by the goal of generalist robots that can complete a wi...
research
∙
03/06/2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
A video prediction model that generalizes to diverse scenes would enable...
research
∙
12/30/2020
Model-Based Visual Planning with Self-Supervised Functional Distances
A generalist robot must be able to complete a variety of tasks in its en...
research
∙
10/29/2020
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones
Safety remains a central obstacle preventing widespread use of RL in the...
research
∙
10/22/2020
Batch Exploration with Examples for Scalable Robotic Reinforcement Learning
Learning from diverse offline datasets is a promising path towards learn...
research
∙
07/14/2020
Goal-Aware Prediction: Learning to Model What Matters
Learned dynamics models combined with both planning and policy learning ...
research
∙
10/24/2019
RoboNet: Large-Scale Multi-Robot Learning
Robot learning has emerged as a promising tool for taming the complexity...
research
∙
10/03/2019
Causal Induction from Visual Observations for Goal Directed Tasks
Causal reasoning has been an indispensable capability for humans and oth...
research
∙
09/12/2019
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
Video prediction models combined with planning algorithms have shown pro...
research
∙
10/02/2018
Time Reversal as Self-Supervision
A longstanding challenge in robot learning for manipulation tasks has be...
research
∙
07/10/2018
Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration
Our goal is for a robot to execute a previously unseen task based on a s...
research
∙
10/04/2017
Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
In this work, we propose a novel robot learning framework called Neural ...
research
∙
09/22/2017
