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09/18/2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
In this work, we present a scalable reinforcement learning method for tr...
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09/11/2023
Robot Parkour Learning
Parkour is a grand challenge for legged locomotion that requires robots ...
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08/24/2023
BridgeData V2: A Dataset for Robot Learning at Scale
We introduce BridgeData V2, a large and diverse dataset of robotic manip...
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07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
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07/26/2023
Waypoint-Based Imitation Learning for Robotic Manipulation
While imitation learning methods have seen a resurgent interest for robo...
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07/24/2023
Contrastive Example-Based Control
While many real-world problems that might benefit from reinforcement lea...
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07/07/2023
Polybot: Training One Policy Across Robots While Embracing Variability
Reusing large datasets is crucial to scale vision-based robotic manipula...
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07/07/2023
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation
What makes generalization hard for imitation learning in visual robotic ...
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06/26/2023
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Large transformer models trained on diverse datasets have shown a remark...
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06/19/2023
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts
Effective machine learning models learn both robust features that direct...
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06/14/2023
Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
Whereas machine learning models typically learn language by directly tra...
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06/08/2023
Conservative Prediction via Data-Driven Confidence Minimization
Errors of machine learning models are costly, especially in safety-criti...
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05/22/2023
Neural Functional Transformers
The recent success of neural networks as implicit representation of data...
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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...
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03/09/2023
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
A compelling use case of offline reinforcement learning (RL) is to obtai...
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03/02/2023
Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning
In imitation and reinforcement learning, the cost of human supervision l...
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03/02/2023
Open-World Object Manipulation using Pre-trained Vision-Language Models
For robots to follow instructions from people, they must be able to conn...
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02/27/2023
Permutation Equivariant Neural Functionals
This work studies the design of neural networks that can process the wei...
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02/24/2023
Language-Driven Representation Learning for Robotics
Recent work in visual representation learning for robotics demonstrates ...
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02/10/2023
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features
Conventional approaches to robustness try to learn a model based on caus...
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02/06/2023
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Training machine learning models robust to distribution shifts is critic...
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01/26/2023
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
The fluency and factual knowledge of large language models (LLMs) height...
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01/19/2023
A Survey of Meta-Reinforcement Learning
While deep reinforcement learning (RL) has fueled multiple high-profile ...
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01/18/2023
NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis
Expert demonstrations are a rich source of supervision for training visu...
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12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
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12/08/2022
Learning Options via Compression
Identifying statistical regularities in solutions to some tasks in multi...
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11/27/2022
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models
A growing ecosystem of large, open-source foundation models has reduced ...
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11/25/2022
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
Distribution shift occurs when the test distribution differs from the tr...
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11/21/2022
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference
While large pre-trained language models are powerful, their predictions ...
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11/16/2022
Giving Feedback on Interactive Student Programs with Meta-Exploration
Developing interactive software, such as websites or games, is a particu...
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10/25/2022
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations
There is an inescapable long-tailed class-imbalance issue in many real-w...
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10/20/2022
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
A common approach to transfer learning under distribution shift is to fi...
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10/19/2022
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning
A long-term goal of reinforcement learning is to design agents that can ...
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10/17/2022
You Only Live Once: Single-Life Reinforcement Learning
Reinforcement learning algorithms are typically designed to learn a perf...
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10/11/2022
C-Mixup: Improving Generalization in Regression
Improving the generalization of deep networks is an important open chall...
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10/11/2022
Knowledge-Driven New Drug Recommendation
Drug recommendation assists doctors in prescribing personalized medicati...
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10/11/2022
Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials
Recent progress in deep learning highlights the tremendous potential of ...
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10/06/2022
Learning to Reason With Relational Abstractions
Large language models have recently shown promising progress in mathemat...
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07/26/2022
Offline Reinforcement Learning at Multiple Frequencies
Leveraging many sources of offline robot data requires grappling with th...
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06/13/2022
Memory-Based Model Editing at Scale
Even the largest neural networks make errors, and once-correct predictio...
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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...
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05/11/2022
A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning
While reinforcement learning (RL) provides a framework for learning thro...
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04/18/2022
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models
We present a data-efficient framework for solving sequential decision-ma...
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04/04/2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Large language models can encode a wealth of semantic knowledge about th...
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03/15/2022
Vision-Based Manipulators Need to Also See from Their Hands
We study how the choice of visual perspective affects learning and gener...
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03/03/2022
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations
Spurious correlations pose a major challenge for robust machine learning...
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02/14/2022
Robust Policy Learning over Multiple Uncertainty Sets
Reinforcement learning (RL) agents need to be robust to variations in sa...
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02/07/2022
Diversify and Disambiguate: Learning From Underspecified Data
Many datasets are underspecified, which means there are several equally ...
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02/04/2022
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning
In this paper, we study the problem of enabling a vision-based robotic m...
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02/03/2022