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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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05/23/2023
Improving Factuality and Reasoning in Language Models through Multiagent Debate
Large language models (LLMs) have demonstrated remarkable capabilities i...
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05/04/2023
Masked Trajectory Models for Prediction, Representation, and Control
We introduce Masked Trajectory Models (MTM) as a generic abstraction for...
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03/27/2023
Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning
Most successes in robotic manipulation have been restricted to single-ar...
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03/06/2023
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks. However, e...
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03/01/2023
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control
Recent progress in large language models (LLMs) has demonstrated the abi...
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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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11/24/2022
Melting Pot 2.0
Multi-agent artificial intelligence research promises a path to develop ...
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11/23/2022
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets
Using massive datasets to train large-scale models has emerged as a domi...
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11/17/2022
VeLO: Training Versatile Learned Optimizers by Scaling Up
While deep learning models have replaced hand-designed features across m...
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10/24/2022
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners
Large language models (LLM) trained using the next-token-prediction obje...
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10/21/2022
Implicit Offline Reinforcement Learning via Supervised Learning
Offline Reinforcement Learning (RL) via Supervised Learning is a simple ...
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10/20/2022
Composing Ensembles of Pre-trained Models via Iterative Consensus
Large pre-trained models exhibit distinct and complementary capabilities...
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07/12/2022
Inner Monologue: Embodied Reasoning through Planning with Language Models
Recent works have shown how the reasoning capabilities of Large Language...
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06/30/2022
Learning Iterative Reasoning through Energy Minimization
Deep learning has excelled on complex pattern recognition tasks such as ...
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05/30/2022
Multi-Game Decision Transformers
A longstanding goal of the field of AI is a strategy for compiling diver...
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03/15/2022
Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning
Most successes in robotic manipulation have been restricted to single-ar...
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03/15/2022
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning
Assembly of multi-part physical structures is both a valuable end produc...
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02/03/2022
Pre-Trained Language Models for Interactive Decision-Making
Language model (LM) pre-training has proven useful for a wide variety of...
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01/18/2022
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Can world knowledge learned by large language models (LLMs) be used to a...
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11/04/2021
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning
Dexterous manipulation of arbitrary objects, a fundamental daily task fo...
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11/04/2021
Unsupervised Learning of Compositional Energy Concepts
Humans are able to rapidly understand scenes by utilizing concepts extra...
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10/14/2021
The Neural MMO Platform for Massively Multiagent Research
Neural MMO is a computationally accessible research platform that combin...
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09/01/2021
Implicit Behavioral Cloning
We find that across a wide range of robot policy learning scenarios, tre...
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07/14/2021
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Existing evaluation suites for multi-agent reinforcement learning (MARL)...
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06/24/2021
Brax – A Differentiable Physics Engine for Large Scale Rigid Body Simulation
We present Brax, an open source library for rigid body simulation with a...
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06/24/2021
Model-Based Reinforcement Learning via Latent-Space Collocation
The ability to plan into the future while utilizing only raw high-dimens...
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06/02/2021
Decision Transformer: Reinforcement Learning via Sequence Modeling
We present a framework that abstracts Reinforcement Learning (RL) as a s...
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03/09/2021
Pretrained Transformers as Universal Computation Engines
We investigate the capability of a transformer pretrained on natural lan...
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12/07/2020
Reset-Free Lifelong Learning with Skill-Space Planning
The objective of lifelong reinforcement learning (RL) is to optimize age...
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12/02/2020
Improved Contrastive Divergence Training of Energy Based Models
We propose several different techniques to improve contrastive divergenc...
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11/24/2020
Energy-Based Models for Continual Learning
We motivate Energy-Based Models (EBMs) as a promising model class for co...
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11/03/2020
Rearrangement: A Challenge for Embodied AI
We describe a framework for research and evaluation in Embodied AI. Our ...
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10/27/2020
γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction
We introduce the γ-model, a predictive model of environment dynamics wit...
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07/09/2020
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
Reinforcement learning is typically concerned with learning control poli...
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04/16/2020
A Game Theoretic Framework for Model Based Reinforcement Learning
Model-based reinforcement learning (MBRL) has recently gained immense in...
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04/13/2020
Compositional Visual Generation and Inference with Energy Based Models
A vital aspect of human intelligence is the ability to compose increasin...
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12/03/2019
Adaptive Online Planning for Continual Lifelong Learning
We study learning control in an online lifelong learning scenario, where...
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09/17/2019
Emergent Tool Use From Multi-Agent Autocurricula
Through multi-agent competition, the simple objective of hide-and-seek, ...
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09/15/2019
Model Based Planning with Energy Based Models
Model-based planning holds great promise for improving both sample effic...
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03/20/2019
Implicit Generation and Generalization in Energy-Based Models
Energy based models (EBMs) are appealing due to their generality and sim...
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03/02/2019
Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents
The emergence of complex life on Earth is often attributed to the arms r...
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01/29/2019
Multi Agent Reinforcement Learning with Multi-Step Generative Models
The dynamics between agents and the environment are an important compone...
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11/06/2018
Concept Learning with Energy-Based Models
Many hallmarks of human intelligence, such as generalizing from limited ...
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11/05/2018
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control
We propose a plan online and learn offline (POLO) framework for the sett...
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03/20/2018
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines
Policy gradient methods have enjoyed great success in deep reinforcement...
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11/02/2017
Interpretable and Pedagogical Examples
Teachers intentionally pick the most informative examples to show their ...
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10/10/2017
Emergent Complexity via Multi-Agent Competition
Reinforcement learning algorithms can train agents that solve problems i...
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10/10/2017
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Ability to continuously learn and adapt from limited experience in nonst...
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09/13/2017
