b'Pieter Abbeel'

research

∙ 06/02/2023

Probabilistic Adaptation of Text-to-Video Models

Large text-to-video models trained on internet-scale data have demonstra...

5 Mengjiao Yang, et al. ∙

research

∙ 05/31/2023

Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration

A promising technique for exploration is to maximize the entropy of visi...

0 Dongyoung Kim, et al. ∙

research

∙ 05/30/2023

Blockwise Parallel Transformer for Long Context Large Models

Transformers have emerged as the cornerstone of state-of-the-art natural...

0 Hao Liu, et al. ∙

research

∙ 05/26/2023

Emergent Agentic Transformer from Chain of Hindsight Experience

Large transformer models powered by diverse data and model scale have do...

0 Hao Liu, et al. ∙

research

∙ 05/25/2023

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

Learning from human feedback has been shown to improve text-to-image mod...

0 Ying Fan, et al. ∙

research

∙ 05/25/2023

The False Promise of Imitating Proprietary LLMs

An emerging method to cheaply improve a weaker language model is to fine...

0 Arnav Gudibande, et al. ∙

research

∙ 05/23/2023

Video Prediction Models as Rewards for Reinforcement Learning

Specifying reward signals that allow agents to learn complex behaviors i...

4 Alejandro Escontrela, et al. ∙

research

∙ 05/10/2023

Self-Supervised Instance Segmentation by Grasping

Instance segmentation is a fundamental skill for many robotic applicatio...

0 YuXuan Liu, et al. ∙

research

∙ 05/04/2023

Masked Trajectory Models for Prediction, Representation, and Control

We introduce Masked Trajectory Models (MTM) as a generic abstraction for...

0 Philipp Wu, et al. ∙

research

∙ 05/03/2023

Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN

Object recognition and instance segmentation are fundamental skills in a...

0 YuXuan Liu, et al. ∙

research

∙ 03/31/2023

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?

We present the largest and most comprehensive empirical study of pre-tra...

0 Arjun Majumdar, et al. ∙

research

∙ 03/07/2023

Foundation Models for Decision Making: Problems, Methods, and Opportunities

Foundation models pretrained on diverse data at scale have demonstrated ...

0 Sherry Yang, et al. ∙

research

∙ 03/02/2023

Preference Transformer: Modeling Human Preferences using Transformers for RL

Preference-based reinforcement learning (RL) provides a framework to tra...

0 Changyeon Kim, et al. ∙

research

∙ 02/23/2023

Aligning Text-to-Image Models using Human Feedback

Deep generative models have shown impressive results in text-to-image sy...

1 Kimin Lee, et al. ∙

research

∙ 02/19/2023

Robust and Versatile Bipedal Jumping Control through Multi-Task Reinforcement Learning

This work aims to push the limits of agility for bipedal robots by enabl...

0 Zhongyu Li, et al. ∙

research

∙ 02/13/2023

Guiding Pretraining in Reinforcement Learning with Large Language Models

Reinforcement learning algorithms typically struggle in the absence of a...

0 Yuqing Du, et al. ∙

research

∙ 02/10/2023

The Wisdom of Hindsight Makes Language Models Better Instruction Followers

Reinforcement learning has seen wide success in finetuning large languag...

0 Tianjun Zhang, et al. ∙

research

∙ 02/10/2023

Controllability-Aware Unsupervised Skill Discovery

One of the key capabilities of intelligent agents is the ability to disc...

0 Seohong Park, et al. ∙

research

∙ 02/06/2023

Languages are Rewards: Chain of Hindsight Finetuning using Human Feedback

Learning from human preferences is important for language models to be h...

0 Hao Liu, et al. ∙

research

∙ 02/05/2023

Multi-View Masked World Models for Visual Robotic Manipulation

Visual robotic manipulation research and applications often use multiple...

0 Younggyo Seo, et al. ∙

research

∙ 02/02/2023

Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment

Recent progress in scaling up large language models has shown impressive...

0 Hao Liu, et al. ∙

research

∙ 01/31/2023

Learning Universal Policies via Text-Guided Video Generation

A goal of artificial intelligence is to construct an agent that can solv...

7 Yilun Du, et al. ∙

research

∙ 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...

0 David Venuto, et al. ∙

research

∙ 11/23/2022

Masked Autoencoding for Scalable and Generalizable Decision Making

We are interested in learning scalable agents for reinforcement learning...

0 Fangchen Liu, et al. ∙

research

∙ 11/21/2022

VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models

Diffusion models have shown impressive results in text-to-image synthesi...

2 Ajay Jain, et al. ∙

research

∙ 11/03/2022

StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS

Most existing methods for category-level pose estimation rely on object ...

0 Kai Chen, et al. ∙

research

∙ 10/25/2022

Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data

Autonomous driving is complex, requiring sophisticated 3D scene understa...

0 John So, et al. ∙

research

∙ 10/24/2022

Dichotomy of Control: Separating What You Can Control from What You Cannot

Future- or return-conditioned supervised learning is an emerging paradig...

0 Mengjiao Yang, et al. ∙

research

∙ 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...

0 Hao Liu, et al. ∙

research

∙ 10/24/2022

Instruction-Following Agents with Jointly Pre-Trained Vision-Language Models

Humans are excellent at understanding language and vision to accomplish ...

0 Hao Liu, et al. ∙

research

∙ 10/19/2022

CLUTR: Curriculum Learning via Unsupervised Task Representation Learning

Reinforcement Learning (RL) algorithms are often known for sample ineffi...

0 Abdus Salam Azad, et al. ∙

research

∙ 10/14/2022

Skill-Based Reinforcement Learning with Intrinsic Reward Matching

While unsupervised skill discovery has shown promise in autonomously acq...

0 Ademi Adeniji, et al. ∙

research

∙ 10/13/2022

Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction

3D bounding boxes are a widespread intermediate representation in many c...

0 YuXuan Liu, et al. ∙

research

∙ 10/06/2022

Real-World Robot Learning with Masked Visual Pre-training

In this work, we explore self-supervised visual pre-training on images f...

15 Ilija Radosavovic, et al. ∙

research

∙ 10/05/2022

Temporally Consistent Video Transformer for Long-Term Video Prediction

Generating long, temporally consistent video remains an open challenge i...

0 Wilson Yan, et al. ∙

research

∙ 09/16/2022

Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks

In temporal-difference reinforcement learning algorithms, variance in va...

0 Litian Liang, et al. ∙

research

∙ 09/15/2022

HARP: Autoregressive Latent Video Prediction with High-Fidelity Image Generator

Video prediction is an important yet challenging problem; burdened with ...

0 Younggyo Seo, et al. ∙

research

∙ 09/15/2022

Multi-Objective Policy Gradients with Topological Constraints

Multi-objective optimization models that encode ordered sequential const...

0 Kyle Hollins Wray, et al. ∙

research

∙ 08/03/2022

AdaCat: Adaptive Categorical Discretization for Autoregressive Models

Autoregressive generative models can estimate complex continuous data di...

4 Qiyang Li, et al. ∙

research

∙ 06/29/2022

Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision

Commercial and industrial deployments of robot fleets often fall back on...

2 Ryan Hoque, et al. ∙

research

∙ 06/28/2022

Masked World Models for Visual Control

Visual model-based reinforcement learning (RL) has the potential to enab...

0 Younggyo Seo, et al. ∙

research

∙ 06/28/2022

DayDreamer: World Models for Physical Robot Learning

To solve tasks in complex environments, robots need to learn from experi...

10 Philipp Wu, et al. ∙

research

∙ 06/08/2022

Deep Hierarchical Planning from Pixels

Intelligent agents need to select long sequences of actions to solve com...

0 Danijar Hafner, et al. ∙

research

∙ 06/08/2022

Patch-based Object-centric Transformers for Efficient Video Generation

In this work, we present Patch-based Object-centric Video Transformer (P...

0 Wilson Yan, et al. ∙

research

∙ 06/07/2022

On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning

Intelligent agents should have the ability to leverage knowledge from pr...

0 Zhao Mandi, et al. ∙

research

∙ 05/27/2022

Multimodal Masked Autoencoders Learn Transferable Representations

Building scalable models to learn from diverse, multimodal data remains ...

0 Xinyang Geng, et al. ∙

research

∙ 05/24/2022

Reward Uncertainty for Exploration in Preference-based Reinforcement Learning

Conveying complex objectives to reinforcement learning (RL) agents often...

0 Xinran Liang, et al. ∙

research

∙ 05/22/2022

Chain of Thought Imitation with Procedure Cloning

Imitation learning aims to extract high-performance policies from logged...

0 Mengjiao Yang, et al. ∙

research

∙ 05/16/2022

An Empirical Investigation of Representation Learning for Imitation

Imitation learning often needs a large demonstration set in order to han...

8 Xin Chen, et al. ∙

research

∙ 04/26/2022

Coarse-to-fine Q-attention with Tree Expansion

Coarse-to-fine Q-attention enables sample-efficient robot manipulation b...

2 Stephen James, et al. ∙

Pieter Abbeel

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