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Found 12 papers, 5 papers with code
AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agent
Encouraged by the remarkable achievements of language and vision foundation models, developing generalist robotic agents through imitation learning, using large demonstration datasets, has become a prominent area of interest in robot learning.
Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving
Large Language Models (LLMs) have achieved tremendous progress, yet they still often struggle with challenging reasoning problems.
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization
Nowadays, algorithms with fast convergence, small memory footprints, and low per-iteration complexity are particularly favorable for artificial intelligence applications.
Boosting Reinforcement Learning and Planning with Demonstrations: A Survey
Although reinforcement learning has seen tremendous success recently, this kind of trial-and-error learning can be impractical or inefficient in complex environments.
ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
Generalizable manipulation skills, which can be composed to tackle long-horizon and complex daily chores, are one of the cornerstones of Embodied AI.
On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline
In this paper, we examine the effectiveness of pre-training for visuo-motor control tasks.
Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
In the abstract environment, complex dynamics such as physical manipulation are removed, making abstract trajectories easier to generate.
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning
We present a two-step hybrid reinforcement learning (RL) policy that is designed to generate interpretable and robust hierarchical policies on the RL problem with graph-based input.
ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Here we propose SAPIEN Manipulation Skill Benchmark (ManiSkill) to benchmark manipulation skills over diverse objects in a full-physics simulator.
Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals
We study how to learn a policy with compositional generalizability.
State Alignment-based Imitation Learning
Consider an imitation learning problem that the imitator and the expert have different dynamics models.
Transfer Value or Policy? A Value-centric Framework Towards Transferrable Continuous Reinforcement Learning
In this paper, we investigate the problem of transfer learning across environments with different dynamics while accomplishing the same task in the continuous control domain.
