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Found 12 papers, 10 papers with code
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.
Reparameterized Policy Learning for Multimodal Trajectory Optimization
We then present a practical model-based RL method, called Reparameterized Policy Gradient (RPG), which leverages the multimodal policy parameterization and learned world model to achieve strong exploration capabilities and high data efficiency.
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability
Model distillation, the process of creating smaller, faster models that maintain the performance of larger models, is a promising direction towards the solution.
On the Efficacy of 3D Point Cloud Reinforcement Learning
Recent studies on visual reinforcement learning (visual RL) have explored the use of 3D visual representations.
Deductive Verification of Chain-of-Thought Reasoning
In light of this, we propose to decompose a reasoning verification process into a series of step-by-step subprocesses, each only receiving their necessary context and premises.
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.
PartSLIP: Low-Shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models
Generalizable 3D part segmentation is important but challenging in vision and robotics.
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds
We study how choices of input point cloud coordinate frames impact learning of manipulation skills from 3D point clouds.
Improving Policy Optimization with Generalist-Specialist Learning
Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations.
Approximate Convex Decomposition for 3D Meshes with Collision-Aware Concavity and Tree Search
Approximate convex decomposition aims to decompose a 3D shape into a set of almost convex components, whose convex hulls can then be used to represent the input shape.
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.
State Alignment-based Imitation Learning
Consider an imitation learning problem that the imitator and the expert have different dynamics models.
