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Found 10 papers, 6 papers with code
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Model-Free Reinforcement Learning (MFRL), leveraging the policy gradient theorem, has demonstrated considerable success in continuous control tasks.
On the Opportunities and Risks of Foundation Models
AI is undergoing a paradigm shift with the rise of models (e. g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.
Dexterous Manipulation Primitives for the Real Robot Challenge
We use model-based trajectory optimization and control to plan and execute these primitives.
Robotics
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones
Safety remains a central obstacle preventing widespread use of RL in the real world: learning new tasks in uncertain environments requires extensive exploration, but safety requires limiting exploration.
Learning to be Safe: Deep RL with a Safety Critic
Safety is an essential component for deploying reinforcement learning (RL) algorithms in real-world scenarios, and is critical during the learning process itself.
Learning Hierarchical Control for Robust In-Hand Manipulation
Finally, we show how our approach generalizes to objects of other shapes.
Controlling Assistive Robots with Learned Latent Actions
Our insight is that we can make assistive robots easier for humans to control by leveraging latent actions.
Robotics
Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks
Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback.
Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks
Contact-rich manipulation tasks in unstructured environments often require both haptic and visual feedback.
Graph-based Neural Multi-Document Summarization
We propose a neural multi-document summarization (MDS) system that incorporates sentence relation graphs.
Ranked #1 on
Multi-Document Summarization
on DUC 2004
