103 citations · 190 across the 12 of their papers we have counts for
3 papers · 1 filter
Offline Meta-Reinforcement Learning for Industrial Insertion
Tony Z. Zhao, Jianlan Luo, Oleg Sushkov +5
Reinforcement learning (RL) can in principle let robots automatically adapt to new tasks, but current RL methods require a large number of trials to accomplish this. In this paper,…
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta, Justin Yu, Tony Z. Zhao +5
Reinforcement Learning (RL) algorithms can in principle acquire complex robotic skills by learning from large amounts of data in the real world, collected via trial and error. Howe…
Calibrate Before Use: Improving Few-Shot Performance of Language Models
Tony Z. Zhao, Eric Wallace, Shi Feng +2
GPT-3 can perform numerous tasks when provided a natural language prompt that contains a few training examples. We show that this type of few-shot learning can be unstable: the cho…