39 citations · 44 across the 11 of their papers we have counts for
4 papers · 1 filter
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback
Max Balsells, Marcel Torne, Zihan Wang +3
Ideally, we would place a robot in a real-world environment and leave it there improving on its own by gathering more experience autonomously. However, algorithms for autonomous ro…
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo +5
Large language models (LLMs) have made impressive progress in natural language processing. These models rely on proper human instructions (or prompts) to generate suitable response…
Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback
Marcel Torne, Max Balsells, Zihan Wang +4
Exploration and reward specification are fundamental and intertwined challenges for reinforcement learning. Solving sequential decision-making tasks requiring expansive exploration…
Guiding Pretraining in Reinforcement Learning with Large Language Models
Yuqing Du, Olivia Watkins, Zihan Wang +5
Reinforcement learning algorithms typically struggle in the absence of a dense, well-shaped reward function. Intrinsically motivated exploration methods address this limitation by…