Mar 11, 2024 · In this paper, we propose RLingua, a framework that can leverage the internal knowledge of large language models (LLMs) to reduce the sample ...
Jul 9, 2024 · In this paper, we propose RLingua, a framework that can leverage the internal knowledge of large language models (LLMs) to reduce the sample ...
Mar 20, 2024 · RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models.
The paper RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models introduces a novel framework ...
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models. Paper Link: arXiv 2403.06420, homepage.
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models. L Chen, Y Lei, S Jin, Y Zhang, L Zhang. IEEE ...
Jul 4, 2024 · Low sample efficiency is an enduring challenge of reinforcement learning (RL). With the advent of versatile large language models (LLMs), recent ...
Missing: RLingua: Robotic Manipulations
Low sample efficiency is an enduring challenge of reinforcement learning (RL). With the advent of versatile large language models (LLMs), recent works impart ...
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models ... In this paper, we propose RLingua, a framework ...
Jul 5, 2024 · RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models. ... Large Language Models ...