154 citations · 510 across the 52 of their papers we have counts for
7 papers · 1 filter
Accelerating Reinforcement Learning of Robotic Manipulations via Feedback from Large Language Models
Kun Chu, Xufeng Zhao, Cornelius Weber +2
Reinforcement Learning (RL) plays an important role in the robotic manipulation domain since it allows self-learning from trial-and-error interactions with the environment. Still,…
Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic
Xufeng Zhao, Mengdi Li, Wenhao Lu +4
Recent advancements in large language models have showcased their remarkable generalizability across various domains. However, their reasoning abilities still have significant room…
Chat with the Environment: Interactive Multimodal Perception Using Large Language Models
Xufeng Zhao, Mengdi Li, Cornelius Weber +2
Programming robot behavior in a complex world faces challenges on multiple levels, from dextrous low-level skills to high-level planning and reasoning. Recent pre-trained Large Lan…
Sample-efficient Real-time Planning with Curiosity Cross-Entropy Method and Contrastive Learning
Mostafa Kotb, Cornelius Weber, Stefan Wermter
Model-based reinforcement learning (MBRL) with real-time planning has shown great potential in locomotion and manipulation control tasks. However, the existing planning methods, su…
Learning Bidirectional Action-Language Translation with Limited Supervision and Incongruent Input
Ozan Özdemir, Matthias Kerzel, Cornelius Weber +4
Human infant learning happens during exploration of the environment, by interaction with objects, and by listening to and repeating utterances casually, which is analogous to unsup…
Emphasizing Unseen Words: New Vocabulary Acquisition for End-to-End Speech Recognition
Leyuan Qu, Cornelius Weber, Stefan Wermter
Due to the dynamic nature of human language, automatic speech recognition (ASR) systems need to continuously acquire new vocabulary. Out-Of-Vocabulary (OOV) words, such as trending…