32 citations · 65 across the 13 of their papers we have counts for
14 papers
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…
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…
Internally Rewarded Reinforcement Learning
Mengdi Li, Xufeng Zhao, Jae Hee Lee +2
We study a class of reinforcement learning problems where the reward signals for policy learning are generated by an internal reward model that is dependent on and jointly optimize…
Harnessing the Power of Multi-Task Pretraining for Ground-Truth Level Natural Language Explanations
Björn Plüster, Jakob Ambsdorf, Lukas Braach +2
Natural language explanations promise to offer intuitively understandable explanations of a neural network's decision process in complex vision-language tasks, as pursued in recent…
Neuro-Symbolic Spatio-Temporal Reasoning
Jae Hee Lee, Michael Sioutis, Kyra Ahrens +3
Knowledge about space and time is necessary to solve problems in the physical world: An AI agent situated in the physical world and interacting with objects often needs to reason a…
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning
Kyra Ahrens, Matthias Kerzel, Jae Hee Lee +2
Spatial reasoning poses a particular challenge for intelligent agents and is at the same time a prerequisite for their successful interaction and communication in the physical worl…