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Explorer: Exploration-guided reasoning for textual reinforcement learning
K Basu, K Murugesan, S Chaudhury… - ar** autonomous agents to deal with real-world problems is challenging, especially
when developers are not necessarily specialists in artificial intelligence. This poses two key …
when developers are not necessarily specialists in artificial intelligence. This poses two key …
Language Model Adaption for Reinforcement Learning with Natural Language Action Space
Reinforcement learning with natural language action space often suffers from the curse of
dimensionality due to the combinatorial nature of the natural language. Previous research …
dimensionality due to the combinatorial nature of the natural language. Previous research …
Leveraging Non-Parametric Reasoning with Large Language Models for Enhanced Knowledge Graph Completion
Y Zhang, YP Shen, G **ao, JH Peng - IEEE Access, 2024 - ieeexplore.ieee.org
The completeness of knowledge graphs is critical to their effectiveness across various
applications. However, existing knowledge graph completion methods face challenges such …
applications. However, existing knowledge graph completion methods face challenges such …
[PDF][PDF] Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning
M Atzeni - 2024 - infoscience.epfl.ch
The ability to reason, plan and solve highly abstract problems is a hal