KG-Reasoner uses reinforcement learning to train LLMs for end-to-end multi-hop knowledge graph reasoning, achieving competitive or better results on eight benchmarks.
InProceedings of the 2018 Con- ference on Empirical Methods in Natural Language Processing, pages 3243–3253
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KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning
KG-Reasoner uses reinforcement learning to train LLMs for end-to-end multi-hop knowledge graph reasoning, achieving competitive or better results on eight benchmarks.