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Learning to Reason and Use Tools through Unsupervised Fine-Tuning in Task-Oriented Dialog Systems
Current dialogue systems struggle with dynamic information retrieval, often leading to hallucinations and lower response accuracy. We address this by adapting the ReAct framework for Task-Oriented Dialogue, enabling Large Language Models (LLMs) to access external knowledge and produce factual respon
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