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About this paper
Qiang Zhang, Jason Naradowsky, Yusuke Miyao
A framework named "Ask an Expert" was developed by University of Tokyo researchers, enabling goal-oriented dialogue models to consult large language models (LLMs) for strategic advice. This led to enhanced performance in mental health support conversations, with models utilizing a `davinci` expert achieving up to a -10.93% total win percentage against human conversations, demonstrating a notable improvement over baseline models and direct LLM generation.
Key insights
- Large Language Models are highly effective as external "reasoning engines" for strategic advice in goal-oriented dialogue systems when guided by appropriate structured prompts.
- A modular approach, combining a smaller fine-tuned dialogue model with a larger LLM expert, outperforms directly using a large LLM for end-to-end dialogue generation in complex tasks.
- The quality and utility of the expert advice are directly correlated with the size and capability of the underlying LLM, with more powerful models yielding superior reasoning.
Summary by alphaXiv.
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