A self-discovery approach: DeepMind framework allows LLMs to find and use task-intrinsic reasoning structures

Illustration of three actions of SELF-DISCOVER. We use LMs to compose a coherent reasoning structure by selecting relevant modules, adapting to task-specific descriptions, and implement a reasoning structure in JSON. Credit: arXiv (2024). DOI: 10.48550/arxiv.2402.03620

A team of AI researchers at Google’s DeepMind project, working with a colleague from the University of Southern California, has developed a vehicle for allowing large language models (LLMs) to find and use task-intrinsic reasoning structures as a means for improving returned results.

The group has written a paper describing their framework and outlining how well it has tested thus far, and have posted it on …
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