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Tool Use as Problem Decomposition in LLMs
In Large Language Models (LLMs), integrating external tools is a practical application of problem decomposition. Since LLMs may lack real-time or highly specific accurate data (like stock prices or weather updates) after training or fine-tuning, they can be connected with external APIs. To fulfill a complex query, the LLM decomposes the task into sub-problems: it handles parts of the query internally while generating specific markers to call external tools for the remaining sub-problems, effectively merging internal generation with external data retrieval.
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Foundations of Large Language Models
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Tool Use as Problem Decomposition in LLMs