Structural Embeddings of Tools for Large Language Models
Eren Unlu
It is evident that the current state of Large Language Models (LLMs)
necessitates the incorporation of external tools. The lack of straightforward
algebraic and logical reasoning is well documented and prompted researchers to
develop frameworks which allow LLMs to operate via external tools. The
ontological nature of tool utilization for a specific task can be well
formulated with a Directed Acyclic Graph (DAG). The central aim of the paper is
to highlight the importance of graph based approaches to LLM-tool interaction
in near future. We propose an exemplary framework to guide the orchestration of
exponentially increasing numbers of external tools with LLMs,where objectives
and functionalities of tools are graph encoded hierarchically. Assuming that
textual segments of a Chain-of-Thought (CoT) can be imagined as a tool as
defined here, the graph based framework can pave new avenues in that particular
direction as well.