Structural Embeddings of Tools for Large Language Models
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 26 references that are in the map. First posted on arXiv 1 Aug 2023.
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21 of 26 references.
References · 21
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9 more
- 2021Time-Aware Language Models as Temporal Knowledge Basescited by 290
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- 2024Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs
- 2024ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph
- 2024Synergizing Knowledge Graphs with Large Language Models: A Comprehensive Review and Future Prospects ↗
- 2026Are Large Language Models Suitable for Graph Computation? Progress and Prospects
- 2023Large Language Models on Graphs: A Comprehensive Survey
- 2025GraphGhost: Tracing Structures Behind Large Language Models
- 2023Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
- 2024Can LLMs perform structured graph reasoning?