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Graph-of-Thought(GoT)
Non-linear reasoning with thoughts as nodes and dependencies as edges
In 30 seconds
- What
- Models reasoning as a directed graph where thoughts are nodes, dependencies are edges, and the agent explores multiple paths with backtracking and synthesis.
- When to use
- Problems with many interdependent factors where linear reasoning misses emergent solutions or requires revisiting earlier conclusions.
- Watch out
- Computational cost and latency grow sharply; easy to lose coherence across a large graph without explicit synthesis steps.
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Graph-of-Thought: Overview
Non-linear reasoning with thoughts as nodes and dependencies as edges
- Non-linear thought exploration
- Thoughts as vertices, dependencies as edges
- Synergistic idea combination
- Feedback loops and backtracking
- Complex network distillation
- Superior to linear CoT for complex problems
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References
The papers, specifications, and repositories this pattern is based on.
- Graph of Thoughts: Solving Elaborate Problems with Large Language Models (Besta et al., 2023)arXiv:2308.09687
- Graph-of-Thought for Complex and Dynamic Business Problems (Li, 2024)arXiv:2401.06801
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022)arXiv:2201.11903
- Tree of Thoughts: Deliberate Problem Solving with Large Language Models (Yao et al., 2023)arXiv:2305.10601
- SPCL: Graph-of-Thoughts Official Implementation
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