贡献四:与state of art方法对比,评估GOT,发现GOT在解决一些 可以被细分为多个独立相似的子任务最后merge的那些任务上非常合适。 贡献五:提出了一个新的metric,用于评估prompting 策略。 GOT framework GOT可以被建模为一个元组(,,,G,τ,ε,R), G 是 LLM reasoning process(包含所有LLM thoughts和上下文和依赖关系...
Figure 1: Comparison of Graph of Thoughts (GoT) to other prompting strategies (Image from paper) Implementing Graph of Thoughts To implement GoT, developers need to represent the problem-solving process as a graph, where each node or vertex represents a thought or a piece of information. ...
Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models" - spcl/graph-of-thoughts
KRAGEN uses advanced prompting techniques: namely graph-of-thoughts (GoT), to dynamically break down a complex problem into smaller subproblems, and proceeds to solve each subproblem by using the relevant knowledge through the RAG framework, which limits the hallucinations, and finally, consolidates ...
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models - wyl-willing/MindMap
To enhance the understanding of graph structural information bylarge language models, our framework emphasizes aligning theencoding of graph structures with the natural language space. 为了增强大型语言模型对图结构信息的理解,我们的框架强调将图结构编码与自然语言空间相一致。
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models This is the official codebase of the MindMap ❄️ framework for eliciting the graph-of-thoughts reasoning capability in LLMs, proposed in MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large La...