【206论文泛读】Graph of Thoughts: Solving Elaborate Problems with Large Language Models 小z呀 凭君莫话封侯事, 一将功成万骨枯。问题: 现有的大型语言模型在解决复杂问题时,受限于提示策略的简单性,如直接输入输出(IO)、链式思考(Chain-of-Thought, CoT)和思想树(Tree of Thoughts, ToT)。这些方法在处理...
generation transformations 根据某个存在的thought生成一个或者多个新的thought.以及它们的边 \varepsilon,R分别代表计算当前thought的评分和排名的函数 工程实现 实现了关键字统计、排序、集合求交集、文档合并四个任务,并对比了多种思维链方法 https://github.com/spcl/graph-of-thoughts/tree/main...
The final thought states' scores indicate the number of errors in the sorted list. Documentation The paper gives a high-level overview of the framework and its components. In order to understand the framework in more detail, you can read the documentation of the individual modules. ...
Structured Memory Mapping:Anchor the AI's thought process as notes within an evolving fractal mind map. Graph your AI Conversations:Segment AI's responses into a cohesive web of thought that both improves AI reasoning and allows for the history of your chain of thought to dynamically construct ...
The first term simply replaces the observation with a similar Wh factor, which could be thought of as the model’s prediction of the input. (We will revisit this interpretation when we examine conditional probability models in Section 9.7 and restricted Boltzmann machines in Section 10.5.) This...
专栏/Beyond Chain-of-Thought Effective Graph- Beyond Chain-of-Thought Effective Graph- 2023年10月08日 10:0754浏览· 0点赞· 0评论 视频地址: Beyond Chain-of-Thought Effective Graph-of-Thought Reasoning in Large Language M 奶妈的摇摇车 粉丝:14文章:47 关注 04:24分享...
Informal Controls and the Explanation of Propensity to Offend: A Test in Two Urban Samples Propensity to offend is an important and stable predictor of offending. A person's propensity is often thought of as a multidimensional trait consisting of... L Pauwels,R Svensson - 《European Journal on...
最后,通过思维链(Chain-of-Thought)将闭源大语言模型(如,ChatGPT)蒸馏整合到GraphGPT中,增强了其逐步推理能力,极大地改善了分布偏移带来的性能下降。 本研究的主要贡献如下: 将图领域特定的结构知识与大语言模型的推理能力对齐,以提高图学习的泛化。 提出的方法旨在通过图指令微调范式将大语言模型与图结构数据对齐。
思维链(Chain-of-Thought, CoT):生成几个中间理由,然后再给出最终答案,以提高LLM处理复杂推理任务的能力。 知识链(Chain-of-Knowledge, CoK):一个异构源增强的LLM框架。 Think-on-Graph(ToG):一个基于知识图谱的方法,用于搜索有用的三元组进行推理。
为了应对这一挑战并在分布变化的情况下提高准确性,为GraphGPT配备逐步推理能力是至关重要的。受思维链技术(Chain-of-Thought)技术的启发,提出通过整合思维链技术,提高GraphGPT生成文本的连贯性和一致性,使模型能够遵循逻辑上的思维发展,进一步增强其理解和推理给定图数据的能力。