1、Self-Ask:输入生成后续问题,并问自己这些问题。然后将问题和中间答案添加到CoTs中:Measuring and narrowing the compositionality gap in language models. 2、iCAP: 一种上下文感知提示器,可以动态调整每个推理步骤的上下文:2022.Iteratively prompt pre-trained language models for chain of thought. 3、Least-to-...
它采用协同方法,结合信息检索机制和上下文学习(In-Context Learning, ICL)来增强LLM的性能。在这个框架中,用户发起的查询通过搜索算法检索相关信息。然后将这些信息编织到LLM的提示中,为生成过程提供额外的上下文。RAG的关键优势在于它消除了为特定任务重新训练LLMs的需要。开发者可以添加一个外部知识库,丰富输入,从而提高...
Towards Reasoning in Large Language Models: A Survey. Jie Huang, Kevin Chen-Chuan Chang. [abs], 2022.12 A Survey of Deep Learning for Mathematical Reasoning. Pan Lu, Liang Qiu, Wenhao Yu, Sean Welleck, Kai-Wei Chang. [abs], 2022.12 A Survey for In-context Learning. Qingxiu Dong, Lei ...
BIJC’s Jewelry Industry I.D.E.A. education program will launch in January and is designed to promote inclusivity, diversity, and equity for all. It is being presented in partnership with more than a half-dozen major industry organizations. “The jewelry industry’s leading organizations have j...
For both humans and machines, the essence of learning is to pinpoint which components in its information processing pipeline are responsible for an error in its output, a challenge that is known as ‘credit assignment’. It has long been assumed that credit assignment is best solved by backpro...
(2022 IVC 行人再识别综述)Deep learning-based person re-identification methods: A survey and outlook of recent works 深度学习行人重识别综述与展望 论文地址:https://arxiv.org/abs/2110.04764 摘要 近年来,随着公共安全需求的不断增加和智能监控网络的快速发展,行人再识别(Re-ID)已成为计算机视觉...
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024. - EnnengYang/Awesome-Forgetting-in-Deep-Learning
5). In both cases, learning is done by the individual, and is mediated by the social context. 1.4. Community of Inquiry and the Nth presence (Huang, Law and Lee, 2019) note that “while there have been debates regarding learning presence, it is clear that one cannot fully explain and ...
Ni. 2020. Generalizing from a few examples: A survey on few-shot learning. ACM Computing Surveys 53, 3 (2020), 1–34. 文章的分类方法引用了以上论文,分类依据主要是方法在那一份是哪个面提升了对高级知识的应用。(1) 数据扩增。通常作为预处理步骤进行。通过对图像进行旋转、转换、缩放、对称反转等...
【Arxiv-2021】【IEEE members/fellows】Graph Self-Supervised Learning: A Survey 核心要点 文章旨在对现有图神经网络的方法进行全面的总结和分类,并给出常用的数据集、评估基准、方法间的性能比较和开源代码链接。图的深度学习的热度与日俱增,但大多数工作集中在(半)监督学习上。对比标签的严重依赖导致模型泛化能力...