源代码：github.com/facebookresearch/MetaICL 前言 “学会学习”或元学习，是利用过去的经验指导新任务学习，提升模型自学习能力的一种方法，尤其适用于小样本学习场景。语境学习强调通过上下文直接解决新任务，无需参数更新，但效果往往不如微调，且模板设计复杂。MetaICL旨在通过元学习简化这一过程。MetaICL...
“学会学习“(Learning to learn),又称元学习(Meta-Learing), 即利用以往的知识经验来指导新任务的学习,使网络具备学会学习的能力,是解决小样本问题(Few-shot Learning)常用的方法之一。 语境学习(In-context learning),完全依赖语言模型从预训练过程中习得的推理能力,通过上下文语境(task description)直接解决新任务的...
In-context learning在推理的时候输入任务的样例对,体感上似乎是让模型来了解这些任务,再对新的数据进行判断,但是在推理的过程中其实并没有对参数做更新。这种形式体感上有点让人摸不清楚模型为什么会有这种迁移到新任务上的能力,推理的时候输入的示例具体有什么影响也是个疑问。之前prompt方法有效果更多的是因为预训练...
这篇文章的第一个结论是:in-context learning中,模型并没有学习输入和标签之间的对应关系。 通过给in-context的训练样本赋予随机标签,可以构建随机标注的设置。从下图中可以看出,无论是分类任务(上),还是多项选择任务(下),随机标注设置下(红)模型表现均和...
Large language models (LLMs) have demonstrated their ability to learn in-context, allowing them to perform various tasks based on a few input-output examples. However, the effectiveness of in-context learning is heavily reliant on the quality of the selected examples. In this paper...
the course of a one‐year postgraduate programme and the importance of the interaction between learner identities and the contexts in which student teachers learn to teach: a relationship that is critical to our understanding of beginning teachers' development in whatever specific context it occurs. ...
in-context learning区别于其他学习形式,如机器学习、深度学习、监督学习和无监督学习,后者的学习过程依赖于梯度更新模型参数。在in-context learning中,"context"意指上下文,即输入的数据背景。通过理解输入文本,模型从文本中获取知识和信息,不更新参数,单纯理解输入文本内容,并在后续对话中应用这些知识。对于未曾见识过的...
Self-instruction in the EFL Context: Learning How to Learn a Foreign Language The label `self instruction' is used to refer to situations in which a learner, with others, or alone, is working without the direct control of a teacher (... MD Tzotzou,SE Teacher 被引量: 0发表: 0年 A ...
语境学习(in-context learning)是一种直接通过给定实例集合理解任务并给出答案的方法,本质是使用训练完毕的语言模型来估计在给定实例条件下的条件概率分布模型。实例集合由指令规则下的自由文本表达实例组成,根据此集合可得到候选答案的概率模型。大规模预训练语言模型在语境学习方面表现出色,但通过减少预训练与推理阶段的差...
[1] MetaICL: Learning to Learn In Context:https://aclanthology.org/2022.naacl-main.201/ [2] LaMDA: Language Models for Dialog Applications:https://arxiv.org/abs/2201.08239 [3] Finetuned Language Models are Zero-Shot Learners:https://openreview.net/forum?id=gEZrGCozdqR ...