Hierarchical RNN for Few-Shot Information Extraction Learning InformationEXTRACTIONATTENTIONRNNFew-ShotLEARNINGShengpeng LiuZhejiang UniversityYing LiZhejiang UniversityBinbin FanZhejiang University国际计算机前沿大会会议论文集
简介:少样本关系提取旨在通过在每个关系中使用几个标记的例子进行训练来预测句子中一对实体的关系。最近的一些工作引入了关系信息 A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction 论文:https://aclanthology.org/2022.findings-acl.62.pdf 代码:https://github.com/lyly...
[ACL 23] CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors artpli.github.io/CodeIE/ Topics information-extraction large-language-models Resources Readme Activity Stars 35 stars Watchers 2 watching Forks 0 forks Report repository Releases No releases published...
本着实用的原则,今天教大家怎样进行微调nlp任务(文本分类,文本匹配,关系抽取三个任务)。 1、finetune:利用下游任务的数据集更新大模型的参数 2、few-shot(fs):推理的时候给一些声明作为条件,但是不更新权…
Named entity recognition (NER) is one of the fundamental tasks of information extraction. Recognizing unseen entities from numerous contents with the support of only a few labeled samples, also termed as few-shot learning, is a crucial issue to be studied. Few-shot NER aims at identifying ...
论文链接:[2205.09536] A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction (arxiv.org) Abstract 本文提出了一种直接相加的方法来引入关系信息。具体来说,对于每个关系类,首先通过连接两个关系视图(即[CLS] token embedding和所有token embedding的平均值)生成关系表示,然后...
The goal of few-shot relation extraction is to predict relations between name entities in a sentence when only a few labeled instances are available for training. Existing few-shot relation extraction methods focus on uni-modal information such as text only. This reduces performance when there are...
nlpdeep-learningpromptpytorchinformation-extractionknowledge-graphnamed-entity-recognitionchinesenermulti-modalkgrelation-extractionlightnerfew-shotlow-resourcedocument-levelattribute-extractionknowpromptdeepkeinstructie UpdatedDec 19, 2024 Python learnables/learn2learn ...
其实也有一些Few Shot Learning的任务，例如我们在2018年构建的FewRel数据集，就是面向Relation Extraction...
15. Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations 会议:ACL 2020. 作者:Samuel Coope, Tyler Farghly, Daniela Gerz, Ivan Vulić, Matthew Henderson 链接:https://www.aclweb.org/anthology/2020.acl-main.11.pdf ...