前段时间用过预训练模型ERNIE-1.0 做过一些NLP方面的小实践,并读过对应的论文,在此对行文结构进行梳理,并在最后对ERNIE预训练模型进行总结。 1.Introduction:(1)预训练语言表达模型(Pre-trained language repre…
The leaves on the tree represent all the words in the vocabulary. We consider the process of calculating conditional probabilities as the softmax of dot product of node embedding and word embedding from root to leaf node. (wIwIindicates the input word). We consider the process of calculating t...
The leaves on the tree represent all the words in the vocabulary. We consider the process of calculating conditional probabilities as the softmax of dot product of node embedding and word embedding from root to leaf node. (\(w_I\) indicates the input word). We consider the process of calc...
The aim of context- independent representations is to encode properties related to single tokens, discarding the syntactic relations between them. However, a dynamic representation considering the information of the nearby words is the advantage of the context-aware methods. In particular, contextualized...
The commonly used improvement ideas mainly include two parts: the improvement of training strategy and the improvement of model structure. This section will introduce and summarize the research status of AE-based representation learning in the industrial process according to the different requirements of...
Word representation, aiming to represent a word with a vector, plays an essential role in NLP. In this chapter, we first introduce several typical word representation learning methods, including one-hot representation and distributed representation. Afte
(2)structure-aware tasks:学习syntactic information Sentences Reordering:一段话被划分成n\in [1,m]句话,将这n句话随机排列之后,让模型还原正确顺序,可以将其建模成k分类问题,其中k=\sum_{n=1}^{m}{n!} Sentences Distance: 被建模成了三分类任务,“0”表示两个句子在同一个document中并且相邻,“1”表...
In graph-level representation learning tasks, graph neural networks have received much attention for their powerful feature learning capabilities. However, with the increasing scales of graph data, how to efficiently process and extract the key information has become the focus of research. The graph ...
Russo, P.Velardi, Representation and Control Strategies for large Knowledge Domains : an Application to NLP, Journal of Applied Artificial Intelligence, in print 1988.F. Antonacci, M. Russo, M.T. Pazienza, and P. Velardi. Representation and Control Strategies for large Knowledge Domains: An ...
Syntactic TrDep Checking whether an encoder infers the hierarchical structure of sentence Syntactic ToCo Sentences should be classified in terms of the sequence of top constituents immediately below the sentence node Syntactic BShif Testing whether two consecutive tokens within the sentence have been inver...