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attrcnn-cnns icon attrcnn-cnns

论文介绍:针对已有模型不能充分提取语义特征,以及单一使用语义或语言学特征来进行预测等不足,使用BERT预训练模型进行句子层面的特征提取。同时阅读了关于多模态以及特征融合的论文,使用LSTM-Attention和CNN进行文档层面特征提取,同时结合Mairesse语言学特征,将多个层面提取的特征融合起来进行分析,最终使用Pytorch进行模型实现。

awesome-gcn icon awesome-gcn

resources for graph convolutional networks (图卷积神经网络相关资源)

ddshop icon ddshop

叮咚买菜自动抢购下单程序

hedwig icon hedwig

PyTorch deep learning models for document classification

lw-pt icon lw-pt

Dataset and code for "Label-Wise Document Pre-Training for Multi-Label Text Classification" (NLPCC 2020)

patent-classification icon patent-classification

PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT

twinbert icon twinbert

pytorch implementation of the TwinBert paper

wordgcn icon wordgcn

ACL 2019: Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

x-transformer icon x-transformer

X-Transformer: Taming Pretrained Transformers for eXtreme Multi-label Text Classification

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