https://github.com/Maluuba/mctest-model
A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Mandar-Sharma/TCube
https://github.com/ManuelVs/NNForTextClassification
https://github.com/ManuelVs/NeuralNetworks
https://github.com/MariBax/Paraphrase-Identification
Bilateral Multi-Perspective Matching for Natural Language Sentences
https://github.com/Matthewdowney18/Yelp_attention
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/Matthewdowney18/Yelp_seq2seq
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/MayukhSobo/Conv4RNN
https://github.com/Mind23-2/MindCode-131
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/Mind23-2/MindCode-138
https://github.com/Mind23-2/MindCode-145
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
https://github.com/Mind23-2/MindCode-156
LXMERT: Learning Cross-Modality Encoder Representations from Transformers
https://github.com/Mind23-2/MindCode-159
https://github.com/Mind23-2/MindCode-166
Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
https://github.com/Mind23-2/MindCode-34
https://github.com/Mind23-2/MindCode-73
https://github.com/MindCode-4/code-13/tree/main/Three-Dimensional-Lip-Motion-Network-for-Text-Independent-Speaker-Recognition-master
Three-Dimensional Lip Motion Network for Text-Independent Speaker Recognition
https://github.com/MindCode-4/code-4/tree/main/realm
https://github.com/MindCode-4/code-9/tree/main/Three-Dimensional-Lip-Motion-Network-for-Text-Independent-Speaker-Recognition-master
Three-Dimensional Lip Motion Network for Text-Independent Speaker Recognition
https://github.com/MindCode-4/code-9/tree/main/Two-Layer-ReLU-Network-Analytically
Three-Dimensional Lip Motion Network for Text-Independent Speaker Recognition
https://github.com/MindSpore-paper-code-2/code3/tree/main/tall
https://github.com/MindSpore-paper-code-2/code399/tree/main/dscnn
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents
https://github.com/MindSpore-paper-code-2/code400/tree/main/DeepText
https://github.com/MindSpore-paper-code-3/code6/tree/main/cnn_direction_model
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding
https://github.com/MindSpore-paper-code-3/code9/tree/main/DeepText
https://github.com/MindSpore-paper-code-3/code9/tree/main/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/MindSpore-paper-code-3/code9/tree/main/gnmt_v2
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/MindSpore-paper-code-3/code9/tree/main/lstm_crf
https://github.com/MindSpore-paper-code-3/code9/tree/main/mass
MASS: Masked Sequence to Sequence Pre-training for Language Generation
https://github.com/MindSpore-paper-code-3/code9/tree/main/seq2seq
https://github.com/MindSpore-paper-code-3/code9/tree/main/textcnn
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/MindSpore-scientific/code-10/tree/main/nystrom-attention
Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding
https://github.com/MindSpore-scientific/code-11/tree/main/Least_Generative
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
https://github.com/MindSpore-scientific/code-12/tree/main/Hyena-A-Convolutional-Neural-Network-for-Modelling-Sentences
https://github.com/MingyuLi19910814/C-LSTM-Tensorflow
https://github.com/MingyuLi19910814/Convolutional-Neural-Networks-for-Sentence-Classification-tf2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.