https://github.com/2023-MindSpore-1/ms-code-12
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
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https://github.com/2023-MindSpore-1/ms-code-132
https://github.com/2023-MindSpore-1/ms-code-160
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/MCNN
Multimodal Convolutional Neural Networks for Matching Image and Sentence
https://github.com/2023-MindSpore-1/ms-code-197
https://github.com/2023-MindSpore-1/ms-code-198
https://github.com/2023-MindSpore-1/ms-code-200
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tall
https://github.com/2023-MindSpore-1/ms-code-219/tree/main/albert
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/2023-MindSpore-1/ms-code-220/tree/main/final
https://github.com/2023-MindSpore-1/ms-code-222/tree/main/SGAE
https://github.com/2023-MindSpore-1/ms-code-5/tree/main/gnmt_v2
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
https://github.com/2023-MindSpore-1/ms-code-5/tree/main/lstm_crf
https://github.com/2023-MindSpore-1/ms-code-56
NEZHA: Neural Contextualized Representation for Chinese Language Understanding
https://github.com/2023-MindSpore-1/ms-code-61
https://github.com/2023-MindSpore-1/ms-code-62
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/TNT
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tall
https://github.com/2023-MindSpore-4/Code10/tree/main/DeepText
https://github.com/2023-MindSpore-4/Code12/tree/main/ganleilei/CleanLabelBackdoorAttackMindspore-master
https://github.com/2023-MindSpore-4/Code8/tree/main/cnn_direction_model
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding
https://github.com/2024-MindSpore-1/Code4/tree/main/DeepText
https://github.com/21-projects-for-deep-learning/image2text
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
https://github.com/2281123066/visual-semantic-embedding
Multimodal Convolutional Neural Networks for Matching Image and Sentence
https://github.com/27182812/ChineseBERT_paddle
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information
https://github.com/A-Jacobson/minimal-nmt
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/AI-Mart/distill_lstm
Distilling Task-Specific Knowledge from BERT into Simple Neural Networks
https://github.com/AI4Bharat/indicTrans
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
https://github.com/AMNAALMGLY/NLP
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/AaronCCWong/Show-Attend-and-Tell
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/AbdelMahm/AI4D-MSL-app
Towards A Sign Language Gloss Representation Of Modern Standard Arabic
https://github.com/AbdelMahm/AI4D-data
Towards A Sign Language Gloss Representation Of Modern Standard Arabic
https://github.com/AbhilashaRavichander/NLI_StressTest
https://github.com/Abishalini/LipReadingGUI
https://github.com/AdamStein97/Semi-Supervised-BERT-NER
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
https://github.com/AhmedYounes94/Semi-supervised-BERT-NER
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.