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Abstractive Text Summarization
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Abstractive Text Summarization is the task of generating a short and concise summary that captures the salient ideas of the source text. The generated summaries potentially contain new phrases and sentences that may not appear in the source text.
Source: Generative Adversarial Network for Abstractive Text Summarization
Image credit: Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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https://github.com/UdbhavPrasad072300/Transformer-Implementation
https://github.com/UdbhavPrasad072300/Transformer-Implementation-and-Language-Translation
https://github.com/UdbhavPrasad072300/Transformer-Implementations
https://github.com/Ujwal0404/Pointer-Generator-Network
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/VD44/Rouge-L-Tensorflow
https://github.com/VedantYadav/Transformer
https://github.com/Walter-B/bert-20-classes
https://github.com/WenYanger/General-Transformer-Pytorch
https://github.com/WenjieDu/PyPOTS
https://github.com/WolfNiu/AdversarialDialogue
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/Wolfie8935/Implementation-of-Attention-is-all-you-need
https://github.com/XINZXZHANG/Bert_repo
https://github.com/XUJitao/WordEmbedding
https://github.com/XapaJIaMnu/transformative
https://github.com/Xinsen-Zhang/transformer
https://github.com/XuhanLiu/Transformer
https://github.com/YYGXjpg/BERT_WL
https://github.com/Yipeng91/text_classifier_pub
https://github.com/YuanEric88/bert-nlu
https://github.com/YunwenTechnology/Unilm
Unified Language Model Pre-training for Natural Language Understanding and Generation
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https://github.com/ZurichNLP/sockeye
https://github.com/a414351664/Bert_MRC
https://github.com/a414351664/my_git_laser
https://github.com/aaronH45/sentimentAnalysis
https://github.com/abelriboulot/onnxt5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture
https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture/blob/main/Transformer.py
https://github.com/abhaskumarsinha/MinimalGPT
https://github.com/abhiagg92/bert_sentiment
https://github.com/abhilash1910/LongPegasus
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
https://github.com/abhilashreddys/Fake-News-Article
https://github.com/abisee/cnn-dailymail
Get To The Point: Summarization with Pointer-Generator Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.