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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.
https://github.com/ArvidWartenberg/retrosynthesis
https://github.com/ArvinZhuang/BiTAG
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/ArvindSridhar/AbstractiveTextSummarization
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/AssafSinger94/sigmorphon-2020-inflection
https://github.com/AtluriNikhil/Image-Captioning
https://github.com/Aveek-Saha/Transformer
https://github.com/BBuf/GLM
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
https://github.com/BasileBron/Artificial-Intelligence-Lexical
https://github.com/Belval/NRTR
https://github.com/Bhavnicksm/vanilla-transformer-jax
https://github.com/BonanKou/ASSORT-Automatic-Summarization-of-Stack-Overflow-Posts
https://github.com/Bread-and-Code/Text-Summarization
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
https://github.com/BrianPulfer/PapersReimplementations
https://github.com/CGCL-codes/naturalcc
https://github.com/CVxTz/music_genre_classification
https://github.com/Caesarzhang/bert-zh
https://github.com/Chang-Chia-Chi/SaintPlus-Knowledge-Tracing-Pytorch
https://github.com/Charliesgithub20221030/BERT
https://github.com/Chen-Wang-CUHK/DialSum-with-SUFM-and-FR
SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
https://github.com/ChernovAndrey/chronos-forecasting-wasserstein
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/Chinnu1103/Machine-Translation-using-Transformers
https://github.com/Chonwai/Learning_BERT
https://github.com/Colanim/BERT_STS-B
https://github.com/DJJune/Transformer
https://github.com/DanielaStep/SC
Scoring Sentence Singletons and Pairs for Abstractive Summarization
https://github.com/DanielaStep/sentence_similarity_rouge
Scoring Sentence Singletons and Pairs for Abstractive Summarization
https://github.com/DanieleVeri/deep_comedy
https://github.com/DataScienceNigeria/SummAE-from-Google-Brain-and-MIT-CSAIL
SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders
https://github.com/Dave870907/Transformer
https://github.com/DeligientSloth/QQsim
https://github.com/DeligientSloth/bert-tensorflow
https://github.com/Delta-ML/delta
https://github.com/DeokO/bert-excercise-ongoing
https://github.com/DevSinghSachan/multilingual_nmt
https://github.com/Doffery/BERT-Sentiment-Analysis-Amazon-Review
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.