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Abstractive Text Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 20
- 보존된 평가 기록
- 98
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/jananiarunachalam/Research-Paper-Summarization
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https://github.com/jbdel/OMG_UMONS_submission
https://github.com/jean-kunz/ml_research_papers
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https://github.com/jeongchanyoung-1234/De-En-NMT
https://github.com/jgcbrouns/Introducing-Sparsity-in-the-Transformer
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Unified Language Model Pre-training for Natural Language Understanding and Generation
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Get To The Point: Summarization with Pointer-Generator Networks
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Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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https://github.com/karta282950/bert-multiclass
https://github.com/kashgupta/textsummarization
Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond
https://github.com/keiyamashita111/aaproject
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.