https://github.com/tensorflow/models/tree/master/research/textsum
A Neural Attention Model for Abstractive Sentence Summarization
Papers with Code 아카이브
Extractive Text Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 5
- 보존된 평가 기록
- 22
Given a document, selecting a subset of the words or sentences which best represents a summary of the document.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/thangarani/bertsum
https://github.com/theamrzaki/text_summurization_abstractive_methods
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/threelittlemonkeys/pointer-network-pytorch
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/thswodnjs3/CSTA
Align and Attend: Multimodal Summarization with Dual Contrastive Losses
https://github.com/toru34/rush_emnlp_2015
A Neural Attention Model for Abstractive Sentence Summarization
https://github.com/uabinf/nlp-fall-2019-project-anuradha_shinjitha
https://github.com/vsubramaniam851/typ_embed
https://github.com/wyu97/permgen
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/zhdbwe/Paper-DailyReading
Searching for Effective Neural Extractive Summarization: What Works and What's Next
https://github.com/zide05/pointer-gen-fastnlp
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.