Papers with Code 아카이브
Story Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 5
- 보존된 평가 기록
- 5
Story generation is the task of automatically generating a coherent narrative, often from a set of premises or a brief summary.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Remiphilius/PoemesProfonds
https://github.com/RenXiangyuan/tf_bert
https://github.com/Rudedaisy/attention-is-all-you-need-pytorch
https://github.com/SCismycat/bert_code_view
https://github.com/SYangDong/bert-with-frozen-code
https://github.com/Satan012/BERT
https://github.com/ScientiaEtVeritas/NeuralMachineTranslation
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/SeoroMin/transformer_pytorch
https://github.com/SeoroMin/transformer_pytorch_ver2
https://github.com/Shasvat-Desai/Shasvat-Desai
https://github.com/Shinya-Kouda/kgc
https://github.com/ShivamRajSharma/Transformer-Architectures-From-Scratch
https://github.com/Shubham-SK/TreeOverAte
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/Shubham-SK/kronos
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/ShuvenduBikash/transformer_spelling_corrector
https://github.com/ShwetaBaranwal/Transformer
https://github.com/Skumarr53/Attention-is-All-you-Need-PyTorch
https://github.com/SpikeKing/My-Bert
https://github.com/StevenLai1994/AM_and_LM
https://github.com/StillKeepTry/Transformer-PyTorch
https://github.com/StoneGH/bert
https://github.com/T9-LIN/MSc-Project
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/THUNLP-MT/THUMT
https://github.com/TSLNIHAOGIT/bert
https://github.com/TSLNIHAOGIT/bert_run
https://github.com/TYTYTYTYTYTYTYTYTY/558-project
https://github.com/The-AI-Summer/self_attention
https://github.com/TheTensorDude/transformer-tf
https://github.com/TieDanCuihua/transformer-Attention-is-All-You-Need
https://github.com/TonyX19/bert_hyperpartisan
https://github.com/UdbhavPrasad072300/Transformer-Implementation
https://github.com/UdbhavPrasad072300/Transformer-Implementation-and-Language-Translation
https://github.com/UdbhavPrasad072300/Transformer-Implementations
https://github.com/VedantYadav/Transformer
https://github.com/Walter-B/bert-20-classes
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.