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Data-to-Text Generation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 3
평가표: 26
보존된 평가 기록: 122

A classic problem in natural-language generation (NLG) involves taking structured data, such as a table, as input, and producing text that adequately and fluently describes this data as output. Unlike machine translation, which aims for complete transduction of the sentence to be translated, this form of NLG is usually taken to require addressing (at least) two separate challenges: what to say, the selection of an appropriate subset of the input data to discuss, and how to say it, the surface realization of a generation.

<span style="color:grey; opacity: 0.6">( Image credit: Data-to-Text Generation with Content Selection and Planning )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

Data-to-Text Generation

코드

https://github.com/iejMac/ScriptWriter

https://github.com/ikergarcia1996/Simultaneous-Machine-Translation

https://github.com/insigh/THUMT

https://github.com/ishritam/Image-captioning-with-visual-attention

https://github.com/jackjhliu/End-to-End-Mandarin-ASR

https://github.com/jackjhliu/Pytorch-End-to-End-ASR-on-TIMIT

https://github.com/jadore801120/attention-is-all-you-need-pytorch

https://github.com/jageshmaharjan/BERT_Service

https://github.com/jaisenbe58r/NLP-Transformer_Translator

https://github.com/jamesdvance/predicting_clicks

https://github.com/jangjoongkeon/JK

https://github.com/jbdel/OMG_UMONS_submission

https://github.com/jean-kunz/ml_research_papers

https://github.com/jelifysh/Transformers

https://github.com/jeongchanyoung-1234/De-En-NMT

https://github.com/jgcbrouns/Introducing-Sparsity-in-the-Transformer

https://github.com/jiahuei/Self-Critical-SCST-TensorFlow

https://github.com/jinzhenfan/BERT

https://github.com/jmnolte/hccnet

https://github.com/jmyrberg/finnlem

https://github.com/joebluems/Soul_Of_AI

https://github.com/joongbo/tta

https://github.com/joytianya/google_bert

https://github.com/jugalw13/Red-Hat-Hack

https://github.com/junhahyung/bert_finetune

https://github.com/junhahyung/bert_transfer

https://github.com/kaituoxu/Speech-Transformer

https://github.com/kaituoxu/SpeechTransformer

https://github.com/karenacorn99/explore-bert

https://github.com/karpathy/makemore

https://github.com/karpathy/minGPT

https://github.com/karta282950/bert-multiclass

https://github.com/keiyamashita111/aaproject

https://github.com/kelly2016/multi-label-bert

https://github.com/keonlee9420/Parallel-Tacotron2

https://github.com/kh-kim/simple-nmt