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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/coronazap/bert_client

https://github.com/cosmoquester/seq2seq

https://github.com/cospplay/bert-master

https://github.com/coxy1989/tfmr

https://github.com/cpm0722/transformer_pytorch

https://github.com/cuber2460/bert

https://github.com/cyberzhg/keras-pos-embd

https://github.com/cyr19/reproducibility

https://github.com/czero69/acomoeye-NN

https://github.com/dalek7/attention

https://github.com/davidalbertonogueira/NLP-tutorials

https://github.com/davisking/dlib-models

https://github.com/dccuchile/CC6204

https://github.com/deepmind/haiku

https://github.com/deepmipt/bert/tree/feat/multi_gpu

https://github.com/demelin/nematode

https://github.com/derylucio/Transformer

https://github.com/dgonzalez-ri/neural-visual-storyteller

https://github.com/dhiraa/tener

https://github.com/dice-group/NABU

https://github.com/dl-nlp/dl-nlp.github.io

https://github.com/dmlc/dgl/tree/master/examples/pytorch/graphwriter

https://github.com/dmlc/gluon-nlp

https://github.com/dqqcasia/st

https://github.com/dreamgonfly/Transformer-pytorch

https://github.com/dreamnotover/english_chinese_machine_translation_baseline

https://github.com/drumpt/Transformer

https://github.com/duyunshu/bert-sentiment-analysis

https://github.com/dyq0811/EEG-Transformer-seq2seq

https://github.com/dzqjorking/transpose

https://github.com/eaplatanios/symphony-mt

https://github.com/eleanorye00/Gamifier

https://github.com/emanuele-progr/PSSP

https://github.com/enhuiz/torchnmt

https://github.com/enhuiz/transformer-pytorch

https://github.com/eric-xw/AREL