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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/majing2019/transformer

https://github.com/manideep2510/siamese-BERT-fake-news-detection-LIAR

https://github.com/maroxtn/tun-sentiment

https://github.com/maxjcohen/transformer

https://github.com/maxmatical/pytorch-projects

https://github.com/maxudong1993/mybert

https://github.com/mayoor/attention_network_experiments

https://github.com/mayurnewase/Quora-Bert

https://github.com/mayurnewase/Translation

https://github.com/mehdibenamorr/Token-Positional-Bias

https://github.com/mehdibenamorr/bert-positional-bias-ner

https://github.com/meizi1114/bert

https://github.com/mhamedLmarbouh/Attention-is-all-you-need

https://github.com/mhaseeb123/DeepMSim

https://github.com/microcoder-py/attn-is-all-you-need

https://github.com/microsoft/onnxruntime-training-examples

https://github.com/mike-a-yen/date-translation

https://github.com/mim-solutions/bert_for_longer_texts

https://github.com/mim-solutions/roberta_for_longer_texts

https://github.com/mindspore-ai/models/tree/master/official/nlp/transformer

https://github.com/mindspore-courses/Deep-Tutorials-for-MindSpore

https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/SelfAttention.py

https://github.com/ming024/FastSpeech2

https://github.com/mithunpaul08/bert_tensorflow

https://github.com/mitran27/Attention-is-all-you-Need

https://github.com/moein-shariatnia/Pix2Seq

https://github.com/monimoyd/NLPEnglishToPythonCodeUsingTransformer

https://github.com/monimoyd/NLPMachineTranslationUsingTransformer

https://github.com/moon23k/Scheduled_Sampling

https://github.com/moon23k/Transformer_Anchors

https://github.com/moon23k/Transformer_Archs

https://github.com/myamamoto555/tf-bert

https://github.com/nachiketaa/bert

https://github.com/nameoverflow/neuro-cangjie

https://github.com/natel9178/transformer-refork

https://github.com/neburseni/NLP