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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.

https://github.com/uzi0espil/research-papers-implementation/tree/master/Effective%20Approaches%20to%20Attention-based%20Neural%20Machine%20Translation

Effective Approaches to Attention-based Neural Machine Translation

Data-to-Text Generation

코드

https://github.com/swimmingCreative/DeepSpeechRecognition-master

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

https://github.com/tatp22/linformer-pytorch

https://github.com/tatp22/multidim-positional-encoding

https://github.com/tbmoon/LANL_Earthquake_Prediction

https://github.com/tcnguyen/bert

https://github.com/tcxdgit/MachineTranslation_t2t

https://github.com/tensorops/TransformerX

https://github.com/text-machine-lab/transformerpy

https://github.com/thanhlong1997/bert_quora

https://github.com/the-Quert/iNLPfun

https://github.com/theQuert/inlpfun

https://github.com/thecodemasterk/BERT

https://github.com/thumt/THUMT

https://github.com/thunlp-mt/ckd

https://github.com/tjrwlgns1198/ChatBot

https://github.com/tomdyer10/fake_news

https://github.com/tree-park/kor-to-eng-translation

https://github.com/tree-park/transformer_lm

https://github.com/truclycs/ocr_seq2seq

https://github.com/tshu-w/dbcopilot

https://github.com/tshu-w/llm4em

https://github.com/tvinith/bert

https://github.com/tyxr/bert

https://github.com/u7javed/Transformer-Multi-Language-Translator

https://github.com/ukplab/m-amr2text

https://github.com/umeiko/mindspore-seq2seq

https://github.com/uzi0espil/research-papers-implementation/tree/master/Attention%20Is%20All%20You%20Need

https://github.com/uzi0espil/research-papers-implementation/tree/master/Effective%20Approaches%20to%20Attention-based%20Neural%20Machine%20Translation

https://github.com/vGkatsis/Chat_Bot_DL

https://github.com/valentinmace/noisy-text

https://github.com/vanpersie32/Multigpu-Bert

https://github.com/vanslerry/long_text

https://github.com/varun-bhaseen/Image-caption-generation-using-attention-model

https://github.com/veekaybee/what_are_embeddings

https://github.com/vijay120/bert