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

https://github.com/MinyeLee/Question-Generation-Pytorch

Learning to Ask: Neural Question Generation for Reading Comprehension

https://github.com/MirkoLenz/ReCAP-Argument-Graph-Retrieval

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

https://github.com/Mleader2/text_scalpel

Encode, Tag, Realize: High-Precision Text Editing

https://github.com/MohamedAbdelsalam9/TT-Transformer

A Structured Self-attentive Sentence Embedding

https://github.com/MorningBooks/A_oveview_of_awesome_causality_dataset

Transfer Learning for Causal Sentence Detection

https://github.com/MorningBooks/Causality

Transfer Learning for Causal Sentence Detection

https://github.com/Mrnoorsingh/image-caption

Show and Tell: A Neural Image Caption Generator

https://github.com/Muennighoff/Im2txt

Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge

https://github.com/MulukenW/test

Cross-lingual Information Retrieval with BERT

https://github.com/MysteryVaibhav/SCAN

Stacked Cross Attention for Image-Text Matching

https://github.com/NLPbox/feng-hirst-service

Two-pass Discourse Segmentation with Pairing and Global Features

https://github.com/NUSTM/ABSC

Effective LSTMs for Target-Dependent Sentiment Classification

https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Translation/GNMT

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

https://github.com/NVIDIA/FasterTransformer

Factuality Enhanced Language Models for Open-Ended Text Generation

https://github.com/NVIDIA/NeMo-Curator

Language Models are Few-Shot Learners

https://github.com/NZ99/transformer_in_transformer_flax

Transformer in Transformer

https://github.com/NamanJain2050/sarcasm-detection

A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks

https://github.com/NamanJain2050/semeval-2014-task-9

A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks

https://github.com/NatthanonNon/text-classification-benchmarks

The Annotation Guideline of LST20 Corpus

https://github.com/Negus25/MindSpore-CNN_sentence

Convolutional Neural Networks for Sentence Classification

https://github.com/NehaTamore/abstractive-text-summarizer

Sequence to Sequence Learning with Neural Networks

https://github.com/Neoanarika/torchexplainer

A Structured Self-attentive Sentence Embedding

https://github.com/Neznakomec/ml-project-transformers

Show and Tell: A Neural Image Caption Generator

https://github.com/NicGian/text_VAE

Generating Sentences from a Continuous Space

https://github.com/NicholasKX/ShowAndTell

Show and Tell: A Neural Image Caption Generator

https://github.com/Nick-Zhao-Engr/Machine-Translation

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/Nirvanabc/sentence_classification

Convolutional Neural Networks for Sentence Classification

https://github.com/Nirvanabc/seq2seq-rnn

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

https://github.com/NonameAuPlatal/Dual_Learning

Dual Learning for Machine Translation

https://github.com/OPAYA/Transformer

A Structured Self-attentive Sentence Embedding

https://github.com/OanaMariaCamburu/e-SNLI

e-SNLI: Natural Language Inference with Natural Language Explanations

https://github.com/OctopusMind/longBert

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/OperaGraecaAdnotata/OGA

Opera Graeca Adnotata: Building a 34M+ Token Multilayer Corpus for Ancient Greek

https://github.com/PDas2206/BERT_emotion_analysis

EmotionX-IDEA: Emotion BERT -- an Affectional Model for Conversation

https://github.com/PJamesY/category_classification-NLP-

Convolutional Neural Networks for Sentence Classification

https://github.com/PKU-ICST-MIPL/MCSM_TIP2018

Modality-specific Cross-modal Similarity Measurement with Recurrent Attention Network

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.