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

https://github.com/distractor-generation/dg_survey

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/dkman94/FastrApp-Android

Learning to detect dysarthria from raw speech

https://github.com/dksifoua/Neural-Machine-Translation

Sequence to Sequence Learning with Neural Networks

https://github.com/dltcls/g2p_pytorch_wiktionary

Sequence to Sequence Learning with Neural Networks

https://github.com/dltmddbs100/SimCSE

SimCSE: Simple Contrastive Learning of Sentence Embeddings

https://github.com/dmis-lab/liquid

Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning

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

Text Generation from Knowledge Graphs with Graph Transformers

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

Convolutional Neural Networks for Sentence Classification

https://github.com/dmlls/negate

This is not correct! Negation-aware Evaluation of Language Generation Systems

https://github.com/dmmiller612/bert-extractive-summarizer

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/dongdong199408/teachchatrobot

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/donghyeonk/match-lstm

Learning Natural Language Inference with LSTM

https://github.com/dongjun-Lee/text-classification-models-tf

Convolutional Neural Networks for Sentence Classification

https://github.com/doragd/text-classification-pytorch

A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

https://github.com/dougsouza/efficient-t2i

Efficient Neural Architecture for Text-to-Image Synthesis

https://github.com/dsfsi/textaugment

Augmenting Data with Mixup for Sentence Classification: An Empirical Study

https://github.com/dsindex/iclassifier

Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence Embedding

https://github.com/dujiaxin/semanticRetrievalMRS

Revealing the Importance of Semantic Retrieval for Machine Reading at Scale

https://github.com/duynguyen158/wann-nlp

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

https://github.com/duyvuleo/Transformer-DyNet

Incorporating Discrete Translation Lexicons into Neural Machine Translation

https://github.com/dwright37/phylogenetic-autoencoder

Skip-Thought Vectors

https://github.com/dyashkir/todo-ideas-links

Calculating the similarity between words and sentences using a lexical database and corpus statistics

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

Effective Approaches to Attention-based Neural Machine Translation

https://github.com/earth-insights/ClassTrans

Aligning and Prompting Everything All at Once for Universal Visual Perception

https://github.com/edchengg/transfusion

Frustratingly Easy Label Projection for Cross-lingual Transfer

https://github.com/edisutoyo/satd-augmentation

AugGPT: Leveraging ChatGPT for Text Data Augmentation

https://github.com/eelenadelolmo/WordVectors

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/eilon47/DL_Ass4

Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference

https://github.com/elaynelemos/gector-api

LM-Critic: Language Models for Unsupervised Grammatical Error Correction

https://github.com/ellerypan/QUORA-INSINCERE-QUESTION-CLASSIFICATION

Dynamic Meta-Embeddings for Improved Sentence Representations

https://github.com/elliottd/compareImageDescriptionMeasures

CIDEr: Consensus-based Image Description Evaluation

https://github.com/epfml/collaborative-attention

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

https://github.com/epwalsh/pytorch-crf

Bidirectional LSTM-CRF Models for Sequence Tagging

https://github.com/eric11eca/NeuralLog

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

https://github.com/ericlee8/space

Semantic-Preserving Adversarial Text Attacks

https://github.com/esadsetts/Mod_4_project

A Structured Self-attentive Sentence Embedding

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