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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/junhahyung/bert_finetune

Attention Is All You Need

https://github.com/junhahyung/bert_transfer

Attention Is All You Need

https://github.com/junjiehu/dali

Domain Adaptation of Neural Machine Translation by Lexicon Induction

https://github.com/justusschock/delira_cycle_gan_pytorch

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/jwieting/beyond-bleu

Beyond BLEU: Training Neural Machine Translation with Semantic Similarity

https://github.com/jxz542189/TCN_classification

An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

https://github.com/k-randl/self-explaining_llms

BARTScore: Evaluating Generated Text as Text Generation

https://github.com/k4black/codebleu

CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

https://github.com/kabongosalomon/listra

Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding

https://github.com/kaikai-sk/char-rnn-chinese

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

https://github.com/kaituoxu/Speech-Transformer

Attention Is All You Need

https://github.com/kaituoxu/SpeechTransformer

Attention Is All You Need

https://github.com/kakaobrain/word2word

word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs

https://github.com/kakaoenterprise/kakaoenterprise.github.io

A Plug-in Method for Representation Factorization in Connectionist Models

https://github.com/kaleidophon/nlp-uncertainty-zoo

Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers

https://github.com/kaletap/language-style-transfer-pytorch

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/kaletap/nlp-experiments

A Probabilistic Formulation of Unsupervised Text Style Transfer

https://github.com/kaletap/nlp-style-transfer

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/kangyeolk/animeceleb

Expression Domain Translation Network for Cross-domain Head Reenactment

https://github.com/kanhereashwin/cs236-project

Unsupervised Image-to-Image Translation Networks

https://github.com/karandesaiii/CheXNet

Learning to diagnose from scratch by exploiting dependencies among labels

https://github.com/karenacorn99/explore-bert

Attention Is All You Need

https://github.com/karl-hajjar/Generative-Adversarial-Networks

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/karlchahine/neural-cover-selection-for-image-steganography

StarGAN v2: Diverse Image Synthesis for Multiple Domains

https://github.com/karpathy/makemore

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

https://github.com/karpathy/minGPT

Attention Is All You Need

https://github.com/karpathy/minbpe

Neural Machine Translation of Rare Words with Subword Units

https://github.com/karshetty/pliks

PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation

https://github.com/karta282950/bert-multiclass

Attention Is All You Need

https://github.com/karthikv792/gpt-plan-benchmark

GPT3-to-plan: Extracting plans from text using GPT-3

https://github.com/kauravin/Neural-Visual-Image-Caption-Generation-using-RNNs-and-LSTMs

Show and Tell: A Neural Image Caption Generator

https://github.com/kaushal-k/Deep-Emotion

Spatial Transformer Networks

https://github.com/kay-ck/bsc-attack

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

https://github.com/kaylode/Clothes-Segmentation

YOLACT: Real-time Instance Segmentation

https://github.com/kaylode/Trash-Segmentation

YOLACT: Real-time Instance Segmentation

https://github.com/keiyamashita111/aaproject

Attention Is All You Need

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