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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/hyunwoongko/asian-bart

Multilingual Denoising Pre-training for Neural Machine Translation

https://github.com/hyunwoongko/transformer

Multi30K: Multilingual English-German Image Descriptions

https://github.com/hz-ants/SilhoNet

SilhoNet: An RGB Method for 6D Object Pose Estimation

https://github.com/hz-ants/yolact

YOLACT: Real-time Instance Segmentation

https://github.com/i-machine-think/machine-tasks

Generalization without systematicity: On the compositional skills of sequence-to-sequence recurrent networks

https://github.com/i2r-simmc/i2r-simmc-2020

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/i404788/DPFP-pytorch

Linear Transformers Are Secretly Fast Weight Programmers

https://github.com/iamjanvijay/rnnt_decoder_cuda

Sequence Transduction with Recurrent Neural Networks

https://github.com/iamyuanchung/Autoregressive-Predictive-Coding

Generative Pre-Training for Speech with Autoregressive Predictive Coding

https://github.com/iankuoli/DFNet_TF2

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

https://github.com/ibraheem-moosa/xlm-indic

The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation

https://github.com/icewing1996/bert_dep

Attention Is All You Need

https://github.com/ictmcg/endef-sigir2022

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

https://github.com/ictnlp/LSG

Agent-SiMT: Agent-assisted Simultaneous Machine Translation with Large Language Models

https://github.com/idiotprofessorchen/bert.github.io

Attention Is All You Need

https://github.com/idsia/modern-srwm

Linear Transformers Are Secretly Fast Weight Programmers

https://github.com/idsia/neuraldiffeq-fwp

Linear Transformers Are Secretly Fast Weight Programmers

https://github.com/iejMac/ScriptWriter

Attention Is All You Need

https://github.com/iinemo/lm-polygraph

Uncertainty Estimation in Autoregressive Structured Prediction

https://github.com/ijauregiCMCRC/ReWE_NMT

Stronger Baselines for Trustable Results in Neural Machine Translation

https://github.com/ikergarcia1996/Iker-Garcia-Ferrero

Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings

https://github.com/ikergarcia1996/Simultaneous-Machine-Translation

Attention Is All You Need

https://github.com/imamathcat/LASER_Dependencies

Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings

https://github.com/imatge-upc/vqa-2016-cvprw

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus

https://github.com/imperialnlp/vtlm

Cross-lingual Visual Pre-training for Multimodal Machine Translation

https://github.com/indobenchmark/indobenchmark-toolkit

IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation

https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning

Device Placement Optimization with Reinforcement Learning

https://github.com/inesylla/energy-disaggregation-DL

Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network

https://github.com/inmoonlight/confcrawl

Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate Layers

https://github.com/insigh/THUMT

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/insop/pytorch-hackathon

Transformers with convolutional context for ASR

https://github.com/interdigitalinc/featurestyleencoder

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/inzva/fake-academic-paper-generation

Tensor2Tensor for Neural Machine Translation

https://github.com/ipieter/universal-distillation

Masked Language Model Scoring

https://github.com/ishritam/Image-captioning-with-visual-attention

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

https://github.com/isl-mt/OpenNMT

OpenNMT: Open-Source Toolkit for Neural Machine Translation

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