natural-language-processing-5

Translation

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in translation-5

Trend

Dataset

Best Model

Actions

MuLD (OpenSubtitles)

Oxford Radar RobotCar Dataset

Libraries

i

Use these libraries to find translation-5 models and implementations

awslabs/sockeye

25 papers 1,206

Datasets

WMT 2016

xP3

CVSS

Oxford Radar RobotCar Dataset

Duolingo STAPLE Shared Task

Subtasks

No subtasks available.

Most implemented papers

Attention is All you Need

Noam Shazeer, Ashish Vaswani, Lukasz Kaiser, Jakob Uszkoreit, Niki Parmar, I. Polosukhin, Llion Jones, Aidan N. Gomez•Sun Jun 11 2017

A new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely is proposed, which generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.

164803

Content

pytorch/fairseq

18 papers 29,233

huggingface/transformers

13 papers 124,889

facebookresearch/fairseq

11 papers 29,237

bzhangGo/zero

11 papers 145

hlt-mt/fbk-fairseq

11 papers 28

tensorflow/tensor2tensor

10 papers 14,881

marian-nmt/marian

9 papers 1,170

eriklindernoren/PyTorch-GAN

7 papers 15,701

espnet/espnet

7 papers 7,871

joeynmt/joeynmt

7 papers 656

Unbabel/COMET

7 papers 396

mgaido91/FBK-fairseq-ST

7 papers 19

bytedance/neurst

6 papers 293

faceonlive/ai-research

6 papers 144

google/sentencepiece

5 papers 9,472

facebookresearch/MUSE

5 papers 3,167

5 papers 691

5 papers 691

5 papers 533

5 papers 126

cordercorder/knn-models

5 papers 28

microsoft/unilm

4 papers 18,315

makcedward/nlpaug

4 papers 4,299

facebookresearch/CodeGen

4 papers 673

sooftware/nlp-attentions

4 papers 480

Demetr

0

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

Phillip Isola, Alexei A. Efros, Jun-Yan Zhu, Taesung Park•Wed Mar 29 2017

This work presents an approach for learning to translate an image from a source domain X to a target domain Y in the absence of paired examples, and introduces a cycle consistency loss to push F(G(X)) ≈ X (and vice versa).

5621 0

Paper Graph

Neural Machine Translation by Jointly Learning to Align and Translate

Yoshua Bengio, Kyunghyun Cho, Dzmitry Bahdanau•Sun Aug 31 2014

It is conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and it is proposed to extend this by allowing a model to automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word, without having to form these parts as a hard segment explicitly.

28857 0

Paper Graph

Image-to-Image Translation with Conditional Adversarial Networks

Phillip Isola, Alexei A. Efros, Jun-Yan Zhu, Tinghui Zhou•Sun Nov 20 2016

Conditional adversarial networks are investigated as a general-purpose solution to image-to-image translation problems and it is demonstrated that this approach is effective at synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks.

21622 0

Paper Graph

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

R. Zemel, Yoshua Bengio, Aaron C. Courville, Kyunghyun Cho, R. Salakhutdinov, Jimmy Ba, Ryan Kiros, Ke Xu•Mon Feb 09 2015

An attention based model that automatically learns to describe the content of images is introduced that can be trained in a deterministic manner using standard backpropagation techniques and stochastically by maximizing a variational lower bound.

10628 0

Paper Graph

Show and tell: A neural image caption generator

O. Vinyals, Samy Bengio, D. Erhan, Alexander Toshev•Sun Nov 16 2014

This paper presents a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image.

6333 0

Paper Graph

R-FCN: Object Detection via Region-based Fully Convolutional Networks

Kaiming He, Jifeng Dai, Yi Li•Thu May 19 2016

This work presents region-based, fully convolutional networks for accurate and efficient object detection, and proposes position-sensitive score maps to address a dilemma between translation-invariance in image classification and translation-variance in object detection.

5948 0

Paper Graph

YOLACT: Real-Time Instance Segmentation

Yong Jae Lee, Fanyi Xiao, Chong Zhou, Daniel Bolya•Wed Apr 03 2019

A simple, fully-convolutional model for real-time instance segmentation that achieves 29.8 mAP on MS COCO at 33.5 fps evaluated on a single Titan Xp, which is significantly faster than any previous competitive approach.

1996 0

Paper Graph

Effective Approaches to Attention-based Neural Machine Translation

Christopher D. Manning, Thang Luong, Hieu Pham•Sun Aug 16 2015

A global approach which always attends to all source words and a local one that only looks at a subset of source words at a time are examined, demonstrating the effectiveness of both approaches on the WMT translation tasks between English and German in both directions.

8298 0

Paper Graph

Regularizing and Optimizing LSTM Language Models

N. Keskar, R. Socher, Stephen Merity•Sun Aug 06 2017

This paper proposes the weight-dropped LSTM which uses DropConnect on hidden-to-hidden weights as a form of recurrent regularization and introduces NT-ASGD, a variant of the averaged stochastic gradient method, wherein the averaging trigger is determined using a non-monotonic condition as opposed to being tuned by the user.

1149 0

Paper Graph

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