Trending Research
Language Models are Unsupervised Multitask Learners
Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.
COMMON SENSE REASONING DOCUMENT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION QUESTION ANSWERING READING COMPREHENSION
A Style-Based Generator Architecture for Generative Adversarial Networks
• NVlabs/stylegan
• 
We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature.
ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero
• pytorch/ELF
• 
The AlphaGo, AlphaGo Zero, and AlphaZero series of algorithms are a remarkable demonstration of deep reinforcement learning's capabilities, achieving superhuman performance in the complex game of Go with progressively increasing autonomy.
nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
COMMON SENSE REASONING CROSS-LINGUAL NATURAL LANGUAGE INFERENCE NAMED ENTITY RECOGNITION QUESTION ANSWERING
Deep Neural Networks with Box Convolutions
NeurIPS 2018
• shrubb/box-convolutions
•
Box filters computed using integral images have been part of the computer vision toolset for a long time.
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
• google-research/disentanglement_lib
•
On the negative side, we observe in our study that well-disentangled models seemingly cannot be identified without access to ground-truth labels even if we are allowed to transfer hyperparameters across data sets.
Bag of Tricks for Image Classification with Convolutional Neural Networks
• dmlc/gluon-cv
• 
Much of the recent progress made in image classification research can be credited to training procedure refinements, such as changes in data augmentations and optimization methods.
IMAGE CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION TRANSFER LEARNING
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
ICLR 2019
• huggingface/pytorch-pretrained-BERT
•
Transformer networks have a potential of learning longer-term dependency, but are limited by a fixed-length context in the setting of language modeling.
SOTA for Language Modelling on Hutter Prize
Efficient softmax approximation for GPUs
ICML 2017
• huggingface/pytorch-pretrained-BERT
•
We propose an approximate strategy to efficiently train neural network based language models over very large vocabularies.
flair
HLT 2018
• zalandoresearch/flair
•
A very simple framework for state-of-the-art Natural Language Processing (NLP)
COREFERENCE RESOLUTION LANGUAGE MODELLING NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS