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Song Lyric Toxicity, Commit Assistant, NLP Progress, DensePose, PyTorch Geometric,…


Welcome to the 18th Issue of the NLP Newsletter! Here is this week’s notable NLP news! Today we have a lot of open datasets, computational health studies, bias and ethics for AI, transfer learning for both computer vision and NLP tasks, and much more.

On People and Society
On safety standards for AI systems and factors to consider (opinion piece) - Link

You think it’s possible to learn accurate cognitive models with no data and little to no human knowledge engineering? If you are curious you will find this work interesting - Link

Christopher Manning talks about neural network that can reason (Video) - Link

Very nice repository to check the current progress of NLP related tasks and research - Link

Learn about the latest work on interpretable machine learning research - Link

Deep Learning for NLP: PyTorch vs Tensorflow (Video) - Link

On Education and Research…
ICYMI, here is the latest work on transfer learning for NLP by OpenAI - Link

Another paper on transfer learning about how to uncover the cluster and relationships (disentangle) between computer vision tasks - Link

A novel spatio-textual clustering algorithm for clustering tweets using heterogeneous data - Link

Detecting social network mental disorders, such as internet overload and net compulsion, through tensor decomposition - Link

On how to learn joint multimodal embedding space with unpaired text and video data - Link

Results are in for the Retro Contest hosted by OpenAI - Link

Learn about how a bidirectional-asynchronous framework is leveraged to generate meaningful emotional replies in conversations (something traditional language models fail to achieve due to generic replies) - Link

On Code and Data…

Here’s a cool website where you can search for machine learning papers that have open source code - Link

A song lyric toxicity dataset is made available accompanied by analysis and slides - Link

An impressive study on how to collect high-quality data through search queries in developing nations, which may have some serious health benefits for society - Link

Code for adversarial training methods for semi-supervised text classification - Link

DeepMind open sources their dataset used to train the generative query networks (GQNs) for neural scene representation and rendering - Link

How to efficient train sequence to sequence models for neural machine translation with Tensorflow (Colab tutorial) - Link

PyTorch Geometric is a tool for implementing geometric deep learning with PyTorch - Link

On Industry…
Here is an AI-based tool that helps make it easier to code video games. The new tool, named Commit Assistant, is offered by Ubisoft - Link

The Facebook research team introduces DensePose, a real-time approach for mapping human pixels from 2D images to 3D surface model of a human body - Link

Understanding emotions for customer support — Link

Detecting sarcasm with deep convolutional neural networks - Link

Learn more about how researchers are making machine learning algorithms fair - Link

Quotes of the day…

Thanks Sebastian for making our lives easier! Deeply appreciate this effort.

Illustrations of the day…

Poster on teaching machines with human language rather than labels - Link

Worthy Mentions…
Sebastian Ruder NLP Newsletter (Issue #26) - Link

Deep Learning for NLP (Lecture slides) - Link

Workshop on deep reinforcement learning (Video presentations) - Link

Learn more about bias and variance in machine learning with very neat visualizations - Link

If you spot any errors or inaccuracies in this newsletter please open an issue. Submit a pull request if you would like to add important NLP news here.