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The Best of Applied Artificial Intelligence, Machine Learning, Automation, Bots, Chatbots

Natural Language Processing

Discovering the Encoded Linguistic Knowledge in NLP Models

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This article is authored by Keyur Faldu and Dr. Amit Sheth. This article elaborates on a niche aspect of the broader cover story on “Rise of Modern NLP and the Need of Interpretability!”At Embibe, we desiderate answers to the open questions while we build the NLP platform to solve numerous problems for the academic content. Modern NLP models (BERT, GPT, … [Read more...] about Discovering the Encoded Linguistic Knowledge in NLP Models

NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer

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Advances in Deep Learning research are of great utility for a Deep Learning engineer working on real-world problems as most of the Deep Learning research is empirical with validation of new techniques and theories done on datasets that closely resemble real-world datasets/tasks (ImageNet pre-trained weights are still useful!). But, churning a vast amount of … [Read more...] about NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer

The Curious Case of Developmental BERTology

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This essay is written for machine learning researchers and neuroscientists (some jargons in both fields will be used). Though it is not intended to be a comprehensive review of literature, we will take a tour through a selection of classic work and new results from a range of topics, in an attempt to develop the following thesis: Just like the fruitful interaction between … [Read more...] about The Curious Case of Developmental BERTology

NeurIPS 2020: Key Research Papers in Natural Language Processing (NLP) & Conversational AI

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NeurIPS is the largest machine learning conference held every December. It brings together researchers in computational neuroscience, reinforcement learning, deep learning, and their applications such as computer vision, fairness and transparency, natural language processing, robotics, and more. Our team reviewed the papers accepted to NeurIPS 2020 and shortlisted the most … [Read more...] about NeurIPS 2020: Key Research Papers in Natural Language Processing (NLP) & Conversational AI

GPT-3 & Beyond: 10 NLP Research Papers You Should Read

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NLP research advances in 2020 are still dominated by large pre-trained language models, and specifically transformers. There were many interesting updates introduced this year that have made transformer architecture more efficient and applicable to long documents. Another hot topic relates to the evaluation of NLP models in different applications. We still lack evaluation … [Read more...] about GPT-3 & Beyond: 10 NLP Research Papers You Should Read

Natural Language Processing in Production: 27 Fast Text Pre-Processing Methods

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Estimates state that 70%–85% of the world’s data is text (unstructured data) [1]. New deep learning language models (transformers) have caused explosive growth in industry applications [5,6,11]. This blog is not an article introducing you to Natural Language Processing. Instead, it assumes you are familiar with noise reduction and normalization of text. It covers … [Read more...] about Natural Language Processing in Production: 27 Fast Text Pre-Processing Methods

The Relationship Between Perplexity And Entropy In NLP

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Perplexity is a common metric to use when evaluating language models. For example, scikit-learn’s implementation of Latent Dirichlet Allocation (a topic-modeling algorithm) includes perplexity as a built-in metric. In this post, I will define perplexity and then discuss entropy, the relation between the two, and how it arises naturally in natural language … [Read more...] about The Relationship Between Perplexity And Entropy In NLP

3 NLP Interpretability Tools For Debugging Language Models

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With constant advances and unprecedented performance on many NLP tasks, language models have gotten really complex and hard to debug. Researchers and engineers often can’t easily answer questions like:  Why did your model make that prediction?   Does your model have any algorithmic biases? What kind of data samples does your model perform poorly … [Read more...] about 3 NLP Interpretability Tools For Debugging Language Models

Highlights of ACL 2020

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ACL Trends Visualization by Wanxiang Che With ACL becoming virtual this year, I unfortunately spent less time networking and catching up with colleagues, but as a silver lining I watched many more talks than I usually do. I decided to share the notes I took and discuss some overall trends. The list is not exhaustive, and is based on my research interests. I recommend also … [Read more...] about Highlights of ACL 2020

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