Learning without Labels

Michael Sollami · #deeplearning

With data rapidly being generated by millions of people, it's not feasible to label all of it. Learn about the recent advancements in ML for how to train vision models with unlabelled data using self-supervised learning.

Salesforce Research at EMNLP 2020

Denna Mafie · #research

This year marks the 24th annual Empirical Methods in Natural Language Processing (EMNLP) conference reimagined for the first time ever in a fully virtual format. EMNLP is a leading conference in the area of Natural Language Processing covering a broad spectrum of diverse research areas that are concerned with computational

ERASER: A Benchmark to Evaluate Rationalized NLP Models

Nazneen Rajani · #research

Many NLP applications today deploy state-of-the-art deep neural networks that are essentially black-boxes. One of the goals of Explainable AI (XAI) is to have AI models reveal why and how they make their predictions so that these predictions are interpretable by a human. But work in this direction has been

The Natural Language Decathlon

Bryan McCann · #research

Deep learning has significantly improved state-of-the-art performance for natural language processing tasks like machine translation, summarization, question answering, and text classification.

Interpretable Counting for Visual Question Answering

Alex Trott · #research

Learning to answer open-ended questions about images, a task known as visual question answering (VQA), has received much attention over the last several years. VQA has been put forth as a benchmark for complete scene understanding and flexible reasoning, two fundamental goals of AI.

Improving end-to-end Speech Recognition Models

Yingbo Zhou · #research

Speech recognition has been successfully depolyed on various smart devices, and is changing the way we interact with them. Traditional phonetic-based recognition approaches require training of separate components such as pronouciation, acoustic and language model.

How to Talk to Your Database

Victor Zhong · #research

A vast amount of today’s information is stored in relational databases. These databases provide the foundation of systems such as medical records, financial markets, and electronic commerce.