Deep Learning & Language | Montréal
Projects
Established:
Machine Reading Comprehension (MRC) is a growing field of research, due to its potential in various enterprise applications, as well as the availability of MRC benchmarking datasets.
A framework to host and train publicly available machine learning models while crowdsourcing a dataset. Ideally, using a model for prediction is free. An incentive mechanism validates added data.
The Generative Neural Visual Artist (GeNeVA) task The GeNeVA task involves a Teller giving a sequence of linguistic instructions to a Drawer for the ultimate goal of image generation. The Teller is able to gauge progress through visual feedback of…
As part of the Eighth Dialog System Technology Challenge (DSTC8), Microsoft Research and Tsinghua University are hosting a track intended to foster progress in two important aspects of dialog systems: dialog complexity and scaling to new domains. For this DSTC8…
Answering questions about a given image is a difficult task, requiring both an understanding of the image and the accompanying query. Microsoft research Montreal’s FigureQA dataset introduces a new visual reasoning task for research, specific to graphical plots and figures.…
Motivation A generation of voice assistants such as Siri, Cortana, and Google Now have been popular spoken dialogue systems. More recently, we have seen a rise in text-based conversational agents (aka chatbots). Text is preferred to voice by many users…
With massive volumes of written text being produced every second, how do we make sure that we have the most recent and relevant information available to us? Microsoft research Montreal is tackling this problem by building AI systems that can…
Microsoft TextWorld is an open-source, extensible engine that both generates and simulates text games. You can use it to train reinforcement learning (RL) agents to learn skills such as language understanding and grounding, combined with sequential decision making.