696 Results
January 1, 2020
Designing Safe Spaces for Virtual Reality
Ethics in Design and Communication
Virtual Reality (VR) designers accept the ethical responsibilities of removing a user’s entire world and superseding it with a fabricated reality. These unique immersive design challenges are intensified when virtual experiences become public and socially-driven. As female VR designers in 2018, we see an opportunity to fold the language of consent into the design practice of virtual reality—as a means to design safe, accessible, virtual spaces.
Publication will be made available in 2020.
By: Michelle Cortese, Andrea Zeller
AR/VR 
Human Computer Interaction & UX June 7, 2019
Cycle-Consistency for Robust Visual Question Answering
Computer Vision and Pattern Recognition (CVPR)
Despite significant progress in Visual Question Answering over the years, robustness of today’s VQA models leave much to be desired. We introduce a new evaluation protocol and associated dataset (VQA-Rephrasings) and show that state-of-the-art VQA models are notoriously brittle to linguistic variations in questions.
By: Meet Shah, Xinlei Chen, Marcus Rohrbach, Devi Parikh
Computer Vision 
Facebook AI Research 
Machine Learning 
Natural Language Processing & Speech June 3, 2019
Pay less attention with Lightweight and Dynamic Convolutions
International Conference on Learning Representations (ICLR)
Self-attention is a useful mechanism to build generative models for language and images. It determines the importance of context elements by comparing each element to the current time step. In this paper, we show that a very lightweight convolution can perform competitively to the best reported self-attention results.
By: Felix Wu, Angela Fan, Alexei Baevski, Yann Dauphin, Michael AuliJune 2, 2019
The emergence of number and syntax units in LSTM language models
Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
We present here a detailed study of the inner mechanics of number tracking in LSTMs at the single neuron level. We discover that long-distance number information is largely managed by two “number units”.
By: Yair Lakretz, Germán Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, Marco BaroniJune 2, 2019
Simple Attention-Based Representation Learning for Ranking Short Social Media Posts
North American Chapter of the Association for Computational Linguistics (NAACL)
This paper explores the problem of ranking short social media posts with respect to user queries using neural networks. Instead of starting with a complex architecture, we proceed from the bottom up and examine the effectiveness of a simple, word-level Siamese architecture augmented with attention-based mechanisms for capturing semantic “soft” matches between query and post tokens.
By: Peng Shi, Jinfeng Rao, Jimmy LinJune 1, 2019
Neural Models of Text Normalization for Speech Applications
Computational Linguistics
Machine learning, including neural network techniques, have been applied to virtually every domain in natural language processing. One problem that has been somewhat resistant to effective machine learning solutions is text normalization for speech applications such as text-to-speech synthesis (TTS).
By: Hao Zhang, Richard Sproat, Axel H. Ng, Felix Stahlberg, Xiaochang Peng, Kyle Gorman, Brian RoarkMay 31, 2019
Abusive Language Detection with Graph Convolutional Networks
North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
Abuse on the Internet represents a significant societal problem of our time. Previous research on automated abusive language detection in Twitter has shown that community-based profiling of users is a promising technique for this task. However, existing approaches only capture shallow properties of online communities by modeling follower–following relationships.
By: Pushkar Mishra, Marco Del Tredici, Helen Yannakoudakis, Ekaterina ShutovaMay 25, 2019
UBIS: Utilization-aware cluster scheduling
International Parallel and Distributed Processing Symposium (IPDPS)
Data center costs are among the major enterprise expenses, and any improvement in data center resource utilization corresponds to significant savings in true dollars. We focus on the problem of scheduling jobs in distributed execution environments to improve resource utilization.
By: Karthik Kambatla, Vamsee Yarlagadda, Íñigo Goiri, Ananth Grama
Systems & Networking May 19, 2019
Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery
Conference on Information Systems for Crisis Response and Management (ISCRAM)
In this paper, we describe the data and methodology that power Facebook Disaster Maps. These maps utilize information about Facebook usage in areas impacted by natural hazards, producing aggregate pictures of how the population is affected by and responding to the hazard. The maps include insights into evacuations, cell network connectivity, access to electricity, and long-term displacement.
By: Paige Maas, Shankar Iyer, Andreas Gros, Wonhee Park, Laura McGorman, Chaya Nayak, Alex Dow
Connectivity 
Data Science May 12, 2019
Provably Accelerated Randomized Gossip Algorithms
IEEE International Conference on Acoustics, Speech, and Signal Processing
In this work we present novel provably accelerated gossip algorithms for solving the average consensus problem.
By: Nicolas Loizou, Michael Rabbat, Peter Richtárik