Week Ending 5.31.2020
RESEARCH WATCH: 5.31.2020
Over the past week, 91 new papers were published in "Computer Science - Artificial Intelligence".
The paper discussed most in the news over the past week was "Universal Masking is Urgent in the COVID-19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations" by De Kai et al (Apr 2020), which was referenced 237 times, including in the article WHO guidance: Healthy people should wear masks only when 'taking care of' coronavirus patients in FOXNews.com. The paper author, Vitamin D. Kai, was quoted saying "I saw the country where I grew up [China], where my family lives [now mostly in the Bay Area], about to face this pandemic without knowing much about something as simple as wearing a mask to protect themselves and others". The paper also got the most social media traction with 3813 shares. A user, @chrish_99, tweeted "Masks more effective than lockdown at suppressing spread. Mandate mask wearing and end the lockdown? Even non medical masks are recommended", while @gastronomy commented "> We present two models for the COVID-19 pandemic predicting the impact of u".
Leading researcher Ruslan Salakhutdinov (Carnegie Mellon University) came out with "Neural Topological SLAM for Visual Navigation", which had 21 shares over the past 5 days. The investigators study the problem of image - goal navigation which involves navigating to the location indicated by a goal image in a novel previously unseen environment.
The paper shared the most on social media this week is "Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search" by Aditya Rawal et al (May 2020) with 161 shares. @stenichele (Stefano Nichele - Living Technology Lab) tweeted "Cool work But didnt like the petri dish analogy, at least based on my experience on working with biological neural networks in a petri dish, which is quite different 😉".
Over the past week, 199 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".
The paper discussed most in the news over the past week was by a team at National Tsing Hua University: "3D Photography using Context-aware Layered Depth Inpainting" by Meng-Li Shih et al (Apr 2020), which was referenced 33 times, including in the article AI researchers say they created a better way to generate 3D photos in Venturebeat. The paper got social media traction with 77 shares. A user, @Mady_ai, tweeted "3D photography using context aware layered in painting Seems very cool 4 all kind of pics. The only thing is, processing takes 2+ mins but amazing work. #deeplearning #computervision #machinelearning #artificialintelligence".
Leading researcher Ruslan Salakhutdinov (Carnegie Mellon University) came out with "Neural Topological SLAM for Visual Navigation", which had 21 shares over the past 5 days. The researchers study the problem of image - goal navigation which involves navigating to the location indicated by a goal image in a novel previously unseen environment.
The paper shared the most on social media this week is "End-to-End Object Detection with Transformers" by Nicolas Carion et al (May 2020) with 586 shares.
This week was very active for "Computer Science - Computers and Society", with 48 new papers.
The paper discussed most in the news over the past week was "Pandemic Programming: How COVID-19 affects software developers and how their organizations can help" by Paul Ralph et al (May 2020), which was referenced 5 times, including in the article COVID 19 pandemic hits programmers’ productivity, well being, study reveals in ITWire. The paper author, Dr Sebastian Baltes, was quoted saying "Many developers began working from home, often at short notice and under difficult and stressful conditions, as COVID-19 swept across the world". The paper got social media traction with 9 shares. The investigators seek to understand the effects of the pandemic on developers wellbeing and productivity.
The paper shared the most on social media this week is by a team at Microsoft: "Language (Technology) is Power: A Critical Survey of Bias in NLP" by Su Lin Blodgett et al (May 2020) with 154 shares. @deliprao (Delip Rao) tweeted "Wish I see more such work. Inspiring 👇🏼".
This week was active for "Computer Science - Human-Computer Interaction", with 24 new papers.
The paper discussed most in the news over the past week was by a team at University of Bayreuth: "HaptiRead: Reading Braille as Mid-Air Haptic Information" by Viktorija Paneva et al (May 2020), which was referenced 3 times, including in the article Amazing haptic speaker lets visually impaired people read braille in midair in Digital Trends. The paper author, Sofia Seinfeld (University of Bayreuth), was quoted saying "Since HaptiRead provides the possibility of reading braille through touchless interactions, it definitely represents a novel solution for reading information in public spaces such as elevators, cash machines, city maps, information booths, [and similar]". The paper got social media traction with 5 shares.
This week was very active for "Computer Science - Learning", with 309 new papers.
The paper discussed most in the news over the past week was "The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America" by Benjamin Charles Germain Lee et al (May 2020), which was referenced 13 times, including in the article LC Labs Letter: May 2020 in Library of Congress. The paper author, Residence Ben Lee, was quoted saying "I loved it because it emphasized the visual nature of the pages — seeing the visual diversity of the content coming out of the project, I just thought it was so cool, and I wondered what it would be like to chronicle content like this from all over America". The paper got social media traction with 207 shares. On Twitter, @Psythor commented "AI has just automated a job I used to have 11 years ago. When I was doing my MA, I worked at in a news clippings department, which would analyse scans of local papers for mentions of companies etc. I’d spend 8 hours non-stop dragging boxes around different headlines and stories".
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning" The authors present a severity score prediction model for COVID-19 pneumonia for frontal chest X - ray images.
The paper shared the most on social media this week is "Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search" by Aditya Rawal et al (May 2020)
Over the past week, 16 new papers were published in "Computer Science - Multiagent Systems".
The paper discussed most in the news over the past week was by a team at University of Southern California: "Lifelong Multi-Agent Path Finding in Large-Scale Warehouses" by Jiaoyang Li et al (May 2020), which was referenced 3 times, including in the article Amazon studies anti-collision method for robots to increase throughput in SupplyChainDive.com. The paper was shared 3 times in social media. The investigators study the lifelong variant of MAPF where agents are constantly engaged with new goal locations, such as in large - scale warehouses.
Over the past week, 21 new papers were published in "Computer Science - Neural and Evolutionary Computing".
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "HAT: Hardware-Aware Transformers for Efficient Natural Language Processing" by Hanrui Wang et al (May 2020), which was referenced 3 times, including in the article New AI technique speeds up language models on edge devices in Venturebeat. The paper got social media traction with 87 shares. A Twitter user, @hanrui_w, observed "Hi Leon, I'm glad to share our paper and code: Feel free to reach out for any questions!".
This week was active for "Computer Science - Robotics", with 47 new papers.
The paper discussed most in the news over the past week was by a team at University of Southern California: "Lifelong Multi-Agent Path Finding in Large-Scale Warehouses" by Jiaoyang Li et al (May 2020), which was referenced 3 times, including in the article Amazon studies anti-collision method for robots to increase throughput in SupplyChainDive.com. The paper was shared 3 times in social media. The researchers study the lifelong variant of MAPF where agents are constantly engaged with new goal locations, such as in large - scale warehouses.
Leading researcher Ruslan Salakhutdinov (Carnegie Mellon University) published "Neural Topological SLAM for Visual Navigation", which had 21 shares over the past 5 days. The authors study the problem of image - goal navigation which involves navigating to the location indicated by a goal image in a novel previously unseen environment. This paper was also shared the most on social media with 80 tweets.