Week Ending 6.7.2020
RESEARCH WATCH: 6.7.2020
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 246 times, including in the article Japan's Coronavirus Numbers Are Low. Are Masks the Reason? in New York Times. 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 3865 shares. A Twitter user, @chrish_99, said "Masks more effective than lockdown at suppressing spread. Mandate mask wearing and end the lockdown? Even non medical masks are recommended", while @gastronomy said "> We present two models for the COVID-19 pandemic predicting the impact of u".
Leading researcher Danielle S. Bassett (University of Pennsylvania) came out with "The growth and form of knowledge networks by kinesthetic curiosity".
The paper shared the most on social media this week is by a team at DeepMind: "Acme: A Research Framework for Distributed Reinforcement Learning" by Matt Hoffman et al (Jun 2020) with 162 shares. @dennybritz (Denny Britz) tweeted "This new RL framework looks pretty cool. There seem to be quite a few abstractions you need to learn about, but the effort may be worth it if you want to scale up your agents. The tutorial on arXiv is excellent".
Over the past week, 179 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".
The paper discussed most in the news over the past week was "MultiNet: Multiclass Multistage Multimodal Motion Prediction" by Nemanja Djuric et al (Jun 2020), which was referenced 5 times, including in the article Uber’s self-driving AI predicts the trajectories of pedestrians, vehicles, and cyclists in Venturebeat. The paper got social media traction with 9 shares.
Leading researcher Jianfeng Gao (Microsoft) came out with "M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training" The authors present a Multitask Multilingual Multimodal Pre - trained model (M3P) that combines multilingual - monomodal pre - training and monolingual - multimodal pre - training into a unified framework via multitask learning and weight sharing.
The paper shared the most on social media this week is "Ear2Face: Deep Biometric Modality Mapping" by Dogucan Yaman et al (Jun 2020) with 342 shares. The investigators explore the correlation between different visual biometric modalities. @deadwisdom (Brantley Harris) tweeted "Holy hell, a system for generating faces based on nothing but a picture of the ear. We are nowhere near ready for the technology about to be unleashed on society".
The most influential Twitter user discussing papers is Danilo J. Rezende who shared "Neural Discrete Representation Learning" by Aaron van den Oord et al (Nov 2017) and said: "On a similar direction: But: Blaming the VAE’s prior for its shortcomings is misleading. The prior is irrelevant in VAEs as it can be absorbed by the decoder. The main bottleneck is how well the encoder approaches the true posterior 1/2". Note that this paper was published about two years ago.
This week was active for "Computer Science - Computers and Society", with 35 new papers.
The paper discussed most in the news over the past week was "Blockchain is Watching You: Profiling and Deanonymizing Ethereum Users" by Ferenc Béres et al (May 2020), which was referenced 8 times, including in the article ‘Careless’ Users Are Ruining Ethereum’s Privacy: Paper in CoinDesk. The paper got social media traction with 238 shares. A user, @theonevortex, tweeted "TLDR; #Ethereum doesn't care much about privacy when it's trivial to deanonymize tens of thousands of users", while @sethisimmons posted "👀 New #Ethereum privacy paper just released today, I know what I'm reading! Really curious what the takeaways are".
The paper shared the most on social media this week is by a team at Santa Fe Institute: "Countering hate on social media: Large scale classification of hate and counter speech" by Joshua Garland et al (Jun 2020) with 82 shares. The researchers made use of a unique situation in Germany where self - labeling groups engaged in organized online hate and counter speech. @hanscees (Hans-Cees🐰) tweeted "Wonderful 👍 What a gigantous work you've done. I would call this memetic battle: counteracting a torrent of hate-memes. #memetics".
Over the past week, 20 new papers were published in "Computer Science - Human-Computer Interaction".
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 5 times, including in the article Ultrasound haptic system projects readable Braille into thin air in New Atlas. The paper author, Viktorija Paneva (University of Bayreuth), was quoted saying "With HaptiRead, we investigate for the first time, in a user study with blind people, the possibility of using midair haptic technology for the purpose of presenting braille text as a touchless haptic sensation". The paper got social media traction with 13 shares.
This week was very active for "Computer Science - Learning", with 428 new papers.
The paper discussed most in the news over the past week was "Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search" by Aditya Rawal et al (May 2020), which was referenced 6 times, including in the article OpenAI & Uber AI Proposed A New Approach To Neural Architecture Search in Analytics India Magazine. The paper got social media traction with 171 shares. A Twitter user, @stenichele, said "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 😉", while @samgreydanus said "This is philosophically a great idea".
Leading researcher Yoshua Bengio (Université de Montréal) published "Training End-to-End Analog Neural Networks with Equilibrium Propagation".
The paper shared the most on social media this week is by a team at DeepMind: "Acme: A Research Framework for Distributed Reinforcement Learning" by Matt Hoffman et al (Jun 2020)
The most influential Twitter user discussing papers is Danilo J. Rezende who shared "Neural Discrete Representation Learning" by Aaron van den Oord et al (Nov 2017)
Over the past week, 16 new papers were published in "Computer Science - Multiagent Systems".
This week was active for "Computer Science - Neural and Evolutionary Computing", with 37 new papers.
Leading researcher Yoshua Bengio (Université de Montréal) published "Training End-to-End Analog Neural Networks with Equilibrium Propagation".
The paper shared the most on social media this week is by a team at Harvard University: "Cascaded Text Generation with Markov Transformers" by Yuntian Deng et al (Jun 2020) with 120 shares. @A_K_Nain (Aakash Kumar Nain) tweeted "The diagrams ❣️❣️".
The most influential Twitter user discussing papers is Danilo J. Rezende who shared "Neural Discrete Representation Learning" by Aaron van den Oord et al (Nov 2017)
This week was active for "Computer Science - Robotics", with 60 new papers.
The paper discussed most in the news over the past week was by a team at UC Berkeley: "DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation" by Mike Lambeta et al (May 2020), which was referenced 1 time, including in the article Facebook’s Digit is a low-cost tactile sensor for robotic hands in Venturebeat. The paper got social media traction with 8 shares.