Week Ending 10.06.19
RESEARCH WATCH: 10.06.19
Over the past week, 920 new papers were published in "Computer Science".
The paper discussed most in the news over the past week was "Can WhatsApp Counter Misinformation by Limiting Message Forwarding?" by Philipe de Freitas Melo et al (Sep 2019), which was referenced 36 times, including in the article WhatsApp Was Extensively Abused For Spreading Misinformation During 2019 Elections In India in Indiatimes. The paper author, Kiran Garimella (Aalto University), was quoted saying "I’m from India and through the current election, individuals have been saying that the forwarding restrict wasn’t serving to a lot".
Leading researcher Yoshua Bengio (Université de Montréal) published "Underwhelming Generalization Improvements From Controlling Feature Attribution", which has 0 shares on Twitter so far.
Over the past week, 50 new papers were published in "Computer Science - Artificial Intelligence".
The paper discussed most in the news over the past week was by a team at Brunel University London: "The Prevalence of Errors in Machine Learning Experiments" by Martin Shepperd et al (Sep 2019), which was referenced 5 times, including in the article Weekend reads: The need for more honesty in science; a fight between authors of a GM mosquito paper; faked academic CVs in Retraction Watch. The paper got social media traction with 68 shares. On Twitter, @dinga92 said "Systematic review of 49 ML papers. 22 contained errors 16 arithmetic (inconsistent confusion matrices) 7 statistical (no multiple comparisons adjustment)", while @ronnyk observed "We want to be data driven, but is the data trustworthy? Some great examples of common errors everyone can check: 1. Inconsistencies in confusion matrices: 2. Statistical errors".
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Variational Temporal Abstraction".
Over the past week, 139 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 Google: "A deep learning system for differential diagnosis of skin diseases" by Yuan Liu et al (Sep 2019), which was referenced 7 times, including in the article How Machine Learning is Transforming Healthcare at Google and Beyond in Towards Data Science. The paper author, Yuan Liu (South China University of Technology), was quoted saying "We believe these limitations can be addressed by including more cases of biopsy-proven skin cancers in the training and validation sets". The paper got social media traction with 244 shares. The investigators developed a deep learning system (DLS) to provide a differential diagnosis of skin conditions for clinical cases (skin photographs and associated medical histories). A Twitter user, @ddonoho, said "Image-based diagnostics... Today: deep learning >= primary care doctors. Tomorrow: deep learning >= specialists. Today #dermatology and #pathology but how much longer will image categorization be a job for humans?".
Leading researcher Yoshua Bengio (Université de Montréal)
Over the past week, 15 new papers were published in "Computer Science - Computers and Society".
The paper discussed most in the news over the past week was "Can WhatsApp Counter Misinformation by Limiting Message Forwarding?" by Philipe de Freitas Melo et al (Sep 2019)
Over the past week, ten new papers were published in "Computer Science - Human-Computer Interaction".
The paper discussed most in the news over the past week was "SwarmTouch: Tactile Interaction of Human with Impedance Controlled Swarm of Nano-Quadrotors" by Evgeny Tsykunov et al (Sep 2019), which was referenced 1 time, including in the article SwarmTouch: A tactile interaction strategy for human-swarm communication in Tech Xplore. The paper author, Dzmitry Tsetserukou (Skolkovo Institute of Science and Technology (Skoltech)), was quoted saying "This approach is somewhat similar to the popular mobile game Angry Birds, but with users pulling a real drone with a rope instead of on a touch screen, in order to navigate its ballistic trajectory in virtual reality". The paper was shared 3 times in social media.
This week was very active for "Computer Science - Learning", with 278 new papers.
The paper discussed most in the news over the past week was by a team at Microsoft: "Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation" by Ze Yang et al (Sep 2019), which was referenced 11 times, including in the article This won't end well. Microsoft's AI boffins unleash a bot that can generate fake comments for news articles in The Register.
Leading researcher Yoshua Bengio (Université de Montréal)
Over the past week, nine 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 New York University: "Finding Generalizable Evidence by Learning to Convince Q&A Models" by Ethan Perez et al (Sep 2019), which was referenced 1 time, including in the article An approach to enhance question answering (QA) models in Tech Xplore. The paper author, Ethan Perez (Rice University), was quoted saying "Our system can find evidence for any answer—not just the answer that the Q&A model thinks is correct, as prior work focused on". The paper got social media traction with 35 shares. A user, @EthanJPerez, tweeted "What evidence do people find convincing? Often, the same evidence that Q&A models find convincing. Check out our #emnlp2019 paper: And blog post: w/ Rob Fergus".
Over the past week, 23 new papers were published in "Computer Science - Neural and Evolutionary Computing".
The paper discussed most in the news over the past week was "Neural Network Applications in Earthquake Prediction (1994-2019): Meta-Analytic Insight on their Limitations" by Arnaud Mignan et al (Oct 2019), which was referenced 1 time, including in the article Complexification of neural networks NOT helping to predict earthquakes in Medium.com.
This week was active for "Computer Science - Robotics", with 59 new papers.
The paper discussed most in the news over the past week was "Nailed It: Autonomous Roofing with a Nailgun-Equipped Octocopter" by Matthew Romano et al (Sep 2019), which was referenced 28 times, including in the article Roofing Drone Nails Down Shingles in Aero-News Network. The paper author, Ella Atkins (University of Michigan), was quoted saying "For me, the biggest excitement of this work is in recognizing that autonomous, useful, physical interaction and construction tasks are possible with drones". The paper was shared 1 time in social media. The investigators present the first demonstration of autonomous roofing with a multicopter.
Leading researcher Abhinav Gupta (Carnegie Mellon University) published "Efficient Bimanual Manipulation Using Learned Task Schemas".