Week Ending 1.30.2022
RESEARCH WATCH: 1.30.2022
This week was active for "Computer Science", with 1,224 new papers.
The paper discussed most in the news over the past week was "Projective Embedding of Dynamical Systems: uniform mean field equations" by Francesco Caravelli et al (Jan 2022), which was referenced 70 times, including in the article MemComputing Announces Collaboration with Los Alamos National Lab in Street Insider. The paper author, Francesco Caravelli, was quoted saying "The findings of this study are very exciting as they demonstrate the first realization of classical tunneling in an a-thermal, passive system moving in an effective potential. This mechanism is appealing for its physical relevance in nanoscale physics and for its possible applications in optimization, Monte Carlo schemes, and machine learning." The paper got social media traction with 8 shares.
Leading researcher Yoshua Bengio (Université de Montréal) published "The Effect of Diversity in Meta-Learning".
The paper shared the most on social media this week is by a team at University of Washington: "Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection" by Suchin Gururangan et al (Jan 2022) with 163 shares. @triciapersisted (Tricia Griffin, MPH, M.Bioethics πππ) tweeted "It's always a good idea talk about "who" in technology, before we glorify the "what". Who is the technology for? Who does it protect/prefer? Who does it exclude?".
This week was very active for "Computer Science - Artificial Intelligence", with 204 new papers.
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "Natural Language Descriptions of Deep Visual Features" by Evan Hernandez et al (Jan 2022), which was referenced 7 times, including in the article Demystifying machine-learning systems in Mirage News. The paper author, Hernandez, was quoted saying "In a neural network that is trained to classify images, there are going to be tons of different neurons that detect dogs. But there are lots of different types of dogs and lots of different parts of dogs. So even though βdogβ might be an accurate description of a lot of these neurons, it is not very informative. We want descriptions that are very specific to what that neuron is doing. This isnβt just dogs; this is the left side of ears on German shepherds". The paper got social media traction with 25 shares. A Twitter user, @summarizedml, posted "We introduce MILAN, a procedure for mutual-information-guided linguistic annotation of neurons that captures categorical, relational, π", while @metasj posted "MILAN: I love this".
Leading researcher E. A. Huerta (University of Illinois at Urbana-Champaign) published "Inference-optimized AI and high performance computing for gravitational wave detection at scale" @summarizedml tweeted "We introduce an inference-optimized AI ensemble for gravitational wave detection that we trained in the Summit supercomputer using 32 nodes, equivalent to π".
The paper shared the most on social media this week is by a team at University of Washington: "Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection" by Suchin Gururangan et al (Jan 2022)
This week was active for "Computer Science - Computer Vision and Pattern Recognition", with 283 new papers.
The paper discussed most in the news over the past week was by a team at North Carolina State University: "Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection" by Xianpeng Liu et al (Dec 2021), which was referenced 9 times, including in the article Technique Improves AI Ability to Understand 3D Space Using 2D Images in Mirage News. The paper author, Tianfu Wu (North Carolina State University), was quoted saying "We live in a 3D world, but when you take a picture, it records that world in a 2D image". The paper got social media traction with 5 shares. The researchers propose a simple yet effective formulation for monocular 3D object detection without exploiting any extra information. A user, @summarizedml, tweeted "Monocular 3D object detection without exploiting any extra information . π".
Leading researcher Yann LeCun (New York University) published "Neural Manifold Clustering and Embedding" @ak92501 tweeted "Neural Manifold Clustering and Embedding abs: significantly outperforms autoencoder-based deep subspace clustering. Further, on more challenging natural image datasets, NMCE can also outperform other algorithms specifically designed for clustering".
The paper shared the most on social media this week is "Patches Are All You Need?" by Asher Trockman et al (Jan 2022) with 129 shares. @weballergy (Nenad Tomasev) tweeted "It's been fascinating to see all the recent progress in computer vision and most of all trying to understand what are the building blocks that seem to work best and why. I'm sure there is more to come!".
Over the past week, 24 new papers were published in "Computer Science - Computers and Society".
This week was very active for "Computer Science - Human-Computer Interaction", with 47 new papers.
The paper discussed most in the news over the past week was "Obstacle avoidance for blind people using a 3D camera and a haptic feedback sleeve" by Manuel Zahn et al (Jan 2022), which was referenced 19 times, including in the article New device could help people who are blind βseeβ in infrared in The Independent. The paper got social media traction with 7 shares. On Twitter, @stripp_lab commented "Quite some media coverage on this 'infrared vision' pre-print... Data not convincing though".
The paper shared the most on social media this week is by a team at University of Stuttgart: "Human Interpretation of Saliency-based Explanation Over Text" by Hendrik Schuff et al (Jan 2022) with 84 shares. @yoavgo ((((Ω()(Ω() 'yoav))))πΎ) tweeted "This work is somewhat outside my element, but I really like it, and find it extremely important. There are many explanation methods for ML. But how do people *perceive* these explanations? turns out that this is far from trivial q, and many factors contribute to potential biases".
The most influential Twitter user discussing papers is Francis Villatoro who shared "Is the Hubble crisis connected with the extinction of dinosaurs?" by Leandros Perivolaropoulos (Jan 2022) and said: "Is the Hubble crisis connected with the extinction of dinosaurs? A change in Newton's constant G by about 10%, taking place 50-150 Myrs ago, can solve the Hubble crisis. cc ruido para el programa".
This week was very active for "Computer Science - Learning", with 443 new papers.
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "Natural Language Descriptions of Deep Visual Features" by Evan Hernandez et al (Jan 2022)
Leading researcher Yoshua Bengio (Université de Montréal) came out with "The Effect of Diversity in Meta-Learning".
The paper shared the most on social media this week is "Patches Are All You Need?" by Asher Trockman et al (Jan 2022)
This week was active for "Computer Science - Multiagent Systems", with 20 new papers.
Over the past week, 30 new papers were published in "Computer Science - Neural and Evolutionary Computing".
The paper discussed most in the news over the past week was "Projective Embedding of Dynamical Systems: uniform mean field equations" by Francesco Caravelli et al (Jan 2022)
This week was active for "Computer Science - Robotics", with 62 new papers.