Week Ending 9.12.2021
RESEARCH WATCH: 9.12.2021
This week was active for "Computer Science", with 1,217 new papers.
The paper discussed most in the news over the past week was by a team at Stanford University: "On the Opportunities and Risks of Foundation Models" by Rishi Bommasani et al (Aug 2021), which was referenced 11 times, including in the article A New AI Lexicon: Power in Medium.com. The paper author, Rishi Bommasani, was quoted saying "The commercial incentive can lead companies to ignore social externalities such as the technological displacement of labor, the health of an informational ecosystem required for democracy, the environmental cost of computing resources, and the profit-driven sale of technologies to non-democratic regimes".
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Learning Neural Causal Models with Active Interventions".
This week was very active for "Computer Science - Artificial Intelligence", with 211 new papers.
The paper discussed most in the news over the past week was by a team at Stanford University: "On the Opportunities and Risks of Foundation Models" by Rishi Bommasani et al (Aug 2021)
Leading researcher Kyunghyun Cho (New York University) published "An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models".
This week was active for "Computer Science - Computer Vision and Pattern Recognition", with 229 new papers.
The paper discussed most in the news over the past week was "Unsupervised Detection of Adversarial Examples with Model Explanations" by Gihyuk Ko et al (Jul 2021), which was referenced 4 times, including in the article Researchers have created a new technique to stop adversarial attacks in The Next Web. The paper author, Gihyuk Ko, was quoted saying "Our recent work began with a simple observation that adding small noise to inputs resulted in a huge difference in their explanations".
Leading researcher Luc Van Gool (Computer Vision Laboratory) published "Perceptual Learned Video Compression with Recurrent Conditional GAN".
Over the past week, 21 new papers were published in "Computer Science - Computers and Society".
The paper discussed most in the news over the past week was by a team at Stanford University: "On the Opportunities and Risks of Foundation Models" by Rishi Bommasani et al (Aug 2021)
This week was very active for "Computer Science - Human-Computer Interaction", with 38 new papers.
The paper discussed most in the news over the past week was "Metaverse for Social Good: A University Campus Prototype" by Haihan Duan et al (Aug 2021), which was referenced 1 time, including in the article The “Metaverse” and the Future of Video Conferencing in Craving Tech.
This week was very active for "Computer Science - Learning", with 396 new papers.
The paper discussed most in the news over the past week was by a team at Stanford University: "On the Opportunities and Risks of Foundation Models" by Rishi Bommasani et al (Aug 2021)
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Learning Neural Causal Models with Active Interventions".
Over the past week, ten 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 Honda Research Institute USA: "LOKI: Long Term and Key Intentions for Trajectory Prediction" by Harshayu Girase et al (Aug 2021), which was referenced 1 time, including in the article LOKI: An intention dataset to train models for pedestrian and vehicle trajectory prediction in Tech Xplore. The paper author, Chiho Choi (Honda Research Institute USA), was quoted saying "We already started exploring other research directions aimed at jointly reasoning about intentions and trajectories while considering different internal/external factors such as agents' will, social interactions and environmental factors".
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 "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers" by Róbert Csordás et al (Aug 2021), which was referenced 1 time, including in the article Swiss AI Lab Uses Simple Tricks to Dramatically Improve Transformers' Systematic Generalization in SyncedReview.com.
This week was very active for "Computer Science - Robotics", with 100 new papers.
The paper discussed most in the news over the past week was by a team at Honda Research Institute USA: "LOKI: Long Term and Key Intentions for Trajectory Prediction" by Harshayu Girase et al (Aug 2021)