Week Ending 4.24.2022
RESEARCH WATCH: 4.24.2022
SPONSORED BY
This week was active for "Computer Science", with 1,169 new papers.
The paper discussed most in the news over the past week was by a team at University of Oxford: "Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels" by Konrad Kollnig et al (Apr 2022), which was referenced 45 times, including in the article A year after Apple enforces app tracking policy, covert iOS tracking remains in ArsTechnica. The paper got social media traction with 158 shares. A Twitter user, @RDBinns, posted "One of the worrying details from this research was the circumvention of Apple's privacy controls by trackers. When you 'Ask App Not to Track', iOS stops third parties accessing the advertising ID. So some resort to fingerprinting instead. One example is Alibaba-owned Umeng".
Leading researcher Sergey Levine (University of California, Berkeley) published "Context-Aware Language Modeling for Goal-Oriented Dialogue Systems" The investigators formulate goal - oriented dialogue as a partially observed Markov decision process, interpreting the language model as a representation of both the dynamics and the policy. @ak92501 tweeted "Context-Aware Language Modeling for Goal-Oriented Dialogue Systems abs: project page: CALM outperforms the state-of-the-art method by 7% in terms of task success, matching human-level task performance".
The paper shared the most on social media this week is "VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance" by Katherine Crowson et al (Apr 2022) with 255 shares. @HochreiterSepp (Sepp Hochreiter) tweeted "ArXiv Generating images from open domain text prompts using CLIP to guide VQGAN. Higher visual quality outputs than DALL-E, GLIDE and Open-Edit. Prompts of higher semantic complexity. Code available (colab notebooks)".
The most influential Twitter user discussing papers is AK who shared "mGPT: Few-Shot Learners Go Multilingual" by Oleh Shliazhko et al (Apr 2022) and said: "mGPT: Few-Shot Learners Go Multilingual abs: introduces two autoregressive GPT-like models with 1.3 billion and 13 billion parameters trained on 60 languages from 25 language families using Wikipedia and Colossal Clean Crawled Corpus".
This week was very active for "Computer Science - Artificial Intelligence", with 185 new papers.
The paper discussed most in the news over the past week was by a team at Cornell: "Unsupervised Semantic Segmentation by Distilling Feature Correspondences" by Mark Hamilton et al (Mar 2022), which was referenced 18 times, including in the article MIT's newest computer vision algorithm identifies images down to the pixel in Yahoo! News. The paper author, Mark Hamilton (Microsoft), was quoted saying "If you're looking at oncological scans, the surface of planets, or high-resolution biological images, it’s hard to know what objects to look for without expert knowledge. In emerging domains, sometimes even human experts don't know what the right objects should be". The paper got social media traction with 20 shares. A user, @ZetaVector, tweeted "More image segmentation without supervision. "Unsupervised Semantic Segmentation by Distilling Feature Correspondences" by Mark Hamilton, now at".
Leading researcher Sergey Levine (University of California, Berkeley) came out with "Context-Aware Language Modeling for Goal-Oriented Dialogue Systems" The investigators formulate goal - oriented dialogue as a partially observed Markov decision process, interpreting the language model as a representation of both the dynamics and the policy. @ak92501 tweeted "Context-Aware Language Modeling for Goal-Oriented Dialogue Systems abs: project page: CALM outperforms the state-of-the-art method by 7% in terms of task success, matching human-level task performance".
The paper shared the most on social media this week is by a team at Carnegie Mellon University: "Deep Equilibrium Optical Flow Estimation" by Shaojie Bai et al (Apr 2022) with 84 shares. @HochreiterSepp (Sepp Hochreiter) tweeted "ArXiv Optical flow estimation by deep equilibrium models. 4 to 6× times less memory than recurrent networks since using cheap inexact gradient makes backward pass almost for free. Improves SOTA methods on Sintel and KITTI with less compute and memory".
This week was very active for "Computer Science - Computer Vision and Pattern Recognition", with 329 new papers.
The paper discussed most in the news over the past week was by a team at Cornell: "Unsupervised Semantic Segmentation by Distilling Feature Correspondences" by Mark Hamilton et al (Mar 2022)
Leading researcher Devi Parikh (Georgia Institute of Technology) published "MUGEN: A Playground for Video-Audio-Text Multimodal Understanding and GENeration".
The paper shared the most on social media this week is "VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance" by Katherine Crowson et al (Apr 2022)
The most influential Twitter user discussing papers is AK who shared "mGPT: Few-Shot Learners Go Multilingual" by Oleh Shliazhko et al (Apr 2022)
Over the past week, 27 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 University of Oxford: "Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels" by Konrad Kollnig et al (Apr 2022)
The paper shared the most on social media this week is "I think I discovered a military base in the middle of the ocean -- Null Island, the most real of fictional places" by Levente Juhasz et al (Apr 2022) with 95 shares. The researchers explore Null Island, a fictional place located at 0∘∘ latitude and 0∘∘ longitude in the WGS84 geographic coordinate system. @fiugis (FIU GIS Center) tweeted "📢📢New Preprint Alert ⚠️📢📢 from our center and his co-author P. Mooney from argue that has serious technological, social and even philosophical implications. But what is #NullIsland? Read the preprint below to find out more!".
This week was very active for "Computer Science - Human-Computer Interaction", with 49 new papers.
The paper discussed most in the news over the past week was by a team at Columbia University: "Opal: Multimodal Image Generation for News Illustration" by Vivian Liu et al (Apr 2022), which was referenced 12 times, including in the article Deep Science: AI simulates economies and predicts which startups receive funding in Yahoo! News. The paper was shared 3 times in social media.
The paper shared the most on social media this week is "I think I discovered a military base in the middle of the ocean -- Null Island, the most real of fictional places" by Levente Juhasz et al (Apr 2022)
This week was very active for "Computer Science - Learning", with 341 new papers.
The paper discussed most in the news over the past week was by a team at Cornell: "Unsupervised Semantic Segmentation by Distilling Feature Correspondences" by Mark Hamilton et al (Mar 2022)
Leading researcher Sergey Levine (University of California, Berkeley) came out with "INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL" @summarizedml tweeted "A modified objective for model-based RL that, in conjunction with mutual information maximization, allows us to learnSourceFilerepresentations and dynamics 📄".
The paper shared the most on social media this week is by a team at Carnegie Mellon University: "Deep Equilibrium Optical Flow Estimation" by Shaojie Bai et al (Apr 2022)
The most influential Twitter user discussing papers is AK who shared "mGPT: Few-Shot Learners Go Multilingual" by Oleh Shliazhko et al (Apr 2022)
Over the past week, 13 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 Harvard University: "Using Reinforcement Learning to Study Platform Economies under Market Shocks" by Xintong Wang et al (Mar 2022), which was referenced 12 times, including in the article Deep Science: AI simulates economies and predicts which startups receive funding in Yahoo! News. The paper was shared 4 times in social media. The authors develop a multi - agent simulation environment to capture key elements of a platform economy, including the kinds of economic shocks that disrupt a traditional, off - platform market.
Over the past week, 17 new papers were published in "Computer Science - Neural and Evolutionary Computing".
This week was active for "Computer Science - Robotics", with 59 new papers.
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "GelSight Fin Ray: Incorporating Tactile Sensing into a Soft Compliant Robotic Gripper" by Sandra Q. Liu et al (Apr 2022), which was referenced 9 times, including in the article MIT CSAIL develops robotic gripper that can feel what it grabs in Robot Report.com. The paper author, Edward Adelson, was quoted saying "GelSight Fin Ray". Wenzhen Yuan (Carnegie Mellon University), who is not part of the study, said "Sensing with soft robots has been a big challenge, because it is difficult to set up sensors — which are traditionally rigid — on soft bodies". The paper was shared 2 times in social media.
Leading researcher Sergey Levine (University of California, Berkeley) published "INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL" @summarizedml tweeted "A modified objective for model-based RL that, in conjunction with mutual information maximization, allows us to learnSourceFilerepresentations and dynamics 📄".