{"date":"2026-07-03","schema_version":1,"captured_at":"2026-08-25T23:14:34.116Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"2026 FIFA World Cup","views":657600,"rank":3,"extract":"The 2026 FIFA World Cup was the 23rd FIFA World Cup, the quadrennial international men's soccer championship contested by the national teams of the member associations of FIFA. 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(2025)","points":234,"comments":141,"url":"https://inpreparation.substack.com/p/opinion-i-was-not-allowed-to-type","discussion":"https://news.ycombinator.com/item?id=48777728"},{"title":"Markets are competitive if and only if P != NP","points":231,"comments":164,"url":"https://arxiv.org/abs/2602.20415","discussion":"https://news.ycombinator.com/item?id=48776345"}],"research":[{"title":"Playing 20 Question Game with Policy-Based Reinforcement Learning","abstract":"The 20 Questions (Q20) game is a well known game which encourages deductive reasoning and creativity. In the game, the answerer first thinks of an object such as a famous person or a kind of animal. Then the questioner tries to guess the object by asking 20 questions. In a Q20 game system, the user is considered as the answerer while the system itself acts as the questioner which requires a good strategy of question ","authors":["Hu, Huang","Wu, Xianchao","Luo, Bingfeng","Tao, Chongyang","Xu, Can","Wu, Wei"],"url":"https://arxiv.org/abs/1808.07645","arxiv_id":"1808.07645","published":"2026-07-03"},{"title":"Learning Consumer Preferences from Bundle Sales Data","abstract":"Problem definition: This paper studies the problem of estimating consumer preferences from bundle sales data. Product bundling is a widely used pricing strategy in retail markets. To set profitable bundle selection and prices, the seller needs to learn the distribution of consumers' valuations for individual products from the transaction data. When customers purchase bundles or multiple products, classical method","authors":["Chen, Ningyuan","Farajollahzadeh, Setareh","Jin, Qingwei","Shen, Fanni","Wang, Guan"],"url":"https://arxiv.org/abs/2209.04942","arxiv_id":"2209.04942","published":"2026-07-03"},{"title":"Spintronics for image recognition: performance benchmarking via data-driven simulations","abstract":"We present a demonstration of image classification using an extreme learning machine (ELM) based on a unique simulated magnetic tunnel junction (MTJ) delayed in time. As the ground state of the MTJ is a magnetic vortex, we refer to it as a vortex-based spin-torque oscillator (STVO). The dynamics of the magnetic vortex is simulated with a model called the data-driven Thiele equation approach (DD-TEA). This allows to a","authors":["Moureaux, Anatole","Chopin, Chloé","de Wergifosse, Simon","Jacques, Laurent","Araujo, Flavio Abreu"],"url":"https://arxiv.org/abs/2308.05810","arxiv_id":"2308.05810","published":"2026-07-03"},{"title":"Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination","abstract":"Over the past decade, deep learning has proven to be a highly effective tool for learning meaningful features from raw data. However, it remains an open question how deep networks perform hierarchical feature learning across layers. In this work, we attempt to unveil this mystery by investigating the structures of intermediate features. Motivated by our empirical findings that linear layers mimic the roles of deep la","authors":["Wang, Peng","Li, Xiao","Yaras, Can","Zhu, Zhihui","Balzano, Laura","Hu, Wei"],"url":"https://arxiv.org/abs/2311.02960","arxiv_id":"2311.02960","published":"2026-07-03"},{"title":"Introduction to Transformers: an NLP Perspective","abstract":"Transformers have dominated empirical machine learning models of natural language processing. In this paper, we introduce basic concepts of Transformers and present key techniques that form the recent advances of these models. This includes a description of the standard Transformer architecture, a series of model refinements, and common applications. Given that Transformers and related deep learning techniques might ","authors":["Xiao, Tong","Zhu, Jingbo"],"url":"https://arxiv.org/abs/2311.17633","arxiv_id":"2311.17633","published":"2026-07-03"},{"title":"A global optimization SAR image segmentation model can be easily transformed to a general ROF denoising model","abstract":"In this paper, we propose a novel locally statistical active contour model (LACM) based on Aubert-Aujol (AA) denoising model and variational level set method, which can be used for SAR images segmentation with intensity inhomogeneity. Then we transform the proposed model into a global optimization model by using convex relaxation technique. Firstly, we apply the Split Bregman technique to transform the global optimiz","authors":["Liu, Guangming"],"url":"https://arxiv.org/abs/2312.08376","arxiv_id":"2312.08376","published":"2026-07-03"},{"title":"SAR image segmentation algorithms based on I-divergence-TV model","abstract":"In this paper, we propose a novel variational active contour model based on I-divergence-TV model to segment Synthetic aperture radar (SAR) images with multiplicative gamma noise, which hybrides edge-based model with region-based model. The proposed model can efficiently stop the contours at weak or blurred edges, and can automatically detect the exterior and interior boundaries of images. We further transform the pr","authors":["Liu, Guangming"],"url":"https://arxiv.org/abs/2312.09365","arxiv_id":"2312.09365","published":"2026-07-03"},{"title":"Active contours driven by local and global intensity fitting energy with application to SAR image segmentation and its fast solvers","abstract":"In this paper, we propose a novel variational active contour model based on Aubert-Aujol (AA) denoising model, which hybrides geodesic active contour (GAC) model with active contours without edges (ACWE) model and can be used to segment images corrupted by multiplicative gamma noise. We transform the proposed model into classic ROF model by adding a proximity term.[26] was submitted on 29-Aug-2013, and our early edit","authors":["Liu, Guangming"],"url":"https://arxiv.org/abs/2312.11849","arxiv_id":"2312.11849","published":"2026-07-03"},{"title":"A locally statistical active contour model for SAR image segmentation can be solved by denoising algorithms","abstract":"In this paper, we propose a novel locally statistical variational active contour model based on I-divergence-TV denoising model, which hybrides geodesic active contour (GAC) model with active contours without edges (ACWE) model, and can be used to segment images corrupted by multiplicative gamma noise. By adding a diffusion term into the level set evolution (LSE) equation of the proposed model, we construct a reactio","authors":["Liu, Guangming"],"url":"https://arxiv.org/abs/2401.10083","arxiv_id":"2401.10083","published":"2026-07-03"},{"title":"Entropic Regression DMD (ERDMD) Discovers Informative Sparse and Nonuniformly Time Delayed Models","abstract":"In this work, we present a method which determines optimal multi-step dynamic mode decomposition (DMD) models via entropic regression, which is a nonlinear information flow detection algorithm. Motivated by the higher-order DMD (HODMD) method of \\cite{clainche}, and the entropic regression (ER) technique for network detection and model construction found in \\cite{bollt, bollt2}, we develop a method that we call ERDMD","authors":["Curtis, Christopher W.","Bollt, Erik","Alford-Lago, Daniel Jay"],"url":"https://arxiv.org/abs/2406.12062","arxiv_id":"2406.12062","published":"2026-07-03"},{"title":"Event-based vision sensing and its application to pedestrian detection for intelligent transportation and surveillance","abstract":"Pedestrian detection in conventional frame-based imaging often suffers from limited temporal responsiveness and substantial data redundancy. Inspired by the biological retina, event-based vision sensing (EVS) offers ultra-low latency, high temporal resolution, wide dynamic range, and low power consumption, making it highly attractive for pedestrian perception in complex environments. This paper provides a comprehensi","authors":["Wang, Han","Wu, Juntao","Bao, Jingyuan","Liu, Min","Wang, Yaoxiong","Zhou, Saiao"],"url":"https://arxiv.org/abs/2407.04277","arxiv_id":"2407.04277","published":"2026-07-03"},{"title":"Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition","abstract":"Perturbation robustness evaluates the vulnerabilities of models, arising from a variety of perturbations, such as data corruptions and adversarial attacks. Understanding the mechanisms of perturbation robustness is critical for global interpretability. We present a model-agnostic, global mechanistic interpretability method to interpret the perturbation robustness of image models. This research is motivated by two key","authors":["Luo, Róisín","McDermott, James","O'Riordan, Colm"],"url":"https://arxiv.org/abs/2408.01139","arxiv_id":"2408.01139","published":"2026-07-03"},{"title":"MiraGe: Editable 2D Images using Gaussian Splatting","abstract":"Implicit Neural Representations (INRs) approximate discrete data through continuous functions and are commonly used for encoding 2D images. Traditional image-based INRs employ neural networks to map pixel coordinates to RGB values, capturing shapes, colors, and textures within the network's weights. Recently, GaussianImage has been proposed as an alternative, using Gaussian functions instead of neural networks to","authors":["Waczyńska, Joanna","Szczepanik, Tomasz","Borycki, Piotr","Tadeja, Sławomir","Bohné, Thomas","Spurek, Przemysław"],"url":"https://arxiv.org/abs/2410.01521","arxiv_id":"2410.01521","published":"2026-07-03"},{"title":"Evaluating Synthetic Data Generation for Domain Generalization in Fetal Brain MRI Segmentation","abstract":"Fetal brain tissue segmentation from magnetic resonance imaging (MRI) is crucial for studying neurodevelopment, but remains challenging due to data heterogeneity and limited annotations. Domain randomization (DR) has recently emerged as a promising strategy for single-source domain generalization by synthesizing training images with randomized artifacts, contrast, and resolution. In this work, we investigate how to m","authors":["Zalevskyi, Vladyslav","Sanchez, Thomas","Roulet, Margaux","Bulut, Busra","Lajous, Hélène","Verdera, Jordina Aviles"],"url":"https://arxiv.org/abs/2411.06842","arxiv_id":"2411.06842","published":"2026-07-03"},{"title":"Causal Explanations for Image Classifiers","abstract":"Existing algorithms for explaining the output of image classifiers use different definitions of explanations and a variety of techniques to find them. However, none of the existing tools use a principled approach based on formal definitions of cause and explanation. In this paper we present a novel black-box approach to computing explanations grounded in the theory of actual causality. We prove relevant theoretical r","authors":["Chockler, Hana","Kelly, David A.","Kroening, Daniel","Sun, Youcheng"],"url":"https://arxiv.org/abs/2411.08875","arxiv_id":"2411.08875","published":"2026-07-03"},{"title":"Contrastive Deep Learning Reveals Age Biomarkers in Histopathological Skin Biopsies","abstract":"As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age. Identifying biomarkers that distinguish fast from slow ageing is crucial for understanding the biology of ageing, enabling early disease detection, and improving prevention strategies. Using contrastive deep learning, we show that skin biopsy images alone are suf","authors":["Chakradeo, Kaustubh","Nielsen, Pernille","Gjerdrum, Lise Mette Rahbek","Hansen, Gry Sahl","Duchêne, David A","Mortensen, Laust H"],"url":"https://arxiv.org/abs/2411.16956","arxiv_id":"2411.16956","published":"2026-07-03"},{"title":"Towards Interactive Global Geolocation Assistant","abstract":"Global geolocation, which seeks to predict the geographical location of images captured anywhere in the world, is one of the most challenging tasks in the field of computer vision. In this paper, we introduce an innovative interactive global geolocation assistant named GaGA, built upon the flourishing large vision-language models (LVLMs). GaGA uncovers geographical clues within images and combines them with the exten","authors":["Dou, Zhiyang","Wang, Zipeng","Han, Xumeng","Li, Guorong","Huang, Zhipei","Han, Zhenjun"],"url":"https://arxiv.org/abs/2412.08907","arxiv_id":"2412.08907","published":"2026-07-03"},{"title":"A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors","abstract":"Mental health problems such as stress, anxiety, and depression affect millions of people worldwide. These conditions are usually assessed using questionnaires, which rely on how people describe their own feelings. In this study, we explore whether a wearable device can help measure mental health using physical signals from the body. The device records small changes in blood flow and tissue activity from the fingertip","authors":["Nguyen, Minh Ngoc","Le-Duc, Khai","Pham, Tan-Hanh","Nguyen, Trong Nhan","Trang, Bailey","Tran, Ba Kien"],"url":"https://arxiv.org/abs/2502.00973","arxiv_id":"2502.00973","published":"2026-07-03"},{"title":"Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework","abstract":"Recent studies identified an intriguing phenomenon in recursive generative model training known as model collapse, where models trained on data generated by previous models exhibit severe performance degradation. Addressing this issue and developing more effective training strategies have become central challenges in generative model research. In this paper, we investigate this phenomenon within a novel framework, wh","authors":["He, Hengzhi","Xu, Shirong","Cheng, Guang"],"url":"https://arxiv.org/abs/2502.18049","arxiv_id":"2502.18049","published":"2026-07-03"},{"title":"A Multi-Sensor Fusion Approach for Rapid Orthoimage Generation in Large-Scale UAV Mapping","abstract":"Rapid generation of large-scale orthoimages from Unmanned Aerial Vehicles (UAVs) has been a long-standing focus of research in the field of aerial mapping. A multi-sensor UAV system, integrating the Global Positioning System (GPS), Inertial Measurement Unit (IMU), 4D millimeter-wave radar and camera, can provide an effective solution to this problem. In this paper, we utilize multi-sensor data to overcome the limitat","authors":["He, Jialei","Zhan, Zhihao","Tu, Zhituo","Zhu, Xiang","Yuan, Jie"],"url":"https://arxiv.org/abs/2503.01202","arxiv_id":"2503.01202","published":"2026-07-03"},{"title":"Rethinking Video Super-Resolution: Towards Diffusion-Based Methods without Motion Alignment","abstract":"In this work, we rethink the approach to video super-resolution by introducing a method based on the Diffusion Posterior Sampling framework, combined with an unconditional video diffusion transformer operating in latent space. The video generation model, a diffusion transformer, functions as a space-time model. We argue that a powerful model, which learns the physics of the real world, can easily handle various kinds","authors":["Zhan, Zhihao","Pang, Wang","Zhu, Xiang","Bai, Yechao"],"url":"https://arxiv.org/abs/2503.03355","arxiv_id":"2503.03355","published":"2026-07-03"},{"title":"Split-n-Chain: Privacy-Preserving Multi-Node Split Learning with Blockchain-Based Auditability","abstract":"Deep learning, when integrated with a large amount of training data, has the potential to outperform machine learning in terms of high accuracy. Recently, privacy-preserving deep learning has drawn significant attention of the research community. Different privacy notions in deep learning include privacy of data provided by data-owners and privacy of parameters and/or hyperparameters of the underlying neural network.","authors":["Sahani, Mukesh","Sengupta, Binanda"],"url":"https://arxiv.org/abs/2503.07570","arxiv_id":"2503.07570","published":"2026-07-03"},{"title":"High-Quality Spatial Reconstruction and Orthoimage Generation Using Efficient 2D Gaussian Splatting","abstract":"Highly accurate geometric precision and dense image features characterize True Digital Orthophoto Maps (TDOMs), which are in great demand for applications such as urban planning, infrastructure management, and environmental monitoring. Traditional TDOM generation methods need sophisticated processes, such as Digital Surface Models (DSM) and occlusion detection, which are computationally expensive and prone to errors.","authors":["Wang, Qian","Zhan, Zhihao","He, Jialei","Tu, Zhituo","Yuan, Jie"],"url":"https://arxiv.org/abs/2503.19703","arxiv_id":"2503.19703","published":"2026-07-03"},{"title":"Meta-Representational Predictive Coding: Neuroscience-Informed Self-Supervised Learning","abstract":"Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence. Furthermore, evidence for self-supervised adaptation, such as contrastive formulations, has emerged in recent computational neuroscience and brain-inspired research. Nevertheless, current work on self-supervised learning relies on biologically implausible credit assignment -- in the form of backpropagation of","authors":["Ororbia, Alexander","Friston, Karl","Rao, Rajesh P. N."],"url":"https://arxiv.org/abs/2503.21796","arxiv_id":"2503.21796","published":"2026-07-03"},{"title":"Learning 3D-Gaussian Simulators from RGB Videos","abstract":"Realistic simulation is critical for applications ranging from robotics to animation. Learned simulators have emerged as a possibility to capture real world physics directly from video data, but very often require privileged information such as depth information, particle tracks and hand-engineered features to maintain spatial and temporal consistency. These strong inductive biases or ground truth 3D information help","authors":["Zhobro, Mikel","Geist, Andreas René","Martius, Georg"],"url":"https://arxiv.org/abs/2503.24009","arxiv_id":"2503.24009","published":"2026-07-03"}],"history":{"events":[{"year":2017,"text":"In the U.S. state of Arizona, the Boundary Fire (pictured) burned out after 32 days, burning 17,788 acres (7,199 ha) of the Coconino and Kaibab National Forests.","url":"https://en.wikipedia.org/wiki/Boundary_Fire_(2017)"},{"year":2013,"text":"General Abdel Fattah el-Sisi led a coalition to depose President Mohamed Morsi in a coup d'état in Cairo, suspending the Egyptian Constitution of 2012.","url":"https://en.wikipedia.org/wiki/Abdel_Fattah_el-Sisi"},{"year":2005,"text":"Same-sex marriage became legal in Spain under a law passed by the Cortes Generales.","url":"https://en.wikipedia.org/wiki/Same-sex_marriage"},{"year":1988,"text":"The US Navy warship Vincennes shot down Iran Air Flight 655 over the Persian Gulf, killing all 290 people aboard.","url":"https://en.wikipedia.org/wiki/United_States_Navy"},{"year":1979,"text":"US president Jimmy Carter signed a presidential finding, authorizing covert operations to aid the mujahideen against the Soviet-backed Democratic Republic of Afghanistan.","url":"https://en.wikipedia.org/wiki/Jimmy_Carter"},{"year":1973,"text":"British singer David Bowie retired his stage persona Ziggy Stardust in a surprise announcement on the last day of a 17-month tour.","url":"https://en.wikipedia.org/wiki/David_Bowie"},{"year":1970,"text":"Dan-Air Flight 1903 crashed into the slopes of the Montseny Massif in Catalonia, Spain, killing all 112 people aboard.","url":"https://en.wikipedia.org/wiki/Dan-Air_Flight_1903"},{"year":1970,"text":"The Troubles: The British Army began the Falls Curfew in Belfast, Northern Ireland, which resulted in greater Irish republican resistance.","url":"https://en.wikipedia.org/wiki/The_Troubles"},{"year":1952,"text":"SS United States (pictured) departed New York Harbor on her maiden voyage, on which completion she became the fastest ocean liner to cross the Atlantic.","url":"https://en.wikipedia.org/wiki/SS_United_States"},{"year":1940,"text":"Second World War: The Royal Navy attacked the French fleet at Mers El Kébir (pictured), fearing that the ships would fall into Axis hands after the French–German armistice.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1938,"text":"On the 75th anniversary of the end of the Battle of Gettysburg, U.S. President Franklin D. Roosevelt dedicated the Eternal Light Peace Memorial.","url":"https://en.wikipedia.org/wiki/1938_Gettysburg_reunion"},{"year":1863,"text":"Confederate forces were defeated by the Union Army on the last day of the Battle of Gettysburg (pictured), a turning point in the American Civil War.","url":"https://en.wikipedia.org/wiki/Confederate_States_Army"},{"year":1810,"text":"Mauritius campaign of 1809–1811: A French frigate squadron under Guy-Victor Duperré defeated a convoy of three British East Indiamen near the Comoro Islands.","url":"https://en.wikipedia.org/wiki/Mauritius_campaign_of_1809%E2%80%931811"},{"year":1778,"text":"American Revolutionary War: Loyalists and Iroquois killed over 300 Patriots at the Battle of Wyoming in Pennsylvania.","url":"https://en.wikipedia.org/wiki/American_Revolutionary_War"},{"year":1754,"text":"French and Indian War: George Washington surrendered Fort Necessity in Pennsylvania, the only military surrender in his career.","url":"https://en.wikipedia.org/wiki/French_and_Indian_War"},{"year":324,"text":"Civil wars of the Tetrarchy: Roman emperor Constantine the Great defeated his former colleague Licinius at the Battle of Adrianople.","url":"https://en.wikipedia.org/wiki/Civil_wars_of_the_Tetrarchy"}],"births":[{"year":2001,"text":"Folarin Balogun, American soccer player","url":"https://en.wikipedia.org/wiki/Folarin_Balogun"},{"year":2001,"text":"Promise David, Canadian soccer player","url":"https://en.wikipedia.org/wiki/Promise_David"},{"year":1999,"text":"Nefisa Berberović, Bosnian tennis player","url":"https://en.wikipedia.org/wiki/Nefisa_Berberovi%C4%87"},{"year":1998,"text":"Kim Dong-han, South Korean singer","url":"https://en.wikipedia.org/wiki/Kim_Dong-han"},{"year":1997,"text":"T. J. Hockenson, American football player","url":"https://en.wikipedia.org/wiki/T._J._Hockenson"},{"year":1996,"text":"Cole Tucker, American baseball player","url":"https://en.wikipedia.org/wiki/Cole_Tucker"},{"year":1996,"text":"Alex Twal, Australian-Lebanese rugby league player","url":"https://en.wikipedia.org/wiki/Alex_Twal"},{"year":1994,"text":"Chris Jones, American football player","url":"https://en.wikipedia.org/wiki/Chris_Jones_(defensive_tackle%2C_born_1994)"}],"deaths":[{"year":2025,"text":"Borja Gómez, Spanish motorcycle rider (born 2005)","url":"https://en.wikipedia.org/wiki/Borja_G%C3%B3mez_(motorcyclist)"},{"year":2025,"text":"Diogo Jota, Portuguese footballer (born 1996)","url":"https://en.wikipedia.org/wiki/Diogo_Jota"},{"year":2025,"text":"David Mabuza, South African politician, 8th Deputy President of South Africa (born 1960)","url":"https://en.wikipedia.org/wiki/David_Mabuza"},{"year":2025,"text":"Michael Madsen, American actor (born 1957)","url":"https://en.wikipedia.org/wiki/Michael_Madsen"},{"year":2025,"text":"Peter Rufai, Nigerian footballer (born 1963)","url":"https://en.wikipedia.org/wiki/Peter_Rufai"},{"year":2025,"text":"André Silva, Portuguese footballer (born 2000)","url":"https://en.wikipedia.org/wiki/Andr%C3%A9_Silva_(footballer%2C_born_2000)"},{"year":2025,"text":"Lolit Solis, Filipino talent manager, columnist and talk show host (born 1947)","url":"https://en.wikipedia.org/wiki/Lolit_Solis"},{"year":2020,"text":"Saroj Khan, Indian dance choreographer (born 1948)","url":"https://en.wikipedia.org/wiki/Saroj_Khan"}]},"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"},{"id":"frontier","name":"Hacker News","url":"https://news.ycombinator.com","licence":"Public API — titles and links, credited","attribution":"Hacker News / Y Combinator"},{"id":"research","name":"arXiv cs.AI","url":"https://arxiv.org","licence":"Open metadata, per arXiv API terms","attribution":"arXiv.org"},{"id":"history","name":"Wikipedia On this day","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"}],"licence":"Records are CC BY-SA 4.0, inheriting from Wikipedia. Every item links to its source."}