{"date":"2026-07-20","schema_version":1,"captured_at":"2026-08-25T23:17:13.488Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Lamine Yamal","views":1200352,"rank":3,"extract":"Lamine Yamal Nasraoui Ebana, commonly known as Lamine Yamal, is a Spanish professional footballer who plays as a right winger for the La Liga club Barcelona and the Spain national team. 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Immersive Gaussian Splat tour of grace cathedral, San Francisco","points":263,"comments":60,"url":"https://vincentwoo.com/3d/grace_cathedral/","discussion":"https://news.ycombinator.com/item?id=48984254"}],"research":[{"title":"Representation Recycling for Streaming Video Analysis","abstract":"We present StreamDEQ, a method that aims to infer frame-wise representations on videos with minimal per-frame computation. Conventional deep networks perform feature extraction from scratch at each frame in the absence of ad-hoc solutions. We instead aim to build streaming recognition models that can natively exploit temporal smoothness between consecutive video frames. We observe that the recently emerging implicit ","authors":["Ertenli, Can Ufuk","Cinbis, Ramazan Gokberk","Akbas, Emre"],"url":"https://arxiv.org/abs/2204.13492","arxiv_id":"2204.13492","published":"2026-07-20"},{"title":"Perception-Aligned AI Outputs: End-to-End Visual Prediction for Uncertainty Communication in Clinical Decision-Making","abstract":"Explainable Artificial Intelligence (XAI) is essential for trustworthy AI in healthcare, yet many existing methods rely on technical explanations that are difficult for clinicians and patients to interpret. We introduce Visualized Learning for Machine Learning (VL4ML), a human-centered explainability framework that communicates model predictions and uncertainty through intuitive visual representations rather than num","authors":["Eslami, Mohammad","Tabarestani, Solale","Kazeminasab, Saber","Adeli, Ehsan","Elwyn, Glyn","Elze, Tobias"],"url":"https://arxiv.org/abs/2205.04599","arxiv_id":"2205.04599","published":"2026-07-20"},{"title":"Learn to Memorize: Scalable Continual Learning in Semiparametric Models with Mixture-of-Neighbors Induction Memory","abstract":"Semiparametric language models (LMs) have shown promise in various Natural Language Processing (NLP) tasks. However, they utilize non-parametric memory as static storage, which lacks learning capability and remains disconnected from the internal information flow of the parametric models, limiting scalability and efficiency. Based on recent interpretability theories of LMs, we reconceptualize the non-parametric memory","authors":["Peng, Guangyue","Ge, Tao","Luo, Wen","Li, Wei","Wang, Houfeng"],"url":"https://arxiv.org/abs/2303.01421","arxiv_id":"2303.01421","published":"2026-07-20"},{"title":"GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content","abstract":"The mobile cloud gaming industry has been rapidly growing over the last decade. When streaming gaming videos are transmitted to customers' client devices from cloud servers, algorithms that can monitor distorted video quality without having any reference video available are desirable tools. However, creating No-Reference Video Quality Assessment (NR VQA) models that can accurately predict the quality of streaming","authors":["Chen, Yu-Chih","Saha, Avinab","Davis, Chase","Qiu, Bo","Wang, Xiaoming","Gowda, Rahul"],"url":"https://arxiv.org/abs/2305.02422","arxiv_id":"2305.02422","published":"2026-07-20"},{"title":"Comprehensive Dataset of Synthetic and Manipulated Overhead Imagery for Development and Evaluation of Forensic Tools","abstract":"We present a first of its kind dataset of overhead imagery for development and evaluation of forensic tools. Our dataset consists of real, fully synthetic and partially manipulated overhead imagery generated from a custom diffusion model trained on two sets of different zoom levels and on two sources of pristine data. We developed our model to support controllable generation of multiple manipulation categories includ","authors":["May, Brandon B.","Trapeznikov, Kirill","Fang, Shengbang","Stamm, Matthew C."],"url":"https://arxiv.org/abs/2305.05784","arxiv_id":"2305.05784","published":"2026-07-20"},{"title":"Why do CNNs excel at feature extraction? A mathematical explanation","abstract":"Over the past decade deep learning has revolutionized the field of computer vision, with convolutional neural network models proving to be very effective for image classification benchmarks. However, a fundamental theoretical questions remain answered: why can they solve discrete image classification tasks that involve feature extraction? We address this question in this paper by introducing a novel mathematical mode","authors":["Nandakumar, Vinoth","Tagade, Arush","Liu, Tongliang"],"url":"https://arxiv.org/abs/2307.00919","arxiv_id":"2307.00919","published":"2026-07-20"},{"title":"Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning","abstract":"A central question of network science is how functional properties of systems emerge from their structure. For networked dynamical systems, structure is typically captured through network measures. We investigate the relationship between these measures and stability metrics across non-linear and linear oscillators, as well as real-world power grid topologies and dynamics. We find that this relationship is highly sens","authors":["Nauck, Christian","Lindner, Michael","Molkenthin, Nora","Kurths, Jürgen","Schöll, Eckehard","Raisch, Jörg"],"url":"https://arxiv.org/abs/2402.17500","arxiv_id":"2402.17500","published":"2026-07-20"},{"title":"Decoupled Alignment for Robust Plug-and-Play Adaptation","abstract":"We introduce a training-free safety enhancement method for aligning large language models (LLMs) without the need for supervised fine-tuning or reinforcement learning from human feedback. Our main idea is to provide a robust plug-and-play approach to prevent shadow alignment when models are adapted to downstream tasks. Specifically, we leverage knowledge distillation to extract alignment signals from well-aligned LLM","authors":["Luo, Haozheng","Yu, Jiahao","Zhang, Wenxin","Li, Jialong","Qiu, Chenghao","Wang, Yimin"],"url":"https://arxiv.org/abs/2406.01514","arxiv_id":"2406.01514","published":"2026-07-20"},{"title":"AutoSpec: Automated Generation of Neural Network Specifications","abstract":"The increasing adoption of neural networks in learning-augmented systems highlights the growing need for model safety and robustness, especially in safety-critical domains. While recent advances in neural network verification offer formal guarantees on worst-case behavior, existing approaches require users to manually define model specifications, an error-prone, incomplete, and time-consuming process. In this paper, ","authors":["Jin, Shuowei","Liao, Taobo","Kalia, Anuj","Foukas, Xenofon","Zhang, Huan","Tan, Cheng"],"url":"https://arxiv.org/abs/2409.10897","arxiv_id":"2409.10897","published":"2026-07-20"},{"title":"Robust Random Graph Matching in Dense Graphs via an Approximate Message Passing Type Algorithm","abstract":"In this paper, we focus on the matching recovery problem between a pair of correlated Gaussian Wigner matrices with a latent vertex correspondence. We are particularly interested in a robust version of this problem such that our observation is a perturbed input $(A+E,B+F)$ where $(A,B)$ is a pair of correlated Gaussian Wigner matrices and $E,F$ are adversarially chosen matrices supported on an unknown $εn * εn$ princ","authors":["Li, Zhangsong"],"url":"https://arxiv.org/abs/2412.16457","arxiv_id":"2412.16457","published":"2026-07-20"},{"title":"Multi-SpaCE: Multi-Objective Subsequence-based Sparse Counterfactual Explanations for Multivariate Time Series Classification","abstract":"Deep Learning systems excel in complex tasks but often lack transparency, limiting their use in critical applications. Counterfactual explanations, a core tool within eXplainable Artificial Intelligence (XAI), offer insights into model decisions by identifying minimal changes to an input to alter its predicted outcome. However, existing methods for time series data are limited by univariate assumptions, rigid constra","authors":["Refoyo, Mario","Luengo, David"],"url":"https://arxiv.org/abs/2501.04009","arxiv_id":"2501.04009","published":"2026-07-20"},{"title":"Derivation of effective gradient flow equations and dynamical truncation of training data in Deep Learning","abstract":"We derive explicit equations governing the cumulative biases and weights in Deep Learning with ReLU activation function, based on gradient descent for the Euclidean loss in the input layer, and under the assumption that the weights are, in a precise sense, adapted to the coordinate system distinguished by the activations. We show that gradient descent corresponds to a dynamical process in the input layer, whereby clu","authors":["Chen, Thomas"],"url":"https://arxiv.org/abs/2501.07400","arxiv_id":"2501.07400","published":"2026-07-20"},{"title":"CTC: The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning","abstract":"The critical role of division of labor (DOL) in enhancing cooperation is well-recognized in real-world applications. Consequently, many cooperative multi-agent reinforcement learning (MARL) methods have incorporated DOL mechanisms to improve cooperation among agents. However, the lack of benchmark tasks specifically designed to evaluate and promote DOL and cooperation has limited the effective development and deploym","authors":["Li, Yurui","Chen, Yuxuan","Yang, Xiaoli","Li, Shijian","Pan, Gang"],"url":"https://arxiv.org/abs/2502.00345","arxiv_id":"2502.00345","published":"2026-07-20"},{"title":"Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation","abstract":"Recent works modify CLIP to perform open-vocabulary semantic segmentation in a training-free manner (TF-OVSS). In vanilla CLIP, patch-wise image representations mainly encode homogeneous image-level properties, which hinders the application of CLIP to the dense prediction task. Previous TF-OVSS works sacrifice globality to enhance the locality of CLIP features, by making each patch mainly attend to itself or its neig","authors":["Wang, Jingyun","Yan, Cilin","Kang, Guoliang"],"url":"https://arxiv.org/abs/2502.06818","arxiv_id":"2502.06818","published":"2026-07-20"},{"title":"MAnchors: Memorization-Based Acceleration of Anchors via Rule Reuse and Transformation","abstract":"Anchors is a popular local model-agnostic explanation technique whose applicability is limited by its computational inefficiency. To address this limitation, we propose a memorization-based framework that accelerates Anchors while preserving explanation fidelity and interpretability. Our approach leverages the iterative nature of Anchors' algorithm which gradually refines an explanation until it is precise enough","authors":["Yu, Haonan","Liu, Junhao","Zhang, Xin"],"url":"https://arxiv.org/abs/2502.11068","arxiv_id":"2502.11068","published":"2026-07-20"},{"title":"Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipeline","abstract":"Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carcinoma and liver cirrhosis, often requires interpreting semantically complex criteria. Traditional manual screening methods are time-consuming and prone to errors. While AI-powered pre-screening offers potential solutions, challenges remain regarding accuracy, efficiency, and data privacy. Methods: We developed a novel pat","authors":["Gui, Xiongbin","Lv, Hanlin","Wang, Xiao","Lv, Longting","Xiao, Yi","Wang, Lei"],"url":"https://arxiv.org/abs/2502.18531","arxiv_id":"2502.18531","published":"2026-07-20"},{"title":"A Systematic Review of ECG Arrhythmia Classification: Adherence to Standards, Fair Evaluation, and Embedded Feasibility","abstract":"The classification of electrocardiogram (ECG) signals is crucial for early detection of arrhythmias and other cardiac conditions. However, despite advances in machine learning, many studies fail to follow standardization protocols, leading to inconsistencies in performance evaluation and real-world applicability. Additionally, hardware constraints essential for practical deployment, such as in pacemakers, Holter moni","authors":["Silva, Guilherme","Silva, Pedro","Moreira, Gladston","Freitas, Vander","Gertrudes, Jadson","Luz, Eduardo"],"url":"https://arxiv.org/abs/2503.07276","arxiv_id":"2503.07276","published":"2026-07-20"},{"title":"Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs","abstract":"Seamless operation of mobile robots in challenging environments requires low-latency local motion estimation and accurate global localization. While most sensor-fusion approaches are designed for specific scenarios, this work introduces a flexible open-source solution for task- and setup-agnostic multimodal sensor fusion distinguished by its generality and usability. Holistic Fusion formulates sensor fusion as a comb","authors":["Nubert, Julian","Tuna, Turcan","Frey, Jonas","Cadena, Cesar","Kuchenbecker, Katherine J.","Khattak, Shehryar"],"url":"https://arxiv.org/abs/2504.06479","arxiv_id":"2504.06479","published":"2026-07-20"},{"title":"A Scaffolded GenAI Lab in Early Undergraduate CS: A Mixed-Methods, Multi-Course Evaluation","abstract":"Background and Context. Generative AI (GenAI) tools are increasingly used in programming courses, but we have limited evidence about how brief instruction can foster responsible, learning-oriented use. Objectives. We evaluate "AI-Lab", a scaffolded GenAI literacy intervention, asking how students' self-reported GenAI usage and their openness and comfort using GenAI for conceptual, debugging, and homework ","authors":["Dickey, Ethan","Bejarano, Andres","Kuperus, Rhianna","Fagundes, Bárbara"],"url":"https://arxiv.org/abs/2505.00100","arxiv_id":"2505.00100","published":"2026-07-20"},{"title":"SLAC: Safe and Efficient Real-Robot Reinforcement Learning via Unsupervised Simulation Pre-Training","abstract":"Building capable household and industrial robots requires mastering the control of versatile, high-degree-of-freedom (DoF) systems such as mobile manipulators. While reinforcement learning (RL) holds promise for autonomously acquiring robot control policies, scaling it to high-DoF embodiments remains challenging. Direct RL in the real world demands both safe exploration and high sample efficiency, which are difficult","authors":["Hu, Jiaheng","Stone, Peter","Martín-Martín, Roberto"],"url":"https://arxiv.org/abs/2506.04147","arxiv_id":"2506.04147","published":"2026-07-20"},{"title":"Honesty in Causal Forests: When It Helps and When It Hurts","abstract":"Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and public policy. A standard practice is honest estimation: dividing the data into two samples, one to define subgroups and another to estimate treatment effects within them. This is intended to reduce overfitting and is the default in many software packages. But is it the ri","authors":["Hou, Yanfang","Fernández-Loría, Carlos"],"url":"https://arxiv.org/abs/2506.13107","arxiv_id":"2506.13107","published":"2026-07-20"},{"title":"A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects","abstract":"Video Scene Parsing (VSP) studies dense video understanding, where every pixel in each frame must be segmented, each region must be named, and each object identity must remain coherent over time. This survey reviews recent progress in VSP across five tasks, spanning Video Semantic Segmentation (VSS), Video Instance Segmentation (VIS), Video Panoptic Segmentation (VPS), Video Tracking \\& Segmentation (VTS), and Op","authors":["Xie, Guohuan","Hesham, Syed Ariff Syed","Guo, Wenya","Li, Bing","Cheng, Ming-Ming","Sun, Guolei"],"url":"https://arxiv.org/abs/2506.13552","arxiv_id":"2506.13552","published":"2026-07-20"},{"title":"Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection","abstract":"Detecting deceptive conversations on dynamic platforms is increasingly difficult due to evolving language patterns and Concept Drift (CD)-i.e., semantic or topical shifts that alter the context or intent of interactions over time. These shifts can obscure malicious intent or mimic normal dialogue, making accurate classification challenging. While Large Language Models (LLMs) show strong performance in natural languag","authors":["Şenol, Ali","Agrawal, Garima","Liu, Huan"],"url":"https://arxiv.org/abs/2506.21443","arxiv_id":"2506.21443","published":"2026-07-20"},{"title":"Interpretable Role-Based Clustering in Multi-Layer Financial Networks","abstract":"Understanding the functional roles of financial institutions within interconnected markets is critical for effective supervision, systemic risk assessment, and resolution planning. We propose an interpretable role-based clustering approach for multi-layer financial networks, designed to identify the functional positions of institutions across different market segments. Our method follows a general clustering framewor","authors":["Franssen, Christian","Le, Thao","van Lelyveld, Iman","Heidergott, Bernd"],"url":"https://arxiv.org/abs/2507.00600","arxiv_id":"2507.00600","published":"2026-07-20"},{"title":"EGO: a Recursive and Self-Referential Cognitive Architecture for Artificial General Intelligence","abstract":"Artificial General Intelligence (AGI) is interpreted as an emergent property of autonomous and self-organizing systems, grounded in the principles of autopoiesis and embodied cognition, overcoming the structural limitations of current Large Language Models (LLMs). We introduce EGO (Environment Generative Operator), a software architecture based on the formal E-language, capable of self-referentiality and of maintaini","authors":["Mangiante, Alberto","Totaro, Paolo","Ninno, Domenico"],"url":"https://arxiv.org/abs/2507.14011","arxiv_id":"2507.14011","published":"2026-07-20"}],"history":{"events":[{"year":2015,"text":"A suicide attack (aftermath pictured) in Suruç, Turkey, for which Islamic State of Iraq and the Levant (ISIL) claimed responsibility, killed 34 people and injured 104 others.","url":"https://en.wikipedia.org/wiki/Suru%C3%A7_bombing"},{"year":2012,"text":"A gunman carried out a mass shooting at a movie theater in Aurora, Colorado, killing 12 people and injuring 58 others.","url":"https://en.wikipedia.org/wiki/James_Holmes_(mass_murderer)"},{"year":2001,"text":"Twenty-three-year-old Italian anti-globalist Carlo Giuliani was shot dead by a police officer while protesting outside the 27th G8 summit held in Genoa, Italy.","url":"https://en.wikipedia.org/wiki/Death_of_Carlo_Giuliani"},{"year":1997,"text":"USS Constitution, one of the United States Navy's original six frigates, sailed for the first time in 116 years after a full restoration.","url":"https://en.wikipedia.org/wiki/USS_Constitution"},{"year":1982,"text":"Members of the Provisional Irish Republican Army detonated two bombs in Hyde Park and Regent's Park in London, killing eleven British Army personnel and seven horses.","url":"https://en.wikipedia.org/wiki/Provisional_Irish_Republican_Army"},{"year":1977,"text":"Rain from a stalled thunderstorm caused six dams to fail, flooding Johnstown, Pennsylvania, resulting in 84 deaths and $340 in damages.","url":"https://en.wikipedia.org/wiki/Johnstown_flood_of_1977"},{"year":1976,"text":"The Viking 1 lander became the first spacecraft to successfully land on Mars and perform its mission.","url":"https://en.wikipedia.org/wiki/Viking_1"},{"year":1969,"text":"The Apollo 11 Lunar Module Eagle landed on the Sea of Tranquillity, where Neil Armstrong and Buzz Aldrin became the first men to walk on the Moon six and a half hours later (bootprint pictured).","url":"https://en.wikipedia.org/wiki/Apollo_11"},{"year":1968,"text":"The first games of the Special Olympics (athletes pictured), for athletes with intellectual disabilities, were held at Soldier Field in Chicago.","url":"https://en.wikipedia.org/wiki/1968_Special_Olympics_World_Summer_Games"},{"year":1951,"text":"Abdullah I of Jordan was assassinated while visiting the Al-Aqsa Mosque in Jerusalem.","url":"https://en.wikipedia.org/wiki/Abdullah_I_of_Jordan"},{"year":1950,"text":"Korean War: After a month-long campaign, much of the North Korean air force was destroyed by United Nations forces.","url":"https://en.wikipedia.org/wiki/Korean_War"},{"year":1936,"text":"The July 1936 military uprising in Barcelona is defeated by anarchist militias and Republican loyalists, beginning the Spanish Revolution of 1936.","url":"https://en.wikipedia.org/wiki/July_1936_military_uprising_in_Barcelona"},{"year":1917,"text":"Serbian prime minister Nikola Pašić and Yugoslav Committee president Ante Trumbić signed the Corfu Declaration, agreeing to seek the establishment of the Kingdom of Serbs, Croats, and Slovenes.","url":"https://en.wikipedia.org/wiki/Nikola_Pa%C5%A1i%C4%87"},{"year":1914,"text":"George V reviewed more than 200 Royal Navy vessels at Spithead, England.","url":"https://en.wikipedia.org/wiki/George_V"},{"year":1867,"text":"The United States Congress established the Indian Peace Commission to seek peace treaties with a number of Native American tribes.","url":"https://en.wikipedia.org/wiki/United_States_Congress"},{"year":1807,"text":"French brothers Claude and Nicéphore Niépce received a patent for their Pyréolophore, one of the world's first internal combustion engines.","url":"https://en.wikipedia.org/wiki/Claude_Ni%C3%A9pce"},{"year":1793,"text":"Scottish explorer Alexander Mackenzie reached the Pacific coast at Bella Coola, British Columbia, completing the first recorded transcontinental crossing of North America north of Mexico.","url":"https://en.wikipedia.org/wiki/Alexander_Mackenzie_(explorer)"},{"year":1651,"text":"Wars of the Three Kingdoms: After crossing the Firth of Forth, English Commonwealth forces defeated a Scottish army at the Battle of Inverkeithing, opening the rest of the country to occupation.","url":"https://en.wikipedia.org/wiki/Wars_of_the_Three_Kingdoms"}],"births":[{"year":2001,"text":"Álex Baena, Spanish footballer","url":"https://en.wikipedia.org/wiki/%C3%81lex_Baena"},{"year":1999,"text":"Pop Smoke, American rapper and singer (died 2020)","url":"https://en.wikipedia.org/wiki/Pop_Smoke"},{"year":1999,"text":"Goga Bitadze, Georgian basketball player","url":"https://en.wikipedia.org/wiki/Goga_Bitadze"},{"year":1998,"text":"Morgan Geekie, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Morgan_Geekie"},{"year":1996,"text":"Ben Simmons, Australian basketball player","url":"https://en.wikipedia.org/wiki/Ben_Simmons"},{"year":1995,"text":"Moses Leota, New Zealand rugby league player","url":"https://en.wikipedia.org/wiki/Moses_Leota"},{"year":1994,"text":"Maia Shibutani, American ice dancer","url":"https://en.wikipedia.org/wiki/Maia_Shibutani"},{"year":1993,"text":"Steven Adams, New Zealand basketball player","url":"https://en.wikipedia.org/wiki/Steven_Adams"}],"deaths":[{"year":2025,"text":"Malcolm-Jamal Warner, American actor (born 1970)","url":"https://en.wikipedia.org/wiki/Malcolm-Jamal_Warner"},{"year":2024,"text":"Jerry Miller, American songwriter, guitarist and vocalist (born 1943)","url":"https://en.wikipedia.org/wiki/Jerry_Miller"},{"year":2024,"text":"Jill Schary Robinson, American novelist (born 1936)","url":"https://en.wikipedia.org/wiki/Jill_Schary_Robinson"},{"year":2020,"text":"Michael Brooks, political commentator (born 1983)","url":"https://en.wikipedia.org/wiki/Michael_Brooks_(political_commentator)"},{"year":2017,"text":"Chester Bennington, American singer (born 1976)","url":"https://en.wikipedia.org/wiki/Chester_Bennington"},{"year":2016,"text":"Radu Beligan, Romanian actor, director, and essayist (born 1918)","url":"https://en.wikipedia.org/wiki/Radu_Beligan"},{"year":2015,"text":"Wayne Carson, American singer-songwriter and producer (born 1943)","url":"https://en.wikipedia.org/wiki/Wayne_Carson"},{"year":2015,"text":"Fred Else, English footballer and manager (born 1933)","url":"https://en.wikipedia.org/wiki/Fred_Else"}]},"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 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Every item links to its source."}