{"date":"2026-04-10","schema_version":1,"captured_at":"2026-08-25T23:35:56.642Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Dhurandhar: The Revenge","views":219612,"rank":5,"extract":"Dhurandhar: The Revenge is a 2026 Indian Hindi-language spy action-thriller film written and directed by Aditya Dhar. It is produced by Dhar, Lokesh Dhar, and Jyoti Deshpande under Jio Studios and B62 Studios. 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For unknown reasons, the town's name was spelled as Neetsvil","url":"https://en.wikipedia.org/wiki/Neatsville%2C_Kentucky","thumb":null},{"title":"Mill Basin, Brooklyn","views":96073,"rank":16,"extract":"Mill Basin is a residential neighborhood in southeastern Brooklyn, New York City. It is on a peninsula abutting Jamaica Bay and is bordered by Avenue U on the northwest and the Mill Basin/Mill Island Inlet on its remaining sides. Mill Basin is adjacent to the ","url":"https://en.wikipedia.org/wiki/Mill_Basin%2C_Brooklyn","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/3/36/Mill_Basin_jeh.JPG/330px-Mill_Basin_jeh.JPG?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Lebanon","views":91535,"rank":17,"extract":"Lebanon, officially the Lebanese Republic, is a country in the Levant region of West Asia. 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Bambaataa w","url":"https://en.wikipedia.org/wiki/Afrika_Bambaataa","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/df/Africa_bambaataa-08.jpg/330px-Africa_bambaataa-08.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"2016 NHL Stadium Series","views":76945,"rank":26,"extract":"The 2016 NHL Stadium Series was a series of two outdoor regular season National Hockey League (NHL) games played during the 2015–16 NHL season. 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The votes were counted and the results were declared on 4 May 2026 by the Election Commission of India.","url":"https://en.wikipedia.org/wiki/2026_Puducherry_Legislative_Assembly_election","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/e/ee/N._Rangaswamy_%28cropped%29.jpg/330px-N._Rangaswamy_%28cropped%29.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Avignon Papacy","views":70388,"rank":32,"extract":"The Avignon Papacy was the period from 1309 to 1376 during which seven successive popes resided in Avignon rather than in Rome. The situation arose from the conflict between the papacy and the French crown, culminating in the death of Pope Boniface VIII after ","url":"https://en.wikipedia.org/wiki/Avignon_Papacy","thumb":null},{"title":"Limonene","views":69499,"rank":33,"extract":"Limonene is a slightly yellow-green liquid aliphatic hydrocarbon classified as a cyclic monoterpene, and is the major component in the fragrance and essential oil of citrus fruit peels, taking its name from Italian limone (\"lemon\").","url":"https://en.wikipedia.org/wiki/Limonene","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/c/cb/Limonene.jpg/330px-Limonene.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Euphoria (American TV series)","views":66910,"rank":34,"extract":"Euphoria is an American psychological drama television series created and written by Sam Levinson for HBO. 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to the Linux kernel","points":527,"comments":436,"url":"https://github.com/torvalds/linux/blob/master/Documentation/process/coding-assistants.rst","discussion":"https://news.ycombinator.com/item?id=47721953"},{"title":"You can't trust macOS Privacy and Security settings","points":512,"comments":170,"url":"https://eclecticlight.co/2026/04/10/why-you-cant-trust-privacy-security/","discussion":"https://news.ycombinator.com/item?id=47719602"},{"title":"I still prefer MCP over skills","points":460,"comments":375,"url":"https://david.coffee/i-still-prefer-mcp-over-skills/","discussion":"https://news.ycombinator.com/item?id=47712718"},{"title":"Industrial design files for Keychron keyboards and mice","points":460,"comments":149,"url":"https://github.com/Keychron/Keychron-Keyboards-Hardware-Design","discussion":"https://news.ycombinator.com/item?id=47720419"},{"title":"OpenAI backs Illinois bill that would limit when AI labs can be held 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gate using a geometric phase","points":241,"comments":57,"url":"https://ethz.ch/en/news-and-events/eth-news/news/2026/04/a-new-trick-brings-stability-to-quantum-operations.html","discussion":"https://news.ycombinator.com/item?id=47713495"},{"title":"New iPhone age and identity checks restrict internet freedom in the UK","points":231,"comments":144,"url":"https://bigbrotherwatch.org.uk/blog/apples-new-iphone-update-is-restricting-internet-freedom-in-the-uk/","discussion":"https://news.ycombinator.com/item?id=47712222"}],"research":[{"title":"Tabular GANs for uneven distribution","abstract":"Generative models for tabular data have evolved rapidly beyond Generative Adversarial Networks (GANs). While GANs pioneered synthetic tabular data generation, recent advances in diffusion models and large language models (LLMs) have opened new paradigms with complementary strengths in sample quality, privacy, and controllability. In this paper, we survey the landscape of tabular data generation across three major par","authors":["Ashrapov, Insaf"],"url":"https://arxiv.org/abs/2010.00638","arxiv_id":"2010.00638","published":"2026-04-10"},{"title":"Tractable Uncertainty-Aware Meta-Learning","abstract":"Meta-learning is a popular approach for learning new tasks with limited data by leveraging the commonalities among different tasks. However, meta-learned models can perform poorly when context data is too limited, or when data is drawn from an out-of-distribution (OoD) task. Especially in safety-critical settings, this necessitates an uncertainty-aware approach to meta-learning. In addition, the often multimodal natu","authors":["Park, Young-Jin","Almecija, Cesar","Sharma, Apoorva","Azizan, Navid"],"url":"https://arxiv.org/abs/2210.01881","arxiv_id":"2210.01881","published":"2026-04-10"},{"title":"An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications","abstract":"Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in modern computer science. This automated survey provides an accessible treatment of the field as of early 2026, with a strong focus on the leading model families, deployment protocols, and real-world applications. The core of the survey is devoted to a detailed comparative analysis o","authors":["Garrido-Merchán, Eduardo C.","López, Álvaro López"],"url":"https://arxiv.org/abs/2306.02781","arxiv_id":"2306.02781","published":"2026-04-10"},{"title":"Language Guided Adversarial Purification","abstract":"Adversarial purification using generative models demonstrates strong adversarial defense performance. These methods are classifier and attack-agnostic, making them versatile but often computationally intensive. Recent strides in diffusion and score networks have improved image generation and, by extension, adversarial purification. Another highly efficient class of adversarial defense methods known as adversarial tra","authors":["Singh, Himanshu","Subramanyam, A V"],"url":"https://arxiv.org/abs/2309.10348","arxiv_id":"2309.10348","published":"2026-04-10"},{"title":"Diff-PCR: Diffusion-Based Correspondence Searching in Doubly Stochastic Matrix Space for Point Cloud Registration","abstract":"Efficiently identifying accurate correspondences between point clouds is crucial for both rigid and non-rigid point cloud registration. Existing methods usually rely on geometric or semantic feature embeddings to establish correspondences and then estimate transformations or flow fields. Recently, several state-of-the-art methods have adopted RAFT-like iterative updates to refine solutions. However, these methods sti","authors":["Shi, Haihua","Wu, Qianliang"],"url":"https://arxiv.org/abs/2401.00436","arxiv_id":"2401.00436","published":"2026-04-10"},{"title":"A Survey on 3D Gaussian Splatting","abstract":"3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for an explicit scene representation. Paired with a differentiable rendering algorithm, this approach achieves real-time rendering and unprecedented editability, making it a potential game-changer for 3D reconstruction and representation. In t","authors":["Chen, Guikun","Wang, Wenguan"],"url":"https://arxiv.org/abs/2401.03890","arxiv_id":"2401.03890","published":"2026-04-10"},{"title":"Graph-based Active Learning for Entity Cluster Repair","abstract":"Cluster repair methods aim to determine errors in clusters and modify them so that each cluster consists of records representing the same entity. Current cluster repair methodologies primarily assume duplicate-free data sources, where each record from one source corresponds to a unique record from another. However, real-world data often deviates from this assumption due to quality issues. Recent approaches apply clus","authors":["Christen, Victor","Obraczka, Daniel","Hofer, Marvin","Franke, Martin","Rahm, Erhard"],"url":"https://arxiv.org/abs/2401.14992","arxiv_id":"2401.14992","published":"2026-04-10"},{"title":"Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss","abstract":"Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is important for the encoder to recognize and compress the information necessary for the machine recognition task. There are two main approaches in learned ICM; optimization of the compression model based on task loss, and Region of Interest (ROI) based bit allocation. Thes","authors":["Iino, Kei","Akamatsu, Shunsuke","Watanabe, Hiroshi","Enomoto, Shohei","Sakamoto, Akira","Eda, Takeharu"],"url":"https://arxiv.org/abs/2402.08267","arxiv_id":"2402.08267","published":"2026-04-10"},{"title":"Reconstructing the Geometry of Random Geometric Graphs","abstract":"Random geometric graphs are random graph models defined on metric spaces. Such a model is defined by first sampling points from a metric space and then connecting each pair of sampled points with probability that depends on their distance, independently among pairs. In this work, we show how to efficiently reconstruct the geometry of the underlying space from the sampled graph under the manifold assumption, i.e., ass","authors":["Huang, Han","Jiradilok, Pakawut","Mossel, Elchanan"],"url":"https://arxiv.org/abs/2402.09591","arxiv_id":"2402.09591","published":"2026-04-10"},{"title":"A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representation","abstract":"We introduce a novel approach for the reconstruction of tubular shapes from skeletal representations. Our method processes all skeletal points as a whole, eliminating the need for splitting input structure into multiple segments. We represent the tubular shape as a truncated signed distance function (TSDF) in a voxel hashing manner, in which the signed distance between a voxel center and the object is computed throug","authors":["Zhang, Guoqing","Li, Yang"],"url":"https://arxiv.org/abs/2402.12797","arxiv_id":"2402.12797","published":"2026-04-10"},{"title":"Time series generation for option pricing on quantum computers using tensor network","abstract":"Finance, especially option pricing, is a promising industrial field that might benefit from quantum computing. While quantum algorithms for option pricing have been proposed, it is desired to devise more efficient implementations of costly operations in the algorithms, one of which is preparing a quantum state that encodes a probability distribution of the underlying asset price. In particular, in pricing a path-depe","authors":["Kobayashi, Nozomu","Suimon, Yoshiyuki","Miyamoto, Koichi"],"url":"https://arxiv.org/abs/2402.17148","arxiv_id":"2402.17148","published":"2026-04-10"},{"title":"CODA: A Continuous Online Evolve Framework for Deploying HAR Sensing Systems","abstract":"In always-on HAR deployments, model accuracy erodes silently as domain shift accumulates over time. Addressing this challenge requires moving beyond one-off updates toward instance-driven adaptation from streaming data. However, continuous adaptation exposes a fundamental tension: systems must selectively learn from informative instances while actively forgetting obsolete ones under long-term, non-stationary drift. T","authors":["Qiu, Minghui","Chen, Jun","Chen, Lin","Zhong, Shuxin","Huang, Yandao","Wang, Lu"],"url":"https://arxiv.org/abs/2403.14922","arxiv_id":"2403.14922","published":"2026-04-10"},{"title":"Coupled generator decomposition for fusion of electro- and magnetoencephalography data","abstract":"Data fusion modeling can identify common features across diverse data sources while accounting for source-specific variability. Here we introduce the concept of a \\textit{coupled generator decomposition} and demonstrate how it generalizes sparse principal component analysis (SPCA) for data fusion. Leveraging data from a multisubject, multimodal (electro- and magnetoencephalography (EEG and MEG)) neuroimaging experime","authors":["Olsen, Anders Stevnhoved","Nielsen, Jesper Duemose","Mørup, Morten"],"url":"https://arxiv.org/abs/2403.15409","arxiv_id":"2403.15409","published":"2026-04-10"},{"title":"Deep Privacy Funnel Model: From a Discriminative to a Generative Approach with an Application to Face Recognition","abstract":"In this study, we apply the information-theoretic Privacy Funnel (PF) model to face recognition and develop a method for privacy-preserving representation learning within an end-to-end trainable framework. Our approach addresses the trade-off between utility and obfuscation of sensitive information under logarithmic loss. We study the integration of information-theoretic privacy principles with representation learnin","authors":["Razeghi, Behrooz","Rahimi, Parsa","Marcel, Sébastien"],"url":"https://arxiv.org/abs/2404.02696","arxiv_id":"2404.02696","published":"2026-04-10"},{"title":"Neural Green's Operators for Parametric Partial Differential Equations","abstract":"This work introduces a paradigm for constructing parametric neural operators that are derived from finite-dimensional representations of Green's operators for linear partial differential equations (PDEs). We refer to such neural operators as Neural Green's Operators (NGOs). Our construction of NGOs preserves the linear action of Green's operators on the inhomogeneity fields, while approximating the nonlin","authors":["Melchers, Hugo","Prins, Joost","Abdelmalik, Michael"],"url":"https://arxiv.org/abs/2406.01857","arxiv_id":"2406.01857","published":"2026-04-10"},{"title":"FinTruthQA: A Benchmark for AI-Driven Financial Disclosure Quality Assessment in Investor -- Firm Interactions","abstract":"Accurate and transparent financial information disclosure is essential for market efficiency, investor decision-making, and corporate governance. Chinese stock exchanges' investor interactive platforms provide a widely used channel through which listed firms respond to investor concerns, yet these responses are often limited or non-substantive, making disclosure quality difficult to assess at scale. To address th","authors":["Zhou, Peilin","Xu, Ziyue","Shi, Xinyu","Wu, Jiageng","Jiang, Yikang","Chong, Dading"],"url":"https://arxiv.org/abs/2406.12009","arxiv_id":"2406.12009","published":"2026-04-10"},{"title":"NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation","abstract":"Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navigation necessitates the implementation of perception algorithms, often deep neural networks (DNN), that process the input of sensor observations, such as that from cameras and LiDARs, for control logic. The complexity of such algorithms clashes with the severe constraints","authors":["Johnsen, Timothy K","Harshbarger, Ian","Xia, Zixia","Levorato, Marco"],"url":"https://arxiv.org/abs/2406.13086","arxiv_id":"2406.13086","published":"2026-04-10"},{"title":"NaviSlim: Adaptive Context-Aware Navigation and Sensing via Dynamic Slimmable Networks","abstract":"Small-scale autonomous airborne vehicles, such as micro-drones, are expected to be a central component of a broad spectrum of applications ranging from exploration to surveillance and delivery. This class of vehicles is characterized by severe constraints in computing power and energy reservoir, which impairs their ability to support the complex state-of-the-art neural models needed for autonomous operations. The mai","authors":["Johnsen, Tim","Levorato, Marco"],"url":"https://arxiv.org/abs/2407.01563","arxiv_id":"2407.01563","published":"2026-04-10"},{"title":"BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning","abstract":"Federated learning, while being a promising approach for collaborative model training, is susceptible to backdoor attacks due to its decentralized nature. Backdoor attacks have shown remarkable stealthiness, as they compromise model predictions only when inputs contain specific triggers. As a countermeasure, anomaly detection is widely used to filter out backdoor attacks in FL. However, the non-independent and identi","authors":["Jiang, Zhengyuan","Lyu, Xingyu","Shi, Shanghao","Xiao, Yang","Chen, Yimin","Hou, Y. Thomas"],"url":"https://arxiv.org/abs/2407.09658","arxiv_id":"2407.09658","published":"2026-04-10"},{"title":"Causal Discovery in Linear Models with Unobserved Variables and Measurement Error","abstract":"The presence of unobserved common causes and measurement error poses two major obstacles to causal structure learning, since ignoring either source of complexity can induce spurious causal relations among variables of interest. We study causal structure learning in linear systems where both challenges may occur simultaneously. We introduce a causal model called LV-SEM-ME, which contains four types of variables: direc","authors":["Yang, Yuqin","Nafea, Mohamed","Kiyavash, Negar","Zhang, Kun","Ghassami, AmirEmad"],"url":"https://arxiv.org/abs/2407.19426","arxiv_id":"2407.19426","published":"2026-04-10"},{"title":"A systematic framework for generating novel experimental hypotheses from language models","abstract":"Neural language models (LMs) have been shown to capture complex linguistic patterns, yet their utility in understanding human language and more broadly, human cognition, remains debated. While existing work in this area often evaluates human-machine alignment, few studies attempt to translate findings from this enterprise into novel insights about humans. To this end, we propose a systematic framework for hypothesis ","authors":["Misra, Kanishka","Kim, Najoung"],"url":"https://arxiv.org/abs/2408.05086","arxiv_id":"2408.05086","published":"2026-04-10"},{"title":"Flemme: A Flexible and Modular Learning Platform for Medical Images","abstract":"As the rapid development of computer vision and the emergence of powerful network backbones and architectures, the application of deep learning in medical imaging has become increasingly significant. Unlike natural images, medical images lack huge volumes of data but feature more modalities, making it difficult to train a general model that has satisfactory performance across various datasets. In practice, practition","authors":["Zhang, Guoqing","Yang, Jingyun","Li, Yang"],"url":"https://arxiv.org/abs/2408.09369","arxiv_id":"2408.09369","published":"2026-04-10"},{"title":"Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models","abstract":"Background and Aims: This study evaluates the medical reasoning performance of large language models (LLMs) and vision language models (VLMs) in gastroenterology. Methods: We used 300 gastroenterology board exam-style multiple-choice questions, 138 of which contain images to systematically assess the impact of model configurations and parameters and prompt engineering strategies utilizing GPT-3.5. Next, we assessed t","authors":["Safavi-Naini, Seyed Amir Ahmad","Ali, Shuhaib","Shahab, Omer","Shahhoseini, Zahra","Savage, Thomas","Rafiee, Sara"],"url":"https://arxiv.org/abs/2409.00084","arxiv_id":"2409.00084","published":"2026-04-10"},{"title":"Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data","abstract":"This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimensional tabular data from 9,134 patients across four hospitals. Seven CML models, including XGBoost and random forest (RF), were evaluated alongside eight LLMs, such as GPT-4 and Mistral-7b, which performed zero-shot classification on text-conve","authors":["Ghaffarzadeh-Esfahani, Mohammadreza","Ghaffarzadeh-Esfahani, Mahdi","Salahi-Niri, Arian","Toreyhi, Hossein","Atf, Zahra","Mohsenzadeh-Kermani, Amirali"],"url":"https://arxiv.org/abs/2409.02136","arxiv_id":"2409.02136","published":"2026-04-10"},{"title":"LipKernel: Lipschitz-Bounded Convolutional Neural Networks via Dissipative Layers","abstract":"We propose a novel layer-wise parameterization for convolutional neural networks (CNNs) that includes built-in robustness guarantees by enforcing a prescribed Lipschitz bound. Each layer in our parameterization is designed to satisfy a linear matrix inequality (LMI), which in turn implies dissipativity with respect to a specific supply rate. Collectively, these layer-wise LMIs ensure Lipschitz boundedness for the inp","authors":["Pauli, Patricia","Wang, Ruigang","Manchester, Ian","Allgöwer, Frank"],"url":"https://arxiv.org/abs/2410.22258","arxiv_id":"2410.22258","published":"2026-04-10"}],"history":{"events":[{"year":2019,"text":"Scientists from the Event Horizon Telescope project released the first image of the black hole at the center of the galaxy M87.","url":"https://en.wikipedia.org/wiki/Event_Horizon_Telescope"},{"year":2009,"text":"Fijian President Ratu Josefa Iloilo announced that he had suspended the constitution and assumed all governance in the country after it was ruled that the government of Prime Minister Frank Bainimarama was illegal.","url":"https://en.wikipedia.org/wiki/Josefa_Iloilo"},{"year":1992,"text":"First Nagorno-Karabakh War: Dozens of Armenian civilians were massacred in the village of Maraga by Azerbaijani forces.","url":"https://en.wikipedia.org/wiki/First_Nagorno-Karabakh_War"},{"year":1973,"text":"In the deadliest aviation accident in Swiss history, Invicta International Airlines Flight 435 crashed into a hillside near Hochwald, killing 108 people of 145 on board.","url":"https://en.wikipedia.org/wiki/Invicta_International_Airlines_Flight_435"},{"year":1970,"text":"In the midst of business disagreements with his bandmates, Paul McCartney announced his departure from the Beatles.","url":"https://en.wikipedia.org/wiki/Paul_McCartney"},{"year":1963,"text":"The U.S. Navy nuclear submarine USS Thresher (SSN-593) sank with all hands lost during deep-diving tests in the North Atlantic Ocean.","url":"https://en.wikipedia.org/wiki/United_States_Navy"},{"year":1944,"text":"The Holocaust: Slovak Jewish prisoners Rudolf Vrba and Alfréd Wetzler escaped from Auschwitz, later publishing a report that became one of the earliest and most detailed descriptions of the camp's mass killings.","url":"https://en.wikipedia.org/wiki/The_Holocaust"},{"year":1925,"text":"The Great Gatsby (cover pictured), a novel by American author F. Scott Fitzgerald, was first published by Scribner's.","url":"https://en.wikipedia.org/wiki/The_Great_Gatsby"},{"year":1919,"text":"Mexican Revolution leader Emiliano Zapata was shot to death near Ciudad Ayala, Morelos.","url":"https://en.wikipedia.org/wiki/Mexican_Revolution"},{"year":1866,"text":"The American Society for the Prevention of Cruelty to Animals was founded in New York City by Henry Bergh.","url":"https://en.wikipedia.org/wiki/American_Society_for_the_Prevention_of_Cruelty_to_Animals"},{"year":1858,"text":"Big Ben, the bell in the Palace of Westminster's clock tower in London, was cast after the original bell cracked during testing.","url":"https://en.wikipedia.org/wiki/Big_Ben"},{"year":1815,"text":"Mount Tambora (pictured) in Indonesia began the most powerful volcanic eruption in recorded history, killing at least 71,000 people and affecting temperatures worldwide.","url":"https://en.wikipedia.org/wiki/Mount_Tambora"},{"year":1809,"text":"Napoleonic Wars: The War of the Fifth Coalition began with the Austrian invasion of Bavaria, then a client state of France.","url":"https://en.wikipedia.org/wiki/Napoleonic_Wars"},{"year":1741,"text":"War of the Austrian Succession: Prussian forces defeated Austrian troops at the Battle of Mollwitz in present-day Małujowice, Poland, cementing Frederick II's authority over the newly conquered territory of Silesia.","url":"https://en.wikipedia.org/wiki/War_of_the_Austrian_Succession"},{"year":1724,"text":"Bach led the first performance of his cantata Erfreut euch, ihr Herzen, his first cantata composed for Easter in Leipzig.","url":"https://en.wikipedia.org/wiki/Johann_Sebastian_Bach"},{"year":847,"text":"Pope Leo IV was consecrated without imperial consent following the Saracen sack of Rome.","url":"https://en.wikipedia.org/wiki/Pope_Leo_IV"}],"births":[{"year":2004,"text":"Ismaël Gharbi, French-Spanish footballer","url":"https://en.wikipedia.org/wiki/Isma%C3%ABl_Gharbi"},{"year":2004,"text":"Savinho, Brazilian footballer","url":"https://en.wikipedia.org/wiki/Savinho"},{"year":2000,"text":"Fidias Panayiotou, Cypriot internet celebrity and politician","url":"https://en.wikipedia.org/wiki/Fidias_Panayiotou"},{"year":1997,"text":"Claire Wineland, American activist and author (died 2018)","url":"https://en.wikipedia.org/wiki/Claire_Wineland"},{"year":1996,"text":"Andreas Christensen, Danish footballer","url":"https://en.wikipedia.org/wiki/Andreas_Christensen"},{"year":1994,"text":"Siobhan Hunter, Scottish footballer","url":"https://en.wikipedia.org/wiki/Siobhan_Hunter"},{"year":1992,"text":"Jack Buchanan, Australian rugby league player","url":"https://en.wikipedia.org/wiki/Jack_Buchanan_(rugby_league)"},{"year":1992,"text":"Chaz Mostert, Australian racing driver","url":"https://en.wikipedia.org/wiki/Chaz_Mostert"}],"deaths":[{"year":2026,"text":"Eliot Engel, American politician (born 1947)","url":"https://en.wikipedia.org/wiki/Eliot_Engel"},{"year":2026,"text":"Anja Hatakka, Finnish actress and beauty pageant competitor (born 1938)","url":"https://en.wikipedia.org/wiki/Anja_Hatakka"},{"year":2026,"text":"Sid Krofft, Canadian-American puppeteer and producer (born 1929)","url":"https://en.wikipedia.org/wiki/Sid_and_Marty_Krofft"},{"year":2026,"text":"Browning Nagle, American football player (born 1968)","url":"https://en.wikipedia.org/wiki/Browning_Nagle"},{"year":2025,"text":"Leo Beenhakker, Dutch football manager (born 1942)","url":"https://en.wikipedia.org/wiki/Leo_Beenhakker"},{"year":2025,"text":"Ted Kotcheff, Canadian film and television director (born 1931)","url":"https://en.wikipedia.org/wiki/Ted_Kotcheff"},{"year":2025,"text":"Peter Lovesey, British writer (born 1936)","url":"https://en.wikipedia.org/wiki/Peter_Lovesey"},{"year":2024,"text":"O. J. Simpson, American football player, actor, and broadcaster (born 1947)","url":"https://en.wikipedia.org/wiki/O._J._Simpson"}]},"census":null,"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."}