{"date":"2026-06-26","schema_version":1,"captured_at":"2026-08-25T23:13:46.174Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"2026 FIFA World Cup","views":1124230,"rank":2,"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. The tournament began on June 11, 2026, and concluded on July 19 with Spain winning ","url":"https://en.wikipedia.org/wiki/2026_FIFA_World_Cup","thumb":"https://upload.wikimedia.org/wikipedia/en/thumb/1/17/2026_FIFA_World_Cup_emblem.svg/330px-2026_FIFA_World_Cup_emblem.svg.png?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Sebastián Beccacece","views":333599,"rank":5,"extract":"Sebastián Andrés Beccacece is an Argentine professional football manager. 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It is located at the junction of Kentucky Route 206 and Kentucky Route 76. Its elevation is 705 feet (215 m). For unknown reasons, the town's name was spelled as Neetsvil","url":"https://en.wikipedia.org/wiki/Neatsville%2C_Kentucky","thumb":null},{"title":"Michael Jackson","views":78622,"rank":31,"extract":"Michael Joseph Jackson was an American singer, songwriter, dancer, and philanthropist. Dubbed the \"King of Pop\", he is widely regarded as one of the most culturally significant figures of the 20th century. 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(2011)","points":381,"comments":215,"url":"https://physics.stackexchange.com/questions/535/why-does-kinetic-energy-increase-quadratically-not-linearly-with-speed","discussion":"https://news.ycombinator.com/item?id=48692946"},{"title":"What happened after 2k people tried to hack my AI assistant","points":375,"comments":160,"url":"https://www.fernandoi.cl/posts/hackmyclaw/","discussion":"https://news.ycombinator.com/item?id=48681687"},{"title":"PlayStation Is Deleting 551 Movies from Customers' Accounts","points":359,"comments":224,"url":"https://kotaku.com/playstation-store-movies-digital-studio-canal-terminator-2000711013","discussion":"https://news.ycombinator.com/item?id=48691346"},{"title":"Framework's 10G Ethernet module exposes USB-C's complexity","points":325,"comments":183,"url":"https://www.jeffgeerling.com/blog/2026/framework-10g-ethernet-module-usb-c-complexity/","discussion":"https://news.ycombinator.com/item?id=48681220"},{"title":"Ultrasound imaging of the brain","points":324,"comments":126,"url":"https://alephneuro.com/blog/ultrasound-brain","discussion":"https://news.ycombinator.com/item?id=48685558"},{"title":"Jolla Phone (October 2026)","points":309,"comments":191,"url":"https://commerce.jolla.com/products/jolla-phone-october-2026","discussion":"https://news.ycombinator.com/item?id=48687272"},{"title":"The gap between open weights LLMs and closed source LLMs","points":306,"comments":250,"url":"https://blog.doubleword.ai/frontier-os-llm","discussion":"https://news.ycombinator.com/item?id=48692058"},{"title":"Libre Barcode Project","points":288,"comments":65,"url":"https://graphicore.github.io/librebarcode/","discussion":"https://news.ycombinator.com/item?id=48681949"},{"title":"AI children's books, body horror edition","points":217,"comments":77,"url":"https://lcamtuf.substack.com/p/ai-childrens-books-body-horror-edition","discussion":"https://news.ycombinator.com/item?id=48681250"},{"title":"Show HN: Smart model routing directly in Claude, Codex and Cursor","points":216,"comments":113,"url":"https://github.com/workweave/router","discussion":"https://news.ycombinator.com/item?id=48688700"},{"title":"AI in mathematics is forcing big questions","points":210,"comments":181,"url":"https://spectrum.ieee.org/ai-in-mathematics","discussion":"https://news.ycombinator.com/item?id=48692883"},{"title":"Data centers trigger voter backlash","points":202,"comments":393,"url":"https://www.newsweek.com/cost-me-the-election-data-centers-trigger-voter-backlash-12118327","discussion":"https://news.ycombinator.com/item?id=48689275"},{"title":"Quake in 13 Kilobytes (2021)","points":172,"comments":23,"url":"https://js13kgames.com/games/q1k3","discussion":"https://news.ycombinator.com/item?id=48693428"},{"title":"1.38 Millimeter Microcontroller","points":168,"comments":104,"url":"https://www.ti.com/product/MSPM0C1104","discussion":"https://news.ycombinator.com/item?id=48688685"},{"title":"How to corrupt an SQLite database file","points":160,"comments":40,"url":"https://www.sqlite.org/howtocorrupt.html","discussion":"https://news.ycombinator.com/item?id=48689885"},{"title":"Wallace the 6 inch f/2.8 telescope, building it, and hiking with it","points":153,"comments":33,"url":"https://lucassifoni.info/blog/hiking-with-wallace/","discussion":"https://news.ycombinator.com/item?id=48683475"}],"research":[{"title":"Theory of the Frequency Principle for General Deep Neural Networks","abstract":"Along with fruitful applications of Deep Neural Networks (DNNs) to realistic problems, recently, some empirical studies of DNNs reported a universal phenomenon of Frequency Principle (F-Principle): a DNN tends to learn a target function from low to high frequencies during the training. The F-Principle has been very useful in providing both qualitative and quantitative understandings of DNNs. In this paper, we rigorou","authors":["Luo, Tao","Ma, Zheng","Xu, Zhi-Qin John","Zhang, Yaoyu"],"url":"https://arxiv.org/abs/1906.09235","arxiv_id":"1906.09235","published":"2026-06-26"},{"title":"Learning from a Biased Sample","abstract":"The empirical risk minimization approach to data-driven decision making requires access to training data drawn under the same conditions as those that will be faced when the decision rule is deployed. However, in a number of settings, we may be concerned that our training sample is biased in the sense that some groups (characterized by either observable or unobservable attributes) may be under- or over-represented re","authors":["Sahoo, Roshni","Lei, Lihua","Wager, Stefan"],"url":"https://arxiv.org/abs/2209.01754","arxiv_id":"2209.01754","published":"2026-06-26"},{"title":"NervePool: A Simplicial Pooling Layer","abstract":"For deep learning problems on graph-structured data, pooling layers are important for down sampling, reducing computational cost, and to minimize overfitting. We define a pooling layer, nervePool, for data structured as simplicial complexes, which are generalizations of graphs that include higher-dimensional simplices beyond vertices and edges; this structure allows for greater flexibility in modeling higher-order re","authors":["Scullen, Sarah McGuire","Röell, Ernst","Munch, Elizabeth","Rieck, Bastian","Hirn, Matthew"],"url":"https://arxiv.org/abs/2305.06315","arxiv_id":"2305.06315","published":"2026-06-26"},{"title":"Understanding the Initial Condensation of Convolutional Neural Networks","abstract":"Previous research has shown that fully-connected networks with small initialization and gradient-based training methods exhibit a phenomenon known as condensation during training. This phenomenon refers to the input weights of hidden neurons condensing into isolated orientations during training, revealing an implicit bias towards simple solutions in the parameter space. However, the impact of neural network structure","authors":["Zhou, Zhangchen","Zhou, Hanxu","Li, Yuqing","Xu, Zhi-Qin John"],"url":"https://arxiv.org/abs/2305.09947","arxiv_id":"2305.09947","published":"2026-06-26"},{"title":"Consistent Distributed Ranking of Generative Models via Kernel Distances","abstract":"Ranking generative models based on the fidelity and diversity of their outputs is required to identify the best generator in a group of candidate generative AI models. To rank a group of models in a conventional centralized setting, a standard score is commonly evaluated for each involved model. The selection and design of reference-based evaluation scores have been extensively studied in centralized settings, where ","authors":["Wang, Zixiao","Farnia, Farzan","Lin, Zhenghao","Shen, Yunheng","Yu, Bei"],"url":"https://arxiv.org/abs/2310.11714","arxiv_id":"2310.11714","published":"2026-06-26"},{"title":"Techniques for supercharging academic writing with generative AI","abstract":"Academic writing is an indispensable yet laborious part of the research enterprise. This Perspective maps out principles and methods for using generative artificial intelligence (AI), specifically large language models (LLMs), to elevate the quality and efficiency of academic writing. We introduce a human-AI collaborative framework that delineates the rationale (why), process (how), and nature (what) of AI engagement","authors":["Lin, Zhicheng"],"url":"https://arxiv.org/abs/2310.17143","arxiv_id":"2310.17143","published":"2026-06-26"},{"title":"Gradient Testing and Estimation by Comparisons","abstract":"We study gradient testing and gradient estimation of smooth functions using only a comparison oracle that, given two points, indicates which one has the larger function value. For any smooth $f\\colon\\mathbb R^n\\to\\mathbb R$, $\\mathbf{x}\\in\\mathbb R^n$, and $\\varepsilon>0$, we design a gradient testing algorithm that determines whether the normalized gradient $\\nabla f(\\mathbf{x})/\\|\\nabla f(\\mathbf{x})\\|$ is $\\var","authors":["Tao, Xiwen","Zhang, Chenyi","Wang, Helin","Zhang, Yexin","Li, Tongyang"],"url":"https://arxiv.org/abs/2405.11454","arxiv_id":"2405.11454","published":"2026-06-26"},{"title":"Wearable Device-Based Real-Time Monitoring of Physiological Signals: Evaluating Cognitive Load Across Different Tasks","abstract":"This study employs cutting-edge wearable monitoring technology to conduct high-precision, high-temporal-resolution (1-second interval) cognitive load assessment on electroencephalogram (EEG) data from the FP1 channel and heart rate variability (HRV) data of secondary vocational students. By jointly analyzing these two critical physiological indicators, the research delves into their application value in assessing cog","authors":["He, Ling","Chen, Yanxin","Wang, Wenqi","He, Shuting","Hu, Xiaoqiang"],"url":"https://arxiv.org/abs/2406.07147","arxiv_id":"2406.07147","published":"2026-06-26"},{"title":"Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis","abstract":"Thanks to their extensive capacity, over-parameterized neural networks exhibit superior predictive capabilities and generalization. However, having a large parameter space is considered one of the main suspects of the neural networks' vulnerability to adversarial example -- input samples crafted ad-hoc to induce a desired misclassification. Relevant literature has claimed contradictory remarks in support of and a","authors":["Gupta, Srishti","Chen, Zhang","Demetrio, Luca","Brau, Fabio","Feng, Xiaoyi","Xia, Zhaoqiang"],"url":"https://arxiv.org/abs/2406.10090","arxiv_id":"2406.10090","published":"2026-06-26"},{"title":"Decentralized Best-Response-Based Learning in Two-Player Zero-Sum Stochastic Games: A Finite-Sample Analysis","abstract":"We present a finite-sample analysis of decentralized learning in two-player zero-sum matrix games and stochastic games, with a focus on best-response-based learning algorithms. In matrix games, the learning algorithm is payoff-based and symmetric: each player updates its policy using only its own payoff observations, incrementally moving toward an estimated smoothed best response to the opponent's latest policy. ","authors":["Chen, Zaiwei","Zhang, Kaiqing","Mazumdar, Eric","Ozdaglar, Asuman","Wierman, Adam"],"url":"https://arxiv.org/abs/2409.01447","arxiv_id":"2409.01447","published":"2026-06-26"},{"title":"HELIOT: LLM-Based CDSS for Adverse Drug Reaction Management","abstract":"Medication errors significantly threaten patient safety, leading to adverse drug events and substantial economic burdens on healthcare systems. Clinical Decision Support Systems (CDSSs) aimed at mitigating these errors often face limitations when processing unstructured clinical data, including reliance on static databases and rule-based algorithms, frequently generating excessive alerts that lead to alert fatigue am","authors":["De Vito, Gabriele","Ferrucci, Filomena","Angelakis, Athanasios"],"url":"https://arxiv.org/abs/2409.16395","arxiv_id":"2409.16395","published":"2026-06-26"},{"title":"Byzantine-Robust Aggregation for Securing Decentralized Federated Learning","abstract":"Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) extends the FL paradigm by eliminating the central server, thereby enhancing scalability and robustness through the avoidance of a single point of failure. However, DFL faces significant challenges in optimizing security, as most By","authors":["Cajaraville-Aboy, Diego","Fernández-Vilas, Ana","Díaz-Redondo, Rebeca P.","Fernández-Veiga, Manuel"],"url":"https://arxiv.org/abs/2409.17754","arxiv_id":"2409.17754","published":"2026-06-26"},{"title":"Adversarial Robustness of AI-Generated Image Detectors in the Real World","abstract":"The rapid advancement of Generative Artificial Intelligence (GenAI) capabilities is accompanied by a concerning rise in its misuse. In particular the generation of credible misinformation in the form of images poses a significant threat to the public trust in democratic processes. Consequently, there is an urgent need to develop tools to reliably distinguish between authentic and AI-generated content. The majority of","authors":["Mavali, Sina","Ricker, Jonas","Pape, David","Fischer, Asja","Schönherr, Lea"],"url":"https://arxiv.org/abs/2410.01574","arxiv_id":"2410.01574","published":"2026-06-26"},{"title":"Tuning Language Models by Mixture-of-Depths Ensemble","abstract":"Transformer-based Large Language Models (LLMs) traditionally rely on final-layer loss for finetuning and final-layer representations for predictions, potentially overlooking the predictive power embedded in late layers. Interpretability tools such as the logit lens show that late-layer representations already carry largely formed, task-relevant predictions; here we ask whether that observation can be turned into an a","authors":["Luo, Haoyan","Specia, Lucia"],"url":"https://arxiv.org/abs/2410.13077","arxiv_id":"2410.13077","published":"2026-06-26"},{"title":"DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning","abstract":"In reinforcement learning (RL), temporal difference (TD) error is known to be related to the firing rate of dopamine neurons. It has been observed that each dopamine neuron does not behave uniformly, but each responds to the TD error in an optimistic or pessimistic manner, interpreted as a kind of distributional RL. To explain such a biological data, a heuristic model has also been introduced with learning rates asym","authors":["Kobayashi, Taisuke"],"url":"https://arxiv.org/abs/2410.17473","arxiv_id":"2410.17473","published":"2026-06-26"},{"title":"Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection","abstract":"Dataset distillation provides an effective approach to reduce memory and computational costs by optimizing a compact dataset that achieves performance comparable to the full original. However, for large-scale datasets and complex deep networks (e.g., ImageNet-1K with ResNet-101), the vast optimization space hinders distillation effectiveness, limiting practical applications. Recent methods leverage pre-trained diffus","authors":["Zhong, Xinhao","Sun, Shuoyang","Xu, Zhaoyang","Gu, Xulin","Chen, Bin","Zhang, Min"],"url":"https://arxiv.org/abs/2412.09959","arxiv_id":"2412.09959","published":"2026-06-26"},{"title":"Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization","abstract":"Distributed-memory implementations of numerical optimization algorithm, such as stochastic gradient descent (SGD), require interprocessor communication at every iteration of the algorithm. On modern distributed-memory clusters where communication is more expensive than computation, the scalability and performance of these algorithms are limited by communication cost. This work generalizes prior work on 1D $s$-step SG","authors":["Devarakonda, Aditya","Kannan, Ramakrishnan"],"url":"https://arxiv.org/abs/2501.07526","arxiv_id":"2501.07526","published":"2026-06-26"},{"title":"Guided Persona-based AI Surveys: Can we replicate personal mobility preferences at scale using LLMs?","abstract":"This study explores the potential of Large Language Models (LLMs) to generate artificial surveys, with a focus on personal mobility preferences in Germany. By leveraging LLMs for synthetic data creation, we aim to address the limitations of traditional survey methods, such as high costs, inefficiency and scalability challenges. A novel approach incorporating "Personas" - combinations of demographic and behavi","authors":["Tzachristas, Ioannis","Narayanan, Santhanakrishnan","Antoniou, Constantinos"],"url":"https://arxiv.org/abs/2501.13955","arxiv_id":"2501.13955","published":"2026-06-26"},{"title":"LLMs for Drug-Drug Interaction Prediction: A Comprehensive Comparison","abstract":"The increasing volume of drug combinations in modern therapeutic regimens needs reliable methods for predicting drug-drug interactions (DDIs). While Large Language Models (LLMs) have revolutionized various domains, their potential in pharmaceutical research, particularly in DDI prediction, remains largely unexplored. This study thoroughly investigates LLMs' capabilities in predicting DDIs by uniquely processing m","authors":["De Vito, Gabriele","Ferrucci, Filomena","Angelakis, Athanasios"],"url":"https://arxiv.org/abs/2502.06890","arxiv_id":"2502.06890","published":"2026-06-26"},{"title":"A Systematic Survey of Semantic Role Labeling in the Era of Pretrained Language Models","abstract":"Semantic role labeling (SRL) is a central natural language processing task for understanding predicate-argument structures within texts and enabling downstream applications. Despite extensive research, comprehensive surveys that critically synthesize the field from a unified perspective remain lacking. This survey makes several contributions beyond organizing existing work. We propose a unified four-dimensional taxon","authors":["Chen, Huiyao","Zhang, Meishan","Li, Jing","Øvrelid, Lilja","Hajič, Jan","Fei, Hao"],"url":"https://arxiv.org/abs/2502.08660","arxiv_id":"2502.08660","published":"2026-06-26"},{"title":"Learning to Explain Air Traffic Situation","abstract":"Understanding how air traffic controllers construct a mental 'picture' of complex air traffic situations is crucial but remains a challenge due to the inherently intricate, high-dimensional interactions between aircraft, pilots, and controllers. Previous work on modeling the strategies of air traffic controllers and their mental image of traffic situations often centers on specific air traffic control tasks o","authors":["Chai, Hong-ah","Yoon, Seokbin","Lee, Keumjin"],"url":"https://arxiv.org/abs/2502.10764","arxiv_id":"2502.10764","published":"2026-06-26"},{"title":"Bayesian Optimization for General Reaction Conditions","abstract":"General chemical reaction conditions that achieve consistently high performance across multiple substrates are important for practical applications such as library synthesis and high-throughput experimentation. However, identifying such conditions efficiently has been a longstanding challenge, as it requires decision making under uncertainty with respect to both conditions and substrates, while minimizing the number ","authors":["Schmid, Stefan P.","Rajaonson, Ella Miray","Ser, Cher Tian","Haddadnia, Mohammad","Leong, Shi Xuan","Aspuru-Guzik, Alán"],"url":"https://arxiv.org/abs/2502.18966","arxiv_id":"2502.18966","published":"2026-06-26"},{"title":"TF-TI2I: Training-Free Text-and-Image-to-Image Generation via Multi-Modal Implicit-Context Learning in Text-to-Image Models","abstract":"Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like objects or styles, or they experience a decline in generation quality with complex, multi-image instructions. To overcome these challenges, we introduce Training-Free Text-and-Image-","authors":["Hsiao, Teng-Fang","Ruan, Bo-Kai","Wu, Yi-Lun","Lin, Tzu-Ling","Shuai, Hong-Han"],"url":"https://arxiv.org/abs/2503.15283","arxiv_id":"2503.15283","published":"2026-06-26"},{"title":"Circular Quasiconformal Deturbulence: Geometry-Based Restoration from Multiple Turbulent Frames","abstract":"Imaging through inhomogeneous media often results in severe distortions, posing significant challenges to downstream image-processing tasks. The lack of clean paired images makes supervised learning impractical, motivating unsupervised restoration approaches. In this work, we propose the Circular Quasi-Conformal Deturbulence (CQCD) framework, an unsupervised approach that reconstructs distortion-free images from mult","authors":["Chen, Chu","Zhang, Han","Lui, Lok Ming"],"url":"https://arxiv.org/abs/2504.13432","arxiv_id":"2504.13432","published":"2026-06-26"},{"title":"Chisme: Heterogeneity-Aware Gossip Learning","abstract":"As end-user device capability increases and demand for intelligent services at the Internet's edge rises, distributed learning has emerged as a key enabling technology for the intelligent edge. Existing approaches like federated learning (FL) and decentralized FL (DFL) enable privacy-preserving distributed learning among clients, while gossip learning (GL) approaches have emerged to address the potential challeng","authors":["Kuttivelil, Harikrishna","Obraczka, Katia"],"url":"https://arxiv.org/abs/2505.09854","arxiv_id":"2505.09854","published":"2026-06-26"}],"history":{"events":[{"year":2015,"text":"The U.S. Supreme Court ruled in Obergefell v. Hodges that the right of same-sex couples to marry is guaranteed by the Fourteenth Amendment.","url":"https://en.wikipedia.org/wiki/Supreme_Court_of_the_United_States"},{"year":2013,"text":"The U.S. Supreme Court granted federal recognition to same-sex marriage when it overturned the Defense of Marriage Act.","url":"https://en.wikipedia.org/wiki/Supreme_Court_of_the_United_States"},{"year":2010,"text":"A G20 summit, the largest and most expensive security operation in Canadian history, began in downtown Toronto.","url":"https://en.wikipedia.org/wiki/2010_G20_Toronto_summit"},{"year":2003,"text":"The U.S. Supreme Court struck down sodomy laws in the country in the landmark decision Lawrence v. Texas.","url":"https://en.wikipedia.org/wiki/Supreme_Court_of_the_United_States"},{"year":1997,"text":"J. K. Rowling's Harry Potter and the Philosopher's Stone, the first book in the Harry Potter fantasy novel series, was released.","url":"https://en.wikipedia.org/wiki/J._K._Rowling"},{"year":1950,"text":"A Douglas DC-4 Skymaster aircraft crashed after departing from Perth, becoming the worst peacetime aviation accident in Australia's history.","url":"https://en.wikipedia.org/wiki/Douglas_DC-4"},{"year":1945,"text":"At a conference in San Francisco, delegates from 50 nations signed a charter establishing the United Nations.","url":"https://en.wikipedia.org/wiki/United_Nations_Conference_on_International_Organization"},{"year":1918,"text":"World War I: The 26-day Battle of Belleau Wood near the Marne River in France ended with American forces finally clearing that forest of German troops.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1907,"text":"Organized by Vladimir Lenin and Joseph Stalin, among others, Bolshevik revolutionaries robbed a bank stagecoach in Tiflis, present-day Georgia.","url":"https://en.wikipedia.org/wiki/Vladimir_Lenin"},{"year":1906,"text":"The 1906 French Grand Prix, the first Grand Prix motor racing competition, began near Le Mans.","url":"https://en.wikipedia.org/wiki/1906_French_Grand_Prix"},{"year":1889,"text":"Bangui, the capital and largest city of the present-day Central African Republic, was founded in French Congo.","url":"https://en.wikipedia.org/wiki/Bangui"},{"year":1886,"text":"French chemist Henri Moissan successfully isolated elemental fluorine (pictured in liquid state), for which he later won the Nobel Prize in Chemistry.","url":"https://en.wikipedia.org/wiki/Henri_Moissan"},{"year":1848,"text":"French authorities suppressed the June Days uprising (pictured), in which workers rioted in response to plans to close the National Workshops.","url":"https://en.wikipedia.org/wiki/June_Days_uprising"},{"year":1844,"text":"Julia Gardiner (pictured) married U.S. President John Tyler at the Church of the Ascension in New York, becoming the first lady.","url":"https://en.wikipedia.org/wiki/Julia_Gardiner_Tyler"},{"year":1409,"text":"The Council of Pisa elected Peter of Candia as Alexander V, becoming the third simultaneous claimant of the papacy during the Western Schism.","url":"https://en.wikipedia.org/wiki/Council_of_Pisa"},{"year":1243,"text":"Mongol conquest of Anatolia: Mongols achieved a decisive victory over the Seljuk Turks, leading to the decline and disintegration of the Seljuk state.","url":"https://en.wikipedia.org/wiki/Mongol_conquest_of_Anatolia"}],"births":[{"year":2005,"text":"Princess Alexia of the Netherlands","url":"https://en.wikipedia.org/wiki/Princess_Alexia_of_the_Netherlands"},{"year":2004,"text":"Mikey Williams, American basketball player","url":"https://en.wikipedia.org/wiki/Mikey_Williams_(basketball%2C_born_2004)"},{"year":2002,"text":"Chandler Smith, American race car driver","url":"https://en.wikipedia.org/wiki/Chandler_Smith"},{"year":2002,"text":"Manon Bannerman, Swiss singer and dancer","url":"https://en.wikipedia.org/wiki/Manon_Bannerman"},{"year":2000,"text":"Ann Li, American tennis player","url":"https://en.wikipedia.org/wiki/Ann_Li_(tennis)"},{"year":1999,"text":"Connor Dewar, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Connor_Dewar"},{"year":1997,"text":"Baek Ye-rin, South Korean singer","url":"https://en.wikipedia.org/wiki/Yerin_Baek"},{"year":1997,"text":"Jacob Elordi, Australian actor","url":"https://en.wikipedia.org/wiki/Jacob_Elordi"}],"deaths":[{"year":2026,"text":"Joe Doering, American professional wrestler (born 1982)","url":"https://en.wikipedia.org/wiki/Joe_Doering"},{"year":2025,"text":"Carolyn McCarthy, American nurse and politician (born 1944)","url":"https://en.wikipedia.org/wiki/Carolyn_McCarthy"},{"year":2025,"text":"Bill Moyers, American journalist, 13th White House Press Secretary (born 1934)","url":"https://en.wikipedia.org/wiki/Bill_Moyers"},{"year":2025,"text":"Lalo Schifrin, Argentinian pianist, composer, and conductor (born 1932)","url":"https://en.wikipedia.org/wiki/Lalo_Schifrin"},{"year":2025,"text":"Takutai Tarsh Kemp, New Zealand politician (born 1975)","url":"https://en.wikipedia.org/wiki/Takutai_Tarsh_Kemp"},{"year":2024,"text":"Taiki Matsuno, Japanese voice actor (born 1967)","url":"https://en.wikipedia.org/wiki/Taiki_Matsuno"},{"year":2022,"text":"Margaret Keane, American artist (born 1927)","url":"https://en.wikipedia.org/wiki/Margaret_Keane"},{"year":2021,"text":"Mike Gravel, American politician (born 1930)","url":"https://en.wikipedia.org/wiki/Mike_Gravel"}]},"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."}