{"date":"2026-02-04","schema_version":1,"captured_at":"2026-08-25T23:26:57.848Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Jeffrey Epstein","views":1030479,"rank":2,"extract":"Jeffrey Edward Epstein was an American financier and child sex offender. He began his career as a math teacher at the Dalton School in New York City, before entering the banking and finance sector. 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In 2021, she was convicted of child sex trafficking, and in 2022 was sentenced to 20 years in prison.","url":"https://en.wikipedia.org/wiki/Ghislaine_Maxwell","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/8/8c/Ghislaine_Maxwell_MDC_mug_shot.webp/330px-Ghislaine_Maxwell_MDC_mug_shot.webp.png?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Peter Mandelson","views":202419,"rank":10,"extract":"Peter Benjamin Mandelson, Baron Mandelson, is a British former Labour Party politician, lobbyist and diplomat. He was the Member of Parliament (MP) for Hartlepool from 1992 to 2004. 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I wrote a book about it","points":208,"comments":68,"url":"https://derekyan.com/ma-book/","discussion":"https://news.ycombinator.com/item?id=46888258"},{"title":"Building a 24-bit arcade CRT display adapter from scratch","points":205,"comments":64,"url":"https://www.scd31.com/posts/building-an-arcade-display-adapter","discussion":"https://news.ycombinator.com/item?id=46888795"},{"title":"Spotlighting the World Factbook as We Bid a Fond Farewell","points":184,"comments":153,"url":"https://www.cia.gov/stories/story/spotlighting-the-world-factbook-as-we-bid-a-fond-farewell/","discussion":"https://news.ycombinator.com/item?id=46891794"},{"title":"Attention at Constant Cost per Token via Symmetry-Aware Taylor Approximation","points":164,"comments":96,"url":"https://arxiv.org/abs/2602.00294","discussion":"https://news.ycombinator.com/item?id=46886265"},{"title":"Steve Bannon Proposes Using ICE in Elections","points":140,"comments":94,"url":"https://www.newsweek.com/steve-bannon-proposes-using-ice-in-elections-11462376","discussion":"https://news.ycombinator.com/item?id=46888824"},{"title":"Illinois joins WHO global outbreak network after U.S. withdraws","points":137,"comments":52,"url":"https://capitolnewsillinois.com/news/illinois-joins-who-global-outbreak-network-after-u-s-withdraws/","discussion":"https://news.ycombinator.com/item?id=46879447"},{"title":"Rabbit Ear \"Origami\": programmable origami in the browser","points":134,"comments":5,"url":"https://rabbitear.org/book/origami.html","discussion":"https://news.ycombinator.com/item?id=46886569"},{"title":"The F Word","points":132,"comments":66,"url":"http://muratbuffalo.blogspot.com/2026/02/friction.html","discussion":"https://news.ycombinator.com/item?id=46887084"}],"research":[{"title":"On the Convergence of Experience Replay in Policy Optimization: Characterizing Bias, Variance, and Finite-Time Convergence","abstract":"Experience replay is a core ingredient of modern deep reinforcement learning, yet its benefits in policy optimization are poorly understood beyond empirical heuristics. This paper develops a novel theoretical framework for experience replay in modern policy gradient methods, where two sources of dependence fundamentally complicate analysis: Markovian correlations along trajectories and policy drift across optimizatio","authors":["Zheng, Hua","Xie, Wei","Feng, M. Ben"],"url":"https://arxiv.org/abs/2110.08902","arxiv_id":"2110.08902","published":"2026-02-04"},{"title":"OMSN and FAROS: OCTA Microstructure Segmentation Network and Fully Annotated Retinal OCTA Segmentation Dataset","abstract":"The lack of efficient segmentation methods and fully-labeled datasets limits the comprehensive assessment of optical coherence tomography angiography (OCTA) microstructures like retinal vessel network (RVN) and foveal avascular zone (FAZ), which are of great value in ophthalmic and systematic diseases evaluation. Here, we introduce an innovative OCTA microstructure segmentation network (OMSN) by combining an encoder-","authors":["Xiao, Peng","Hu, Xiaodong","Ma, Ke","Wang, Gengyuan","Feng, Ziqing","Huang, Yuancong"],"url":"https://arxiv.org/abs/2212.13059","arxiv_id":"2212.13059","published":"2026-02-04"},{"title":"Discrete Latent Structure in Neural Networks","abstract":"Many types of data from fields including natural language processing, computer vision, and bioinformatics, are well represented by discrete, compositional structures such as trees, sequences, or matchings. Latent structure models are a powerful tool for learning to extract such representations, offering a way to incorporate structural bias, discover insight about the data, and interpret decisions. However, effective ","authors":["Niculae, Vlad","Corro, Caio F.","Nangia, Nikita","Mihaylova, Tsvetomila","Martins, André F. T."],"url":"https://arxiv.org/abs/2301.07473","arxiv_id":"2301.07473","published":"2026-02-04"},{"title":"Contextual Causal Bayesian Optimisation","abstract":"We introduce a unified framework for contextual and causal Bayesian optimisation, which aims to design intervention policies maximising the expectation of a target variable. Our approach leverages both observed contextual information and known causal graph structures to guide the search. Within this framework, we propose a novel algorithm that jointly optimises over policies and the sets of variables on which these p","authors":["Arsenyan, Vahan","Grosnit, Antoine","Bou-Ammar, Haitham","Dalalyan, Arnak"],"url":"https://arxiv.org/abs/2301.12412","arxiv_id":"2301.12412","published":"2026-02-04"},{"title":"Regulatory Markets: The Future of AI Governance","abstract":"Appropriately regulating artificial intelligence is an increasingly urgent and widespread policy challenge. We identify two primary, competing problem. First is a technical deficit: Legislatures and regulatory face significant challenges in rapidly translating conventional command-and-control legal requirements into technical requirements. Second is a democratic deficit: Over-reliance on industry to provide technical","authors":["Hadfield, Gillian K.","Clark, Jack"],"url":"https://arxiv.org/abs/2304.04914","arxiv_id":"2304.04914","published":"2026-02-04"},{"title":"AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation","abstract":"Attention is the core mechanism of today's most used architectures for natural language processing and has been analyzed from many perspectives, including its effectiveness for machine translation-related tasks. Among these studies, attention resulted to be a useful source of information to get insights about word alignment also when the input text is substituted with audio segments, as in the case of the speech ","authors":["Papi, Sara","Turchi, Marco","Negri, Matteo"],"url":"https://arxiv.org/abs/2305.11408","arxiv_id":"2305.11408","published":"2026-02-04"},{"title":"Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains","abstract":"The computational efficiency of many neural operators, widely used for learning solutions of PDEs, relies on the fast Fourier transform (FFT) for performing spectral computations. As the FFT is limited to equispaced (rectangular) grids, this limits the efficiency of such neural operators when applied to problems where the input and output functions need to be processed on general non-equispaced point distributions. L","authors":["Lingsch, Levi","Michelis, Mike Y.","de Bezenac, Emmanuel","Perera, Sirani M.","Katzschmann, Robert K.","Mishra, Siddhartha"],"url":"https://arxiv.org/abs/2305.19663","arxiv_id":"2305.19663","published":"2026-02-04"},{"title":"Quantum Architecture Search with Unsupervised Representation Learning","abstract":"Unsupervised representation learning presents new opportunities for advancing Quantum Architecture Search (QAS) on Noisy Intermediate-Scale Quantum (NISQ) devices. QAS is designed to optimize quantum circuits for Variational Quantum Algorithms (VQAs). Most QAS algorithms tightly couple the search space and search algorithm, typically requiring the evaluation of numerous quantum circuits, resulting in high computation","authors":["Sun, Yize","Wu, Zixin","Tresp, Volker","Ma, Yunpu"],"url":"https://arxiv.org/abs/2401.11576","arxiv_id":"2401.11576","published":"2026-02-04"},{"title":"Mapping the Unseen: Unified Promptable Panoptic Mapping with Dynamic Labeling using Foundation Models","abstract":"Panoptic maps enable robots to reason about both geometry and semantics. However, open-vocabulary models repeatedly produce closely related labels that split panoptic entities and degrade volumetric consistency. The proposed UPPM advances open-world scene understanding by leveraging foundation models to introduce a panoptic Dynamic Descriptor that reconciles open-vocabulary labels with unified category structure and ","authors":["Mdfaa, Mohamad Al","Salameh, Raghad","Kulathunga, Geesara","Zagoruyko, Sergey","Ferrer, Gonzalo"],"url":"https://arxiv.org/abs/2405.02162","arxiv_id":"2405.02162","published":"2026-02-04"},{"title":"HAAP: Vision-context Hierarchical Attention Autoregressive with Adaptive Permutation for Scene Text Recognition","abstract":"Scene Text Recognition (STR) is challenging in extracting effective character representations from visual data when text is unreadable. Permutation language modeling (PLM) is introduced to refine character predictions by jointly capturing contextual and visual information. However, in PLM, the use of random permutations causes training fit oscillation, and the iterative refinement (IR) operation also introduces addit","authors":["Chen, Honghui","Qiu, Yuhang","Wang, Jiabao","Chen, Pingping","Ling, Nam"],"url":"https://arxiv.org/abs/2405.09125","arxiv_id":"2405.09125","published":"2026-02-04"},{"title":"Sparse maximal update parameterization: A holistic approach to sparse training dynamics","abstract":"Several challenges make it difficult for sparse neural networks to compete with dense models. First, setting a large fraction of weights to zero impairs forward and gradient signal propagation. Second, sparse studies often need to test multiple sparsity levels, while also introducing new hyperparameters (HPs), leading to prohibitive tuning costs. Indeed, the standard practice is to re-use the learning HPs originally ","authors":["Dey, Nolan","Bergsma, Shane","Hestness, Joel"],"url":"https://arxiv.org/abs/2405.15743","arxiv_id":"2405.15743","published":"2026-02-04"},{"title":"ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning","abstract":"Multi-agent credit assignment is a fundamental challenge for cooperative multi-agent reinforcement learning (MARL), where a team of agents learn from shared reward signals. The Individual-Global-Max (IGM) condition is a widely used principle for multi-agent credit assignment, requiring that the joint action determined by individual Q-functions maximizes the global Q-value. Meanwhile, the principle of maximum entropy ","authors":["Chen, Wen-Tse","Li, Yuxuan","Huang, Shiyu","Chen, Jiayu","Schneider, Jeff"],"url":"https://arxiv.org/abs/2406.13930","arxiv_id":"2406.13930","published":"2026-02-04"},{"title":"How Intermodal Interaction Affects the Performance of Deep Multimodal Fusion for Mixed-Type Time Series","abstract":"Mixed-type time series (MTTS) is a bimodal data type that is common in many domains, such as healthcare, finance, environmental monitoring, and social media. It consists of regularly sampled continuous time series and irregularly sampled categorical event sequences. The integration of both modalities through multimodal fusion is a promising approach for processing MTTS. However, the question of how to effectively fus","authors":["Dietz, Simon","Altstidl, Thomas","Zanca, Dario","Eskofier, Björn","Nguyen, An"],"url":"https://arxiv.org/abs/2406.15098","arxiv_id":"2406.15098","published":"2026-02-04"},{"title":"A Syntax-Injected Approach for Faster and More Accurate Sentiment Analysis","abstract":"Sentiment Analysis (SA) is a crucial aspect of Natural Language Processing (NLP), focusing on identifying and interpreting subjective assessments in textual content. Syntactic parsing is useful in SA as it improves accuracy and provides explainability; however, it often becomes a computational bottleneck due to slow parsing algorithms. This article proposes a solution to this bottleneck by using a Sequence Labeling S","authors":["Imran, Muhammad","Kellert, Olga","Gómez-Rodríguez, Carlos"],"url":"https://arxiv.org/abs/2406.15163","arxiv_id":"2406.15163","published":"2026-02-04"},{"title":"Conformal Prediction for Causal Effects of Continuous Treatments","abstract":"Uncertainty quantification of causal effects is crucial for safety-critical applications such as personalized medicine. A powerful approach for this is conformal prediction, which has several practical benefits due to model-agnostic finite-sample guarantees. Yet, existing methods for conformal prediction of causal effects are limited to binary/discrete treatments and make highly restrictive assumptions such as known ","authors":["Schröder, Maresa","Frauen, Dennis","Schweisthal, Jonas","Heß, Konstantin","Melnychuk, Valentyn","Feuerriegel, Stefan"],"url":"https://arxiv.org/abs/2407.03094","arxiv_id":"2407.03094","published":"2026-02-04"},{"title":"Hyper-Compression: Model Compression via Hyperfunction","abstract":"The rapid growth of large models' size has far outpaced that of computing resources. To bridge this gap, encouraged by the parsimonious relationship between genotype and phenotype in the brain's growth and development, we propose the so-called Hyper-Compression that turns the model compression into the issue of parameter representation via a hyperfunction. Specifically, it is known that the trajectory of some","authors":["Fan, Fenglei","Fan, Juntong","Wang, Dayang","Zhang, Jingbo","Dong, Zelin","Zhang, Shijun"],"url":"https://arxiv.org/abs/2409.00592","arxiv_id":"2409.00592","published":"2026-02-04"},{"title":"Inferring Scientific Cross-Document Coreference and Hierarchy with Definition-Augmented Relational Reasoning","abstract":"We address the fundamental task of inferring cross-document coreference and hierarchy in scientific texts, which has important applications in knowledge graph construction, search, recommendation and discovery. Large Language Models (LLMs) can struggle when faced with many long-tail technical concepts with nuanced variations. We present a novel method which generates context-dependent definitions of concept mentions ","authors":["Forer, Lior","Hope, Tom"],"url":"https://arxiv.org/abs/2409.15113","arxiv_id":"2409.15113","published":"2026-02-04"},{"title":"Saliency-Guided DETR for Moment Retrieval and Highlight Detection","abstract":"Existing approaches for video moment retrieval and highlight detection are not able to align text and video features efficiently, resulting in unsatisfying performance and limited production usage. To address this, we propose a novel architecture that utilizes recent foundational video models designed for such alignment. Combined with the introduced Saliency-Guided Cross Attention mechanism and a hybrid DETR architec","authors":["Gordeev, Aleksandr","Dokholyan, Vladimir","Tolstykh, Irina","Kuprashevich, Maksim"],"url":"https://arxiv.org/abs/2410.01615","arxiv_id":"2410.01615","published":"2026-02-04"},{"title":"Fast Training of Sinusoidal Neural Fields via Scaling Initialization","abstract":"Neural fields are an emerging paradigm that represent data as continuous functions parameterized by neural networks. Despite many advantages, neural fields often have a high training cost, which prevents a broader adoption. In this paper, we focus on a popular family of neural fields, called sinusoidal neural fields (SNFs), and study how it should be initialized to maximize the training speed. We find that the standa","authors":["Yeom, Taesun","Lee, Sangyoon","Lee, Jaeho"],"url":"https://arxiv.org/abs/2410.04779","arxiv_id":"2410.04779","published":"2026-02-04"},{"title":"Individual Regret in Cooperative Stochastic Multi-Armed Bandits","abstract":"We study the regret in stochastic Multi-Armed Bandits (MAB) with multiple agents that communicate over an arbitrary connected communication graph. We analyzed a variant of Cooperative Successive Elimination algorithm, COOP-SE, and show an individual regret bound of $O(R/ m + A^2 + A \\sqrt{\\log T})$ and a nearly matching lower bound. Here $A$ is the number of actions, $T$ the time horizon, $m$ the number of agents, an","authors":["Barnea, Idan","Lancewicki, Tal","Mansour, Yishay"],"url":"https://arxiv.org/abs/2411.06501","arxiv_id":"2411.06501","published":"2026-02-04"},{"title":"MemoryFormer: Minimize Transformer Computation by Removing Fully-Connected Layers","abstract":"In order to reduce the computational complexity of large language models, great efforts have been made to to improve the efficiency of transformer models such as linear attention and flash-attention. However, the model size and corresponding computational complexity are constantly scaled up in pursuit of higher performance. In this work, we present MemoryFormer, a novel transformer architecture which significantly re","authors":["Ding, Ning","Tang, Yehui","Qin, Haochen","Zhou, Zhenli","Xu, Chao","Li, Lin"],"url":"https://arxiv.org/abs/2411.12992","arxiv_id":"2411.12992","published":"2026-02-04"},{"title":"Agnostic Learning of Arbitrary ReLU Activation under Gaussian Marginals","abstract":"We consider the problem of learning an arbitrarily-biased ReLU activation (or neuron) over Gaussian marginals with the squared loss objective. Despite the ReLU neuron being the basic building block of modern neural networks, we still do not understand the basic algorithmic question of whether one arbitrary ReLU neuron is learnable in the non-realizable setting. In particular, all existing polynomial time algorithms o","authors":["Guo, Anxin","Vijayaraghavan, Aravindan"],"url":"https://arxiv.org/abs/2411.14349","arxiv_id":"2411.14349","published":"2026-02-04"},{"title":"Decoding fairness: a reinforcement learning perspective","abstract":"Behavioral experiments on the ultimatum game (UG) reveal that we humans prefer fair acts, which contradicts the prediction made in orthodox Economics. Existing explanations, however, are mostly attributed to exogenous factors within the imitation learning framework. Here, we adopt the reinforcement learning paradigm, where individuals make their moves aiming to maximize their accumulated rewards. Specifically, we app","authors":["Zheng, Guozhong","Zhang, Jiqiang","Ou, Xin","Deng, Shengfeng","Chen, Li"],"url":"https://arxiv.org/abs/2412.16249","arxiv_id":"2412.16249","published":"2026-02-04"},{"title":"Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignment","abstract":"Multimodal learning has been demonstrated to enhance performance across various clinical tasks, owing to the diverse perspectives offered by different modalities of data. However, existing multimodal segmentation methods rely on well-registered multimodal data, which is unrealistic for real-world clinical images, particularly for indistinct and diffuse regions such as liver tumors. In this paper, we introduce Diff4MM","authors":["Chen, Shiyun","Lin, Li","Cheng, Pujin","Jin, ZhiCheng","Chen, JianJian","Zhu, HaiDong"],"url":"https://arxiv.org/abs/2412.20418","arxiv_id":"2412.20418","published":"2026-02-04"},{"title":"Integrators at War: Mediating in AI-assisted Resort-to-Force Decisions","abstract":"The integration of AI systems into the military domain is changing the way war-related decisions are made. It binds together three disparate groups of actors - developers, integrators, users - and creates a relationship between these groups and the machine, embedded in the (pre-)existing organisational and system structures. In this article, we focus on the important, but often neglected, group of integrators within ","authors":["Müller, Dennis","Chiodo, Maurice","Sienknecht, Mitja"],"url":"https://arxiv.org/abs/2501.06861","arxiv_id":"2501.06861","published":"2026-02-04"}],"history":{"events":[{"year":2015,"text":"Shortly after takeoff from Taipei Songshan Airport, the crew of TransAsia Airways Flight 235 shut down the wrong engine in response to a flameout, leading to a crash that resulted in 43 deaths.","url":"https://en.wikipedia.org/wiki/Songshan_Airport"},{"year":2008,"text":"The London low emission zone (sign pictured), charging certain diesel-powered commercial vehicles to enter Greater London, came into operation.","url":"https://en.wikipedia.org/wiki/London_low_emission_zone"},{"year":1999,"text":"Four plain-clothes New York City police officers shot and killed Amadou Diallo, an unarmed 23-year-old immigrant from Guinea, prompting outrage both in and outside the city.","url":"https://en.wikipedia.org/wiki/New_York_City_Police_Department"},{"year":1999,"text":"The Philippine-flagged freighter New Carissa ran aground near Coos Bay, Oregon, causing one of the worst oil spills in the state's history.","url":"https://en.wikipedia.org/wiki/New_Carissa"},{"year":1998,"text":"An earthquake registering 5.9 MW struck northern Afghanistan, triggering landslides that killed over 2,300 people and destroyed around 15,000 homes.","url":"https://en.wikipedia.org/wiki/February_1998_Afghanistan_earthquake"},{"year":1974,"text":"American newspaper heiress and socialite Patty Hearst was kidnapped by the Symbionese Liberation Army, which she later joined.","url":"https://en.wikipedia.org/wiki/Patty_Hearst"},{"year":1974,"text":"The Troubles: The Provisional Irish Republican Army bombed a motor coach carrying off-duty British Armed Forces personnel and their family members, killing twelve people.","url":"https://en.wikipedia.org/wiki/The_Troubles"},{"year":1969,"text":"Yasser Arafat (pictured) was elected chairman of the Palestine Liberation Organization.","url":"https://en.wikipedia.org/wiki/Yasser_Arafat"},{"year":1945,"text":"World War II: American forces liberated the Santo Tomas Internment Camp in Manila, the largest Japanese-run internment camp for enemy civilians in the Philippines.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1899,"text":"The Philippine–American War began when an American soldier, under orders to keep insurgents away from his unit's encampment, fired on a Filipino soldier in Manila.","url":"https://en.wikipedia.org/wiki/Philippine%E2%80%93American_War"},{"year":1859,"text":"Constantin von Tischendorf rediscovered the Codex Sinaiticus, a 4th-century great uncial codex of the Bible in Greek, in Saint Catherine's Monastery, Egypt.","url":"https://en.wikipedia.org/wiki/Constantin_von_Tischendorf"},{"year":1820,"text":"Chilean War of Independence: Chilean forces captured the city of Valdivia.","url":"https://en.wikipedia.org/wiki/Chilean_War_of_Independence"},{"year":1801,"text":"John Marshall, whose court opinions helped lay the basis for U.S. constitutional law and made the Supreme Court a coequal branch of government, took office as chief justice.","url":"https://en.wikipedia.org/wiki/John_Marshall"},{"year":1797,"text":"The Riobamba earthquake, the most powerful in Ecuador's history, devastated Riobamba and many other cities, causing at least 6,000 casualties.","url":"https://en.wikipedia.org/wiki/1797_Riobamba_earthquake"},{"year":1555,"text":"Marian Restoration: Because he opposed Catholicism, John Rogers was burned at the stake (pictured) as the first English Protestant executed for heresy under the reign of Mary I.","url":"https://en.wikipedia.org/wiki/English_Reformation"},{"year":1488,"text":"Bartolomeu Dias landed in Mossel Bay, becoming the first European known to have sailed around the Cape of Good Hope, the southern tip of Africa, beginning Portuguese influence and trade in the Indian Ocean.","url":"https://en.wikipedia.org/wiki/Bartolomeu_Dias"},{"year":1169,"text":"A strong earthquake struck the eastern coast of Sicily, causing at least 15,000 deaths.","url":"https://en.wikipedia.org/wiki/1169_Sicily_earthquake"},{"year":960,"text":"Emperor Taizu (pictured) came to power, initiating the Song dynasty of China that eventually lasted for more than three centuries.","url":"https://en.wikipedia.org/wiki/Emperor_Taizu_of_Song"}],"births":[{"year":2003,"text":"Kyla Kenedy, American actress","url":"https://en.wikipedia.org/wiki/Kyla_Kenedy"},{"year":2003,"text":"Rasmus Højlund, Danish footballer","url":"https://en.wikipedia.org/wiki/Rasmus_H%C3%B8jlund"},{"year":1999,"text":"MJ Lenderman, American singer-songwriter and multi-instrumentalist","url":"https://en.wikipedia.org/wiki/MJ_Lenderman"},{"year":1998,"text":"Malik Monk, American basketball player","url":"https://en.wikipedia.org/wiki/Malik_Monk"},{"year":1998,"text":"Maximilian Wöber, Austrian footballer","url":"https://en.wikipedia.org/wiki/Maximilian_W%C3%B6ber"},{"year":1996,"text":"Mohamed Sherif, Egyptian footballer","url":"https://en.wikipedia.org/wiki/Mohamed_Sherif"},{"year":1989,"text":"Lavoy Allen, American basketball player","url":"https://en.wikipedia.org/wiki/Lavoy_Allen"},{"year":1988,"text":"Charlie Barnett, American actor","url":"https://en.wikipedia.org/wiki/Charlie_Barnett_(actor)"}],"deaths":[{"year":2025,"text":"Aga Khan IV, 49th Imam of the Nizari Isma'ili community (born 1936)","url":"https://en.wikipedia.org/wiki/Aga_Khan_IV"},{"year":2024,"text":"Barry John, Welsh rugby player (born 1945)","url":"https://en.wikipedia.org/wiki/Barry_John"},{"year":2023,"text":"Vani Jairam, Indian playback singer (born 1945)","url":"https://en.wikipedia.org/wiki/Vani_Jairam"},{"year":2023,"text":"Sherif Ismail, 53rd Prime Minister of Egypt (born 1955)","url":"https://en.wikipedia.org/wiki/Sherif_Ismail"},{"year":2022,"text":"Kim In-hyeok, South Korean volleyball player (born 1995)","url":"https://en.wikipedia.org/wiki/Kim_In-hyeok"},{"year":2021,"text":"Millie Hughes-Fulford, American astronaut, molecular biologist and NASA payload specialist (born 1945)","url":"https://en.wikipedia.org/wiki/Millie_Hughes-Fulford"},{"year":2020,"text":"Daniel arap Moi, Former President of Kenya (born 1924)","url":"https://en.wikipedia.org/wiki/Daniel_arap_Moi"},{"year":2019,"text":"Matti Nykänen, Finnish Olympic-winning ski jumper and singer (born 1963)","url":"https://en.wikipedia.org/wiki/Matti_Nyk%C3%A4nen"}]},"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 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Every item links to its source."}