{"date":"2026-03-09","schema_version":1,"captured_at":"2026-08-25T23:31:48.703Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Men's T20 World Cup","views":408146,"rank":3,"extract":"The ICC Men's T20 World Cup, formerly the ICC World Twenty20, is a biennial world cup for cricket in Twenty20 International (T20I) format, organised by the International Cricket Council (ICC). 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(March 2026)","points":290,"comments":1131,"url":"https://news.ycombinator.com/item?id=47303111","discussion":"https://news.ycombinator.com/item?id=47303111"},{"title":"FFmpeg at Meta: Media Processing at Scale","points":281,"comments":100,"url":"https://engineering.fb.com/2026/03/02/video-engineering/ffmpeg-at-meta-media-processing-at-scale/","discussion":"https://news.ycombinator.com/item?id=47305236"},{"title":"Tony Hoare has died","points":268,"comments":34,"url":"http://lefenetrou.blogspot.com/2026/03/in-memoriam-tony-hoare.html","discussion":"https://news.ycombinator.com/item?id=47316880"},{"title":"Okmain: How to pick an OK main colour of an image","points":253,"comments":47,"url":"https://dgroshev.com/blog/okmain/","discussion":"https://news.ycombinator.com/item?id=47309397"},{"title":"The engine of Germany's wealth is blocking its future","points":248,"comments":337,"url":"https://europeancorrespondent.com/en/r/the-engine-of-germanys-wealth-is-blocking-its-future","discussion":"https://news.ycombinator.com/item?id=47310073"},{"title":"The death of social media is the renaissance of RSS (2025)","points":241,"comments":170,"url":"https://www.smartlab.at/rss-revival-life-after-social-media/","discussion":"https://news.ycombinator.com/item?id=47304886"},{"title":"DARPA’s new X-76","points":229,"comments":221,"url":"https://www.darpa.mil/news/2026/darpa-new-x-76-speed-of-jet-freedom-of-helicopter","discussion":"https://news.ycombinator.com/item?id=47311669"},{"title":"Jolla on track to ship new phone with Sailfish OS, user-replaceable battery","points":226,"comments":150,"url":"https://liliputing.com/the-new-jolla-phone-with-sailfish-os-is-on-track-to-start-shipping-in-the-first-half-of-2026/","discussion":"https://news.ycombinator.com/item?id=47311456"},{"title":"Workers report watching Ray-Ban Meta-shot footage of people using the bathroom","points":223,"comments":82,"url":"https://arstechnica.com/gadgets/2026/03/workers-report-watching-ray-ban-meta-shot-footage-of-people-using-the-bathroom/","discussion":"https://news.ycombinator.com/item?id=47313613"},{"title":"New farm bill would condemn pigs to a lifetime in gestation crates","points":207,"comments":229,"url":"https://twitter.com/Lewis_Bollard/status/2030985704902099335","discussion":"https://news.ycombinator.com/item?id=47310092"},{"title":"IMG_0416 (2024)","points":199,"comments":46,"url":"https://ben-mini.com/2024/img-0416","discussion":"https://news.ycombinator.com/item?id=47308547"},{"title":"Fixfest is a global gathering of repairers, tinkerers, and activists","points":182,"comments":20,"url":"https://fixfest.therestartproject.org/","discussion":"https://news.ycombinator.com/item?id=47312329"},{"title":"Reverse-engineering the UniFi inform protocol","points":175,"comments":76,"url":"https://tamarack.cloud/blog/reverse-engineering-unifi-inform-protocol","discussion":"https://news.ycombinator.com/item?id=47308278"}],"research":[{"title":"A mixed-frequency approach for exchange rates predictions","abstract":"Selecting an appropriate statistical model to forecast exchange rates is still today a relevant issue for policymakers and central bankers. The so-called Meese and Rogoff puzzle assesses that exchange rate fluctuations are unpredictable. In the literature, a lot of studies tried to solve the puzzle finding alternative predictors and statistical models based on temporal aggregation. In this paper, we propose an approa","authors":["Mattera, Raffaele","Misuraca, Michelangelo","Scepi, Germana","Spano, Maria"],"url":"https://arxiv.org/abs/2106.00283","arxiv_id":"2106.00283","published":"2026-03-09"},{"title":"A Cognitive Explainer for Fetal ultrasound images classifier Based on Medical Concepts","abstract":"Fetal standard scan plane detection during 2-D mid-pregnancy examinations is a highly complex task, which requires extensive medical knowledge and years of training. Although deep neural networks (DNN) can assist inexperienced operators in these tasks, their lack of transparency and interpretability limit their application. Despite some researchers have been committed to visualizing the decision process of DNN, most ","authors":["Wanga, Yingni","Liua, Yunxiao","Dongc, Licong","Wua, Xuzhou","Zhangb, Huabin","Yed, Qiongyu"],"url":"https://arxiv.org/abs/2201.07798","arxiv_id":"2201.07798","published":"2026-03-09"},{"title":"Mean-based incomplete pairwise comparisons method with the reference values","abstract":"In this article, we propose two quantitative methods for calculating weight vectors for incomplete pairwise comparison matrices using reference values. Both procedures are extensions of arithmetic and geometric heuristic estimation (HRE) methods. The proposed solutions allow flexible selection of the number of reference alternatives and the range of comparisons, from the acceptable minimum to a complete set. In this ","authors":["Kułakowski, Konrad","Kędzior, Anna","Szybowski, Jacek","Mazurek, Jiri"],"url":"https://arxiv.org/abs/2207.10783","arxiv_id":"2207.10783","published":"2026-03-09"},{"title":"Correlations Between COVID-19 and Dengue","abstract":"A dramatic increase in the number of outbreaks of Dengue has recently been reported, and climate change is likely to extend the geographical spread of the disease. In this context, this paper shows how a neural network approach can incorporate Dengue and COVID-19 data as well as external factors (such as social behaviour or climate variables), to develop predictive models that could improve our knowledge and provide ","authors":["Bergero, Paula","Schaposnik, Laura P.","Wang, Grace"],"url":"https://arxiv.org/abs/2207.13561","arxiv_id":"2207.13561","published":"2026-03-09"},{"title":"Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs","abstract":"As phasor measurement units (PMUs) become more widely used in transmission power systems, a fast state estimation (SE) algorithm that can take advantage of their high sample rates is needed. To accomplish this, we present a method that uses graph neural networks (GNNs) to learn complex bus voltage estimates from PMU voltage and current measurements. We propose an original implementation of GNNs over the power system&","authors":["Kundacina, Ognjen","Cosovic, Mirsad","Miskovic, Dragisa","Vukobratovic, Dejan"],"url":"https://arxiv.org/abs/2304.14680","arxiv_id":"2304.14680","published":"2026-03-09"},{"title":"Analyzing the Performance of ChatGPT in Cardiology and Vascular Pathologies","abstract":"The article aims to analyze the performance of ChatGPT, a large language model developed by OpenAI, in the context of cardiology and vascular pathologies. The study evaluated the accuracy of ChatGPT in answering challenging multiple-choice questions (QCM) using a dataset of 190 questions from the Siamois-QCM platform. The goal was to assess ChatGPT potential as a valuable tool in medical education compared to two wel","authors":["Hariri, Walid"],"url":"https://arxiv.org/abs/2307.02518","arxiv_id":"2307.02518","published":"2026-03-09"},{"title":"Expert-Aided Causal Discovery of Ancestral Graphs","abstract":"Causal discovery (CD) is an important component of many scientific applications, yet most techniques produce unreliable point estimates that often contradict expert knowledge. To mitigate this, recent research has focused on ex-ante incorporation of background knowledge into the CD process, typically under an unrealistic causal sufficiency assumption. When probing experts is costly (e.g., hidden behind expensive LLM ","authors":["da Silva, Tiago","Bazaluk, Bruna","da Silva, Eliezer de Souza","Góis, António","Lahlou, Salem","Heider, Dominik"],"url":"https://arxiv.org/abs/2309.12032","arxiv_id":"2309.12032","published":"2026-03-09"},{"title":"RBF Weighted Hyper-Involution for RGB-D Object Detection","abstract":"A vast majority of augmented reality devices come equipped with depth and color cameras. Despite their advantages, extracting both photometric and depth features simultaneously in real-time remains challenging due to inherent differences between depth and color images. Furthermore, standard convolution operations are insufficient for extracting information directly from raw depth images, leading to inefficient interm","authors":["Rahman, Mehfuz A","Das, Khushal","Poovvancheri, Jiju","London, Neil","Chen, Dong"],"url":"https://arxiv.org/abs/2310.00342","arxiv_id":"2310.00342","published":"2026-03-09"},{"title":"A unified framework for learning with nonlinear model classes from arbitrary linear samples","abstract":"We study the fundamental problem of learning an unknown object from data using a prescribed model class. We introduce a unified framework that accommodates objects in arbitrary Hilbert spaces, general (possibly vector-valued) random linear measurements and general types of nonlinear models. We establish novel learning guarantees for this framework that explicitly relate the required amount of data to structural prope","authors":["Adcock, Ben","Cardenas, Juan M.","Dexter, Nick"],"url":"https://arxiv.org/abs/2311.14886","arxiv_id":"2311.14886","published":"2026-03-09"},{"title":"TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training","abstract":"Spiking Neural Networks (SNNs) have gained significant attention as a potentially energy-efficient alternative for standard neural networks with their sparse binary activation. However, SNNs suffer from memory and computation overhead due to spatio-temporal dynamics and multiple backpropagation computations across timesteps during training. To address this issue, we introduce Tensor Train Decomposition for Spiking Ne","authors":["Lee, Donghyun","Yin, Ruokai","Kim, Youngeun","Moitra, Abhishek","Li, Yuhang","Panda, Priyadarshini"],"url":"https://arxiv.org/abs/2401.08001","arxiv_id":"2401.08001","published":"2026-03-09"},{"title":"The Generative AI Paradox on Evaluation: What It Can Solve, It May Not Evaluate","abstract":"This paper explores the assumption that Large Language Models (LLMs) skilled in generation tasks are equally adept as evaluators. We assess the performance of three LLMs and one open-source LM in Question-Answering (QA) and evaluation tasks using the TriviaQA (Joshi et al., 2017) dataset. Results indicate a significant disparity, with LLMs exhibiting lower performance in evaluation tasks compared to generation tasks.","authors":["Oh, Juhyun","Kim, Eunsu","Cha, Inha","Oh, Alice"],"url":"https://arxiv.org/abs/2402.06204","arxiv_id":"2402.06204","published":"2026-03-09"},{"title":"RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model","abstract":"We need to trust robots that use often opaque AI methods. They need to explain themselves to us, and we need to trust their explanation. In this regard, explainability plays a critical role in trustworthy autonomous decision-making to foster transparency and acceptance among end users, especially in complex autonomous driving. Recent advancements in Multi-Modal Large Language models (MLLMs) have shown promising poten","authors":["Yuan, Jianhao","Sun, Shuyang","Omeiza, Daniel","Zhao, Bo","Newman, Paul","Kunze, Lars"],"url":"https://arxiv.org/abs/2402.10828","arxiv_id":"2402.10828","published":"2026-03-09"},{"title":"Make VLM Recognize Visual Hallucination on Cartoon Character Image with Pose Information","abstract":"Leveraging large-scale Text-to-Image (TTI) models have become a common technique for generating exemplar or training dataset in the fields of image synthesis, video editing, 3D reconstruction. However, semantic structural visual hallucinations involving perceptually severe defects remain a concern, especially in the domain of non-photorealistic rendering (NPR) such as cartoons and pixelization-style character. To det","authors":["Kim, Bumsoo","Shin, Wonseop","Lee, Kyuchul","Jung, Yonghoon","Seo, Sanghyun"],"url":"https://arxiv.org/abs/2403.15048","arxiv_id":"2403.15048","published":"2026-03-09"},{"title":"Algorithmic Collusion by Large Language Models","abstract":"We conduct experiments with algorithmic pricing agents based on Large Language Models (LLMs). In oligopoly settings, LLM-based pricing agents quickly and autonomously reach supracompetitive prices and profits. Variation in seemingly innocuous phrases in LLM instructions ("prompts") substantially influence the degree of supracompetitive pricing. We develop novel techniques for behavioral analysis of LLMs and u","authors":["Fish, Sara","Gonczarowski, Yannai A.","Shorrer, Ran I."],"url":"https://arxiv.org/abs/2404.00806","arxiv_id":"2404.00806","published":"2026-03-09"},{"title":"Sentiment Analysis of Citations in Scientific Articles Using ChatGPT: Identifying Potential Biases and Conflicts of Interest","abstract":"Scientific articles play a crucial role in advancing knowledge and informing research directions. One key aspect of evaluating scientific articles is the analysis of citations, which provides insights into the impact and reception of the cited works. This article introduces the innovative use of large language models, particularly ChatGPT, for comprehensive sentiment analysis of citations within scientific articles. ","authors":["Hariri, Walid"],"url":"https://arxiv.org/abs/2404.01800","arxiv_id":"2404.01800","published":"2026-03-09"},{"title":"BInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Design","abstract":"Recent remarkable advancements in geometric deep generative models, coupled with accumulated structural data, enable structure-based drug design (SBDD) using only target protein information. However, existing models often struggle to balance multiple objectives, excelling only in specific tasks. BInD, a diffusion model with knowledge-based guidance, is introduced to address this limitation by co-generating molecules ","authors":["Lee, Joongwon","Zhung, Wonho","Seo, Jisu","Kim, Woo Youn"],"url":"https://arxiv.org/abs/2405.16861","arxiv_id":"2405.16861","published":"2026-03-09"},{"title":"Combining X-Vectors and Bayesian Batch Active Learning: Two-Stage Active Learning Pipeline for Speech Recognition","abstract":"This paper introduces a novel two-stage active learning (AL) pipeline for automatic speech recognition (ASR), combining unsupervised and supervised AL methods. The first stage utilizes unsupervised AL by using x-vectors clustering for diverse sample selection from unlabeled speech data, thus establishing a robust initial dataset for the subsequent supervised AL. The second stage incorporates a supervised AL strategy,","authors":["Kundacina, Ognjen","Vincan, Vladimir","Miskovic, Dragisa"],"url":"https://arxiv.org/abs/2406.02566","arxiv_id":"2406.02566","published":"2026-03-09"},{"title":"My part is bigger than yours -- assessment within a group of peers","abstract":"A project (e.g., writing a collaborative research paper) is often a group effort. At the end, each contributor identifies their contribution, often verbally. The reward, however, is very frequently financial. It leads to the question of what (percentage) share in the creation of the paper is due to individual authors. Different authors may have various opinions on the matter; even worse, their opinions may have diffe","authors":["Kułakowski, Konrad","Szybowski, Jacek"],"url":"https://arxiv.org/abs/2407.01843","arxiv_id":"2407.01843","published":"2026-03-09"},{"title":"Predictive Coding Networks and Inference Learning: Tutorial and Survey","abstract":"Recent years have witnessed a growing call for renewed emphasis on neuroscience-inspired approaches in artificial intelligence research, under the banner of NeuroAI. A prime example of this is predictive coding networks (PCNs), based on the neuroscientific framework of predictive coding. This framework views the brain as a hierarchical Bayesian inference model that minimizes prediction errors through feedback connect","authors":["van Zwol, Björn","Jefferson, Ro","Broek, Egon L. van den"],"url":"https://arxiv.org/abs/2407.04117","arxiv_id":"2407.04117","published":"2026-03-09"},{"title":"Transforming Agency. On the mode of existence of Large Language Models","abstract":"This paper investigates the ontological characterization of Large Language Models (LLMs) like ChatGPT. Between inflationary and deflationary accounts, we pay special attention to their status as agents. This requires explaining in detail the architecture, processing, and training procedures that enable LLMs to display their capacities, and the extensions used to turn LLMs into agent-like systems. After a systematic a","authors":["Barandiaran, Xabier E.","Almendros, Lola S."],"url":"https://arxiv.org/abs/2407.10735","arxiv_id":"2407.10735","published":"2026-03-09"},{"title":"Do Prevalent Bias Metrics Capture Allocational Harms from LLMs?","abstract":"Allocational harms occur when resources or opportunities are unfairly withheld from specific groups. Many proposed bias measures ignore the discrepancy between predictions, which are what the proposed methods consider, and decisions that are made as a result of those predictions. Our work examines the reliability of current bias metrics in assessing allocational harms arising from predictions of large language models","authors":["Cyberey, Hannah","Ji, Yangfeng","Evans, David"],"url":"https://arxiv.org/abs/2408.01285","arxiv_id":"2408.01285","published":"2026-03-09"},{"title":"Fuse4Seg: Image Fusion for Multi-Modal Medical Segmentation via Bi-level Optimization","abstract":"Multi-modal medical image fusion is traditionally optimized for human visual perception, aiming to maximize generic contrast and structural fidelity. However, when these visually pleasing fused images are deployed in automated clinical workflows, this visual-semantic discrepancy causes task-agnostic feature degradation, inadvertently smoothing out critical, high-frequency tumor boundaries. To bridge this semantic gap","authors":["Guo, Yuchen","Gong, Junli","Cai, Hongmin","Cheung, Yiu-ming","Su, Weifeng"],"url":"https://arxiv.org/abs/2409.10328","arxiv_id":"2409.10328","published":"2026-03-09"},{"title":"PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization","abstract":"Parameter-Efficient Fine-Tuning (PEFT) effectively adapts pre-trained transformers to downstream tasks. However, the optimization of tasks performance often comes at the cost of generalizability in fine-tuned models. To address this issue, we theoretically connect smaller weight gradient norms during training and larger datasets to the improvements in model generalization. Motivated by this connection, we propose red","authors":["Ni, Yao","Zhang, Shan","Koniusz, Piotr"],"url":"https://arxiv.org/abs/2409.17137","arxiv_id":"2409.17137","published":"2026-03-09"},{"title":"FALCON: Future-Aware Learning with Contextual Object-Centric Pretraining for UAV Action Recognition","abstract":"We introduce FALCON, a unified self-supervised video pretraining approach for UAV action recognition from raw RGB aerial footage, requiring no additional preprocessing at inference. UAV videos exhibit severe spatial imbalance: large, cluttered backgrounds dominate the field of view, causing reconstruction-based pretraining to waste capacity on uninformative regions and under-learn action-relevant human/object cues. F","authors":["Xian, Ruiqi","Wu, Xiyang","Guan, Tianrui","Wang, Xijun","Gong, Boqing","Manocha, Dinesh"],"url":"https://arxiv.org/abs/2409.18300","arxiv_id":"2409.18300","published":"2026-03-09"},{"title":"AuthFace: Towards Authentic Blind Face Restoration with Face-oriented Generative Diffusion Prior","abstract":"Blind face restoration (BFR) is a fundamental and challenging problem in computer vision. To faithfully restore high-quality (HQ) photos from poor-quality ones, recent research endeavors predominantly rely on facial image priors from the powerful pretrained text-to-image (T2I) diffusion models. However, such priors often lead to the incorrect generation of non-facial features and insufficient facial details, thus ren","authors":["Liang, Guoqiang","Fan, Qingnan","Fu, Bingtao","Chen, Jinwei","Gu, Hong","Wang, Lin"],"url":"https://arxiv.org/abs/2410.09864","arxiv_id":"2410.09864","published":"2026-03-09"}],"history":{"events":[{"year":1977,"text":"Twelve gunmen seized three buildings in Washington, D.C., and took 149 hostages in a 39-hour standoff that ended in two deaths.","url":"https://en.wikipedia.org/wiki/Washington%2C_D.C."},{"year":1967,"text":"Svetlana Alliluyeva, the daughter of former Soviet leader Joseph Stalin, defected to the United States.","url":"https://en.wikipedia.org/wiki/Svetlana_Alliluyeva"},{"year":1959,"text":"The popular fashion doll Barbie debuted at the American International Toy Fair in New York City.","url":"https://en.wikipedia.org/wiki/Barbie"},{"year":1957,"text":"The Andreanof Islands earthquake struck Hawaii and the Aleutian Islands, causing more than $5 million in damage from ground movement and a destructive tsunami.","url":"https://en.wikipedia.org/wiki/1957_Andreanof_Islands_earthquake"},{"year":1956,"text":"In Tbilisi, Georgia, soldiers suppressed mass demonstrations against Soviet leader Nikita Khrushchev's policy of de-Stalinization.","url":"https://en.wikipedia.org/wiki/Tbilisi"},{"year":1946,"text":"Thirty-three people were killed in a human crush at Burnden Park, a football stadium in Bolton, England.","url":"https://en.wikipedia.org/wiki/Burnden_Park_disaster"},{"year":1944,"text":"World War II: As part of the Battle of Narva, the Soviet Air Forces heavily bombed Tallinn, Estonia, killing up to 800 people, mostly civilians.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1933,"text":"U.S. president Franklin D. Roosevelt submitted the Emergency Banking Act to the United States Congress, the first of his New Deal policies.","url":"https://en.wikipedia.org/wiki/Franklin_D._Roosevelt"},{"year":1932,"text":"Éamon de Valera (pictured), a dominant political figure in 20th-century Ireland, became President of the Executive Council of the Irish Free State.","url":"https://en.wikipedia.org/wiki/%C3%89amon_de_Valera"},{"year":1927,"text":"Former Royal Air Force officer Vivian Stranders (pictured) was convicted of industrial espionage by a French court.","url":"https://en.wikipedia.org/wiki/Royal_Air_Force"},{"year":1925,"text":"The Royal Air Force began a bombardment and strafing campaign against the mountain strongholds of Mahsud tribesmen in South Waziristan, present-day Pakistan.","url":"https://en.wikipedia.org/wiki/Royal_Air_Force"},{"year":1910,"text":"A seventeen-month-long strike, which at its peak involved 15,000 coal miners represented by the United Mine Workers across 65 mines, began in Westmoreland County, Pennsylvania, U.S.","url":"https://en.wikipedia.org/wiki/Westmoreland_County_coal_strike_of_1910%E2%80%931911"},{"year":1891,"text":"Kaʻiulani (pictured) was appointed the heir apparent to the throne of the Hawaiian Kingdom.","url":"https://en.wikipedia.org/wiki/Ka%CA%BBiulani"},{"year":1862,"text":"American Civil War: In the world's first battle between two ironclad warships, USS Monitor and CSS Virginia fought to a draw near the mouth of Hampton Roads in Virginia.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1847,"text":"Mexican–American War: The Siege of Veracruz began, the first large-scale amphibious assault conducted by United States military forces.","url":"https://en.wikipedia.org/wiki/Mexican%E2%80%93American_War"},{"year":1842,"text":"Awaking from a nap under a tree at Rancho San Francisco, Francisco López made the first popularly documented discovery of gold in California.","url":"https://en.wikipedia.org/wiki/Rancho_San_Francisco"},{"year":1842,"text":"Nabucco, an opera by Italian composer Giuseppe Verdi that established his reputation, premiered at La Scala in Milan.","url":"https://en.wikipedia.org/wiki/Nabucco"},{"year":1776,"text":"Scottish philosopher Adam Smith published his book The Wealth of Nations, the first classical treatise on political economy.","url":"https://en.wikipedia.org/wiki/Adam_Smith"}],"births":[{"year":2003,"text":"Sunisa Lee, American gymnast","url":"https://en.wikipedia.org/wiki/Sunisa_Lee"},{"year":2002,"text":"Usman Garuba, Spanish basketball player","url":"https://en.wikipedia.org/wiki/Usman_Garuba"},{"year":2001,"text":"Jeon Somi, South Korean-Canadian singer","url":"https://en.wikipedia.org/wiki/Jeon_Somi"},{"year":2000,"text":"Khaby Lame, Senegalese-Italian social media personality","url":"https://en.wikipedia.org/wiki/Khaby_Lame"},{"year":1999,"text":"Ukko-Pekka Luukkonen, Finnish ice hockey player","url":"https://en.wikipedia.org/wiki/Ukko-Pekka_Luukkonen"},{"year":1998,"text":"Najee Harris, American football running back","url":"https://en.wikipedia.org/wiki/Najee_Harris"},{"year":1997,"text":"Nadeo Argawinata, Indonesian footballer","url":"https://en.wikipedia.org/wiki/Nadeo_Argawinata"},{"year":1997,"text":"Chika, American rapper","url":"https://en.wikipedia.org/wiki/Chika_(rapper)"}],"deaths":[{"year":2023,"text":"Chaim Topol, Israeli actor (born 1935)","url":"https://en.wikipedia.org/wiki/Chaim_Topol"},{"year":2021,"text":"James Levine, American conductor and pianist (born 1943)","url":"https://en.wikipedia.org/wiki/James_Levine"},{"year":2021,"text":"Roger Mudd, American journalist (born 1928)","url":"https://en.wikipedia.org/wiki/Roger_Mudd"},{"year":2020,"text":"John Bathersby, Australian Catholic bishop (born 1936)","url":"https://en.wikipedia.org/wiki/John_Bathersby"},{"year":2018,"text":"Jo Min-ki, Korean actor (born 1965)","url":"https://en.wikipedia.org/wiki/Jo_Min-ki"},{"year":2017,"text":"Howard Hodgkin, British painter (born 1932)","url":"https://en.wikipedia.org/wiki/Howard_Hodgkin"},{"year":2016,"text":"Robert Horton, American actor (born 1924)","url":"https://en.wikipedia.org/wiki/Robert_Horton_(actor)"},{"year":2016,"text":"Clyde Lovellette, American basketball player and coach (born 1929)","url":"https://en.wikipedia.org/wiki/Clyde_Lovellette"}]},"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 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Every item links to its source."}