{"date":"2026-03-11","schema_version":1,"captured_at":"2026-08-25T23:31:29.588Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"2026 Iran war","views":330838,"rank":3,"extract":"Since 28 February 2026, the United States and Israel have been at war with Iran and its regional allies. Hostilities broke out after US–Israeli airstrikes killed several Iranian officials, including Supreme Leader Ali Khamenei. The strikes were launched amid o","url":"https://en.wikipedia.org/wiki/2026_Iran_war","thumb":null},{"title":"Mojtaba Khamenei","views":217486,"rank":6,"extract":"Mojtaba Hosseini Khamenei is an Iranian Shia cleric and politician who has served as the third supreme leader of Iran since 2026. A member of the Khamenei family and the second son of second supreme leader Ali Khamenei, he previously served as Vakil of the Sup","url":"https://en.wikipedia.org/wiki/Mojtaba_Khamenei","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/c/c6/Portrait_of_Mojtaba_Khamenei.jpg/330px-Portrait_of_Mojtaba_Khamenei.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Enhypen","views":135437,"rank":7,"extract":"Enhypen is a South Korean boy band formed by Belift Lab. Formerly a joint venture between CJ ENM and Hybe Corporation, the group was formed through the 2020 survival competition show I-Land. 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Tal and Oren were luxury real estate brokers based in Miami and New York City, while Alon was an executive at ","url":"https://en.wikipedia.org/wiki/Alexander_brothers_(sex_offenders)","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/d0/Alexander_brothers.jpg/330px-Alexander_brothers.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Donald Trump","views":73686,"rank":30,"extract":"Donald John Trump is an American politician, media personality, and businessman who is the 47th president of the United States. 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The band's core members included multi-instrumentalist Scholz and lead vocalist Brad Delp, who remained the only constant members from 1975 to","url":"https://en.wikipedia.org/wiki/Boston_(band)","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/5/5e/Boston_1977.JPG/330px-Boston_1977.JPG?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"}],"frontier":[{"title":"Don't post generated/AI-edited comments. 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failure","points":221,"comments":476,"url":"https://www.theregister.com/2026/03/11/swiss_evote_usb_snafu/","discussion":"https://news.ycombinator.com/item?id=47334982"}],"research":[{"title":"SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving","abstract":"With the advancement of vision-based autonomous driving technology, pedestrian detection have become an important component for improving traffic safety and driving system robustness. Nevertheless, in complex traffic scenarios, conventional pose estimation approaches frequently fail to accurately reconstruct occluded keypoints, primarily due to obstructions caused by vehicles, vegetation, or architectural elements. T","authors":["Fu, Honghao","Gu, Yongli","Yan, Yidong","Shen, Yilang","Wu, Yiwen","Sun, Libo"],"url":"https://arxiv.org/abs/2306.03538","arxiv_id":"2306.03538","published":"2026-03-11"},{"title":"A Survey on Decentralized Federated Learning","abstract":"Federated learning (FL) enables collaborative training without pooling raw data, but standard FL relies on a central coordinator, which introduces a single point of failure and concentrates trust in the orchestration infrastructure. Decentralized federated learning (DFL) removes the coordinator and replaces client-server orchestration with peer-to-peer coordination, making learning dynamics topology-dependent and res","authors":["Gabrielli, Edoardo","Di Pietro, Anthony","Fenoglio, Dario","Pica, Giovanni","Tolomei, Gabriele"],"url":"https://arxiv.org/abs/2308.04604","arxiv_id":"2308.04604","published":"2026-03-11"},{"title":"Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets","abstract":"The Strong Lottery Ticket Hypothesis (SLTH) states that randomly-initialised neural networks likely contain subnetworks that perform well without any training. Although unstructured pruning has been extensively studied in this context, its structured counterpart, which can deliver significant computational and memory efficiency gains, has been largely unexplored. One of the main reasons for this gap is the limitation","authors":["da Cunha, Arthur","d'Amore, Francesco","Natale, Emanuele"],"url":"https://arxiv.org/abs/2311.09858","arxiv_id":"2311.09858","published":"2026-03-11"},{"title":"A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI Decoding","abstract":"The Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an efficient technology for target retrieval using electroencephalography (EEG) signals. The performance improvement of traditional decoding methods relies on a substantial amount of training data from new test subjects, which increases preparation time for BCI systems. Several studies introduce data from existing subjects to reduce t","authors":["Li, Xujin","Wei, Wei","Qiu, Shuang","He, Huiguang"],"url":"https://arxiv.org/abs/2401.06340","arxiv_id":"2401.06340","published":"2026-03-11"},{"title":"PnLCalib: Sports Field Registration via Points and Lines Optimization","abstract":"Camera calibration in broadcast sports videos presents numerous challenges for accurate sports field registration due to multiple camera angles, varying camera parameters, and frequent occlusions of the field. Traditional search-based methods depend on initial camera pose estimates, which can struggle in non-standard positions and dynamic environments. In response, we propose an optimization-based calibration pipelin","authors":["Gutiérrez-Pérez, Marc","Agudo, Antonio"],"url":"https://arxiv.org/abs/2404.08401","arxiv_id":"2404.08401","published":"2026-03-11"},{"title":"Markovian Transformers for Informative Language Modeling","abstract":"Chain-of-Thought (CoT) reasoning often fails to faithfully reflect a language model's underlying decision process. We address this by introducing a Markovian language model framework with an autoencoder-style reasoning bottleneck: all information flowing from question to answer must pass through a bounded-length CoT, creating a bandwidth bottleneck analogous to the latent layer of an autoencoder. In practice, the","authors":["Viteri, Scott","Lamparth, Max","Chatain, Peter","Barrett, Clark"],"url":"https://arxiv.org/abs/2404.18988","arxiv_id":"2404.18988","published":"2026-03-11"},{"title":"DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the Wild","abstract":"Blind image quality assessment (IQA) in the wild, which assesses the quality of images with complex authentic distortions and no reference images, presents significant challenges. Given the difficulty in collecting large-scale training data, leveraging limited data to develop a model with strong generalization remains an open problem. Motivated by the robust image perception capabilities of pre-trained text-to-image ","authors":["Fu, Honghao","Wang, Yufei","Yang, Wenhan","Kot, Alex C.","Wen, Bihan"],"url":"https://arxiv.org/abs/2405.19996","arxiv_id":"2405.19996","published":"2026-03-11"},{"title":"Correspondence Analysis and PMI-Based Word Embeddings: A Comparative Study","abstract":"Popular word embedding methods such as GloVe and Word2Vec are related to the factorization of the pointwise mutual information (PMI) matrix. In this paper, we establish a formal connection between correspondence analysis (CA) and PMI-based word embedding methods. CA is a dimensionality reduction method that uses singular value decomposition (SVD), and we show that CA is mathematically close to the weighted factorizat","authors":["Qi, Qianqian","Bagheri, Ayoub","Hessen, David J.","van der Heijden, Peter G. M."],"url":"https://arxiv.org/abs/2405.20895","arxiv_id":"2405.20895","published":"2026-03-11"},{"title":"Controllable Dance Generation with Style-Guided Motion Diffusion","abstract":"Dance plays an important role as an artistic form and expression in human culture, yet automatically generating dance sequences is a significant yet challenging endeavor. Existing approaches often neglect the critical aspect of controllability in dance generation. Additionally, they inadequately model the nuanced impact of music styles, resulting in dances that lack alignment with the expressive characteristics inher","authors":["Wang, Hongsong","Zhu, Ying","Geng, Xin","Wang, Liang"],"url":"https://arxiv.org/abs/2406.07871","arxiv_id":"2406.07871","published":"2026-03-11"},{"title":"Enhancing Computational Efficiency in Multiscale Systems Using Deep Learning of Coordinates and Flow Maps","abstract":"Complex systems often show macroscopic coherent behavior due to the interactions of microscopic agents like molecules, cells, or individuals in a population with their environment. However, simulating such systems poses several computational challenges during simulation as the underlying dynamics vary and span wide spatiotemporal scales of interest. To capture the fast-evolving features, finer time steps are required","authors":["Hamid, Asif","Rafiq, Danish","Nahvi, Shahkar Ahmad","Bazaz, Mohammad Abid"],"url":"https://arxiv.org/abs/2407.00011","arxiv_id":"2407.00011","published":"2026-03-11"},{"title":"Dance of the ADS: Orchestrating Failures through Historically-Informed Scenario Fuzzing","abstract":"As autonomous driving systems (ADS) advance towards higher levels of autonomy, orchestrating their safety verification becomes increasingly intricate. This paper unveils ScenarioFuzz, a pioneering scenario-based fuzz testing methodology. Designed like a choreographer who understands the past performances, it uncovers vulnerabilities in ADS without the crutch of predefined scenarios. Leveraging map road networks, such","authors":["Wang, Tong","Gu, Taotao","Deng, Huan","Li, Hu","Kuang, Xiaohui","Zhao, Gang"],"url":"https://arxiv.org/abs/2407.04359","arxiv_id":"2407.04359","published":"2026-03-11"},{"title":"Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network","abstract":"Reinforcement Learning (RL) algorithms have been used to address the challenging problems in the offloading process of vehicular ad hoc networks (VANET). More recently, they have been utilized to improve the dissemination of high-definition (HD) Maps. Nevertheless, implementing solutions such as deep Q-learning (DQN) and Actor-critic at the autonomous vehicle (AV) may lead to an increase in the computational load, ca","authors":["Redondo, Jeffrey","Aslam, Nauman","Zhang, Juan","Yuan, Zhenhui"],"url":"https://arxiv.org/abs/2407.21460","arxiv_id":"2407.21460","published":"2026-03-11"},{"title":"Sparse Variational Student-t Processes for Heavy-tailed Modeling","abstract":"The Gaussian process (GP) is a powerful tool for nonparametric modeling, but its sensitivity to outliers limits its applicability to data distributions with heavy-tails. Studentt processes offer a robust alternative for heavy tail modeling, but they lack the scalable developments of the GP to large datasets necessary for practical applications. We present Sparse Variational Student-t Processes (SVTP), the first princ","authors":["Xu, Jian","Zeng, Delu","Paisley, John"],"url":"https://arxiv.org/abs/2408.06699","arxiv_id":"2408.06699","published":"2026-03-11"},{"title":"TIMotion: Temporal and Interactive Framework for Efficient Human-Human Motion Generation","abstract":"Human-human motion generation is essential for understanding humans as social beings. Current methods fall into two main categories: single-person-based methods and separate modeling-based methods. To delve into this field, we abstract the overall generation process into a general framework MetaMotion, which consists of two phases: temporal modeling and interaction mixing. For temporal modeling, the single-person-bas","authors":["Wang, Yabiao","Wang, Shuo","Zhang, Jiangning","Fan, Ke","Wu, Jiafu","Xue, Zhucun"],"url":"https://arxiv.org/abs/2408.17135","arxiv_id":"2408.17135","published":"2026-03-11"},{"title":"Robust Training of Neural Networks at Arbitrary Precision and Sparsity","abstract":"The discontinuous operations inherent in quantization and sparsification introduce a long-standing obstacle to backpropagation, particularly in ultra-low precision and sparse regimes. While the community has long viewed quantization as unfriendly to gradient descent due to its lack of smoothness, we pinpoint-for the first time-that the key issue is the absence of a proper gradient path that allows training to learn r","authors":["Ye, Chengxi","Chu, Grace","Liu, Yanfeng","Zhang, Yichi","Lew, Lukasz","Zhang, Li"],"url":"https://arxiv.org/abs/2409.09245","arxiv_id":"2409.09245","published":"2026-03-11"},{"title":"ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning","abstract":"Hyperparameters are a critical factor in reliably training well-performing reinforcement learning (RL) agents. Unfortunately, developing and evaluating automated approaches for tuning such hyperparameters is both costly and time-consuming. As a result, such approaches are often only evaluated on a single domain or algorithm, making comparisons difficult and limiting insights into their generalizability. We propose AR","authors":["Becktepe, Jannis","Dierkes, Julian","Benjamins, Carolin","Mohan, Aditya","Salinas, David","Rajan, Raghu"],"url":"https://arxiv.org/abs/2409.18827","arxiv_id":"2409.18827","published":"2026-03-11"},{"title":"DRUPI: Dataset Reduction Using Privileged Information","abstract":"Dataset Condensation (DC) seeks to select or distill samples from large datasets into smaller subsets while preserving performance on target tasks. Existing methods primarily focus on pruning or synthesizing data in the same format as the original dataset, typically being the input data and corresponding labels. However, in DC settings, we find it is possible to synthesize more information beyond the data-label pair ","authors":["Wang, Shaobo","Jiang, Youxin","Niu, Tianle","Yang, Yantai","Zhang, Ruiji","Hu, Shuhao"],"url":"https://arxiv.org/abs/2410.01611","arxiv_id":"2410.01611","published":"2026-03-11"},{"title":"Overcoming Representation Bias in Fairness-Aware data Repair using Optimal Transport","abstract":"Optimal transport (OT) has an important role in transforming data distributions in a manner which engenders fairness. Typically, the OT operators are learnt from the unfair attribute-labelled data, and then used for their repair. Two significant limitations of this approach are as follows: (i) the OT operators for underrepresented subgroups are poorly learnt (i.e. they are susceptible to representation bias); and (ii","authors":["Langbridge, Abigail","Quinn, Anthony","Shorten, Robert"],"url":"https://arxiv.org/abs/2410.02840","arxiv_id":"2410.02840","published":"2026-03-11"},{"title":"Unsupervised Representation Learning from Sparse Transformation Analysis","abstract":"There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this paper we propose to learn representations from sequence data by factorizing the transformations of the latent variables into sparse components. Input data are first encoded as distributions of latent activations and subsequently transformed usi","authors":["Song, Yue","Keller, Thomas Anderson","Yue, Yisong","Perona, Pietro","Welling, Max"],"url":"https://arxiv.org/abs/2410.05564","arxiv_id":"2410.05564","published":"2026-03-11"},{"title":"Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions","abstract":"From autonomous driving to package delivery, ensuring safe yet efficient multi-agent interaction is challenging as the interaction dynamics are influenced by hard-to-model factors such as social norms and contextual cues. Understanding these influences can aid in the design and evaluation of socially-aware autonomous agents whose behaviors are aligned with human values. In this work, we seek to codify factors governi","authors":["Remy, Isaac","Fridovich-Keil, David","Leung, Karen"],"url":"https://arxiv.org/abs/2410.07409","arxiv_id":"2410.07409","published":"2026-03-11"},{"title":"Calabi-Yau metrics through Grassmannian learning and Donaldson's algorithm","abstract":"Motivated by recent progress in the problem of numerical Kähler metrics, we survey machine learning techniques in this area, discussing both advantages and drawbacks. We then revisit the algebraic ansatz pioneered by Donaldson. Inspired by his work, we present a novel approach to obtaining Ricci-flat approximations to Kähler metrics, applying machine learning within a `principled' framework. In particular, we use","authors":["Ek, Carl Henrik","Kim, Oisin","Mishra, Challenger"],"url":"https://arxiv.org/abs/2410.11284","arxiv_id":"2410.11284","published":"2026-03-11"},{"title":"Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning","abstract":"We propose Scalable Message Passing Neural Networks (SMPNNs) and demonstrate that, by integrating standard convolutional message passing into a Pre-Layer Normalization Transformer-style block instead of attention, we can produce high-performing deep message-passing-based Graph Neural Networks (GNNs). This modification yields results competitive with the state-of-the-art in large graph transductive learning, particula","authors":["Borde, Haitz Sáez de Ocáriz","Lukoianov, Artem","Kratsios, Anastasis","Bronstein, Michael","Dong, Xiaowen"],"url":"https://arxiv.org/abs/2411.00835","arxiv_id":"2411.00835","published":"2026-03-11"},{"title":"SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG","abstract":"The non-stationary nature of electroencephalography (EEG) introduces distribution shifts across domains (e.g., days and subjects), posing a significant challenge to EEG-based neurotechnology generalization. Without labeled calibration data for target domains, the problem is a source-free unsupervised domain adaptation (SFUDA) problem. For scenarios with constant label distribution, Riemannian geometry-aware statistic","authors":["Li, Shanglin","Kawanabe, Motoaki","Kobler, Reinmar J."],"url":"https://arxiv.org/abs/2411.07249","arxiv_id":"2411.07249","published":"2026-03-11"},{"title":"Image Compression Using Novel View Synthesis Priors","abstract":"Real-time visual feedback is essential for tetherless control of remotely operated vehicles, particularly during inspection and manipulation tasks. Though acoustic communication is the preferred choice for medium-range communication underwater, its limited bandwidth renders it impractical to transmit images or videos in real-time. To address this, we propose a model-based image compression technique that leverages pr","authors":["Peng, Luyuan","Chitre, Mandar","Vishnu, Hari","Too, Yuen Min","Kalyan, Bharath","Mishra, Rajat"],"url":"https://arxiv.org/abs/2411.13862","arxiv_id":"2411.13862","published":"2026-03-11"},{"title":"Active Prompt Learning with Vision-Language Model Priors","abstract":"Vision-language models (VLMs) have demonstrated remarkable zero-shot performance across various classification tasks. Nonetheless, their reliance on hand-crafted text prompts for each task hinders efficient adaptation to new tasks. While prompt learning offers a promising solution, most studies focus on maximizing the utilization of given few-shot labeled datasets, often overlooking the potential of careful data sele","authors":["Kim, Hoyoung","Jin, Seokhee","Sung, Changhwan","Kim, Jaechang","Ok, Jungseul"],"url":"https://arxiv.org/abs/2411.16722","arxiv_id":"2411.16722","published":"2026-03-11"}],"history":{"events":[{"year":2020,"text":"The World Health Organization (WHO) officialy declared the COVID-19 outbreak as a pandemic.","url":"https://en.wikipedia.org/wiki/World_Health_Organization"},{"year":2020,"text":"The World Health Organization (WHO) declared the COVID-19 virus epidemic a pandemic.","url":"https://en.wikipedia.org/wiki/World_Health_Organization"},{"year":2012,"text":"U.S. Army soldier Robert Bales murdered sixteen civilians and wounded six others in Kandahar Province, Afghanistan.","url":"https://en.wikipedia.org/wiki/United_States_Army"},{"year":2011,"text":"A massive earthquake and tsunami struck northeastern Japan and triggered a nuclear accident at the Fukushima Daiichi Nuclear Power Plant.","url":"https://en.wikipedia.org/wiki/2011_T%C5%8Dhoku_earthquake_and_tsunami"},{"year":2010,"text":"During the inauguration of Chilean president Sebastián Piñera, earthquakes registering 6.9 and 7.0 .mw-parser-output .tooltip-dotted{border-bottom:1px dotted;cursor:help}Mw struck the O'Higgins Region near the city of Pichilemu, causing widespread damage.","url":"https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Pi%C3%B1era"},{"year":2009,"text":"A teenage gunman engaged in a shooting spree at a secondary school in Winnenden, Germany, killing 16, including himself.","url":"https://en.wikipedia.org/wiki/2009_Winnenden_shootings"},{"year":2007,"text":"Georgian authorities accused Russia of orchestrating a helicopter attack in the Kodori Valley, in the breakaway territory of Abkhazia.","url":"https://en.wikipedia.org/wiki/2007_Georgia_helicopter_incident"},{"year":1993,"text":"The U.S. Senate unanimously confirmed Janet Reno as the first female United States attorney general.","url":"https://en.wikipedia.org/wiki/United_States_Senate"},{"year":1984,"text":"The anime film Nausicaä of the Valley of the Wind by Hayao Miyazaki was released.","url":"https://en.wikipedia.org/wiki/Anime"},{"year":1978,"text":"After hijacking a bus north of Tel Aviv, Israel, members of the Palestine Liberation Organization faction Fatah engaged in a shootout with police, resulting in the deaths of 38 civilians and most of the perpetrators.","url":"https://en.wikipedia.org/wiki/Coastal_road_massacre"},{"year":1888,"text":"The Great Blizzard of 1888 struck the northeastern United States, producing snowdrifts in excess of 50 ft (15 m) and confining some people to their houses for up to a week.","url":"https://en.wikipedia.org/wiki/Great_Blizzard_of_1888"},{"year":1851,"text":"The first performance of Verdi's Rigoletto took place at La Fenice in Venice (poster pictured).","url":"https://en.wikipedia.org/wiki/Rigoletto"},{"year":1845,"text":"Māori forces, led by chiefs Te Ruki Kawiti and Hōne Heke, attacked the British settlement of Kororāreka, New Zealand, beginning the Flagstaff War.","url":"https://en.wikipedia.org/wiki/M%C4%81ori_people"},{"year":1843,"text":"During a period of activity known as the Great Eruption, Eta Carinae (pictured) briefly became the second-brightest star in the night sky.","url":"https://en.wikipedia.org/wiki/Eta_Carinae"},{"year":1708,"text":"Queen Anne withheld royal assent from the Scottish Militia Bill, in the most recent veto by a British monarch of a bill that had been passed by Parliament.","url":"https://en.wikipedia.org/wiki/Anne%2C_Queen_of_Great_Britain"},{"year":1669,"text":"Mount Etna in Sicily began erupting, eventually producing the largest lava flow in the volcano's history, and damaging Catania and other towns.","url":"https://en.wikipedia.org/wiki/Mount_Etna"}],"births":[{"year":2004,"text":"Margarita Kolosov, German rhythmic gymnast","url":"https://en.wikipedia.org/wiki/Margarita_Kolosov"},{"year":2003,"text":"Tristan Vukčević, Serbian-Swedish basketball player","url":"https://en.wikipedia.org/wiki/Tristan_Vuk%C4%8Devi%C4%87"},{"year":1997,"text":"Travis Konecny, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Travis_Konecny"},{"year":1997,"text":"Ray Spalding, American basketball player","url":"https://en.wikipedia.org/wiki/Ray_Spalding"},{"year":1996,"text":"Conor Garland, American ice hockey player","url":"https://en.wikipedia.org/wiki/Conor_Garland"},{"year":1994,"text":"Andy Robertson, Scottish footballer","url":"https://en.wikipedia.org/wiki/Andy_Robertson"},{"year":1993,"text":"Jodie Comer, English actress","url":"https://en.wikipedia.org/wiki/Jodie_Comer"},{"year":1993,"text":"Anthony Davis, American basketball player","url":"https://en.wikipedia.org/wiki/Anthony_Davis"}],"deaths":[{"year":2025,"text":"Junior Bridgeman, American basketball player and businessman (born 1953)","url":"https://en.wikipedia.org/wiki/Junior_Bridgeman"},{"year":2025,"text":"Clive Revill, New Zealand actor and singer (born 1930)","url":"https://en.wikipedia.org/wiki/Clive_Revill"},{"year":2024,"text":"Paul Alexander, Polio survivor (born 1946)","url":"https://en.wikipedia.org/wiki/Paul_Alexander_(polio_survivor)"},{"year":2022,"text":"Rupiah Banda, President of Zambia (born 1937)","url":"https://en.wikipedia.org/wiki/Rupiah_Banda"},{"year":2021,"text":"Ray Campi, American singer and musician (born 1934)","url":"https://en.wikipedia.org/wiki/Ray_Campi"},{"year":2021,"text":"Takis Mousafiris, Greek composer and songwriter (born 1936)","url":"https://en.wikipedia.org/wiki/Takis_Mousafiris"},{"year":2018,"text":"Ken Dodd, English comedian and singer (born 1927)","url":"https://en.wikipedia.org/wiki/Ken_Dodd"},{"year":2018,"text":"Siegfried Rauch, German actor (born 1932)","url":"https://en.wikipedia.org/wiki/Siegfried_Rauch"}]},"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."}