{"date":"2026-05-12","schema_version":1,"captured_at":"2026-08-25T23:08:18.587Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"C. Joseph Vijay","views":327967,"rank":3,"extract":"Chandrasekaran Joseph Vijay is an Indian politician and former actor who is currently serving as the ninth chief minister of Tamil Nadu since May 2026. He is the founder and president of the political party Tamilaga Vettri Kazhagam (TVK). Prior to entering pol","url":"https://en.wikipedia.org/wiki/C._Joseph_Vijay","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/d8/JosephVijay.jpg/330px-JosephVijay.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Hantavirus","views":216463,"rank":5,"extract":"Orthohantavirus is a genus of viruses which includes all hantaviruses that cause disease in humans. 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war","points":260,"comments":439,"url":"https://www.bbc.com/news/articles/c202pgxx89lo","discussion":"https://news.ycombinator.com/item?id=48108313"},{"title":"Reimagining the mouse pointer for the AI era","points":252,"comments":213,"url":"https://deepmind.google/blog/ai-pointer/","discussion":"https://news.ycombinator.com/item?id=48111581"},{"title":"Amazon employees are \"tokenmaxxing\" due to pressure to use AI tools","points":251,"comments":253,"url":"https://arstechnica.com/ai/2026/05/amazon-employees-are-tokenmaxxing-due-to-pressure-to-use-ai-tools/","discussion":"https://news.ycombinator.com/item?id=48110529"},{"title":"Kraftwerk's radical 1976 track","points":238,"comments":212,"url":"https://www.bbc.com/culture/article/20260511-kraftwerks-radical-1976-track-radioactivity-became-an-anti-nuclear-anthem","discussion":"https://news.ycombinator.com/item?id=48115823"},{"title":"eBay Rejects GameStop's $56B Takeover as Not Credible","points":237,"comments":239,"url":"https://www.bloomberg.com/news/articles/2026-05-12/ebay-rejects-gamestop-s-56-billion-takeover-as-not-credible","discussion":"https://news.ycombinator.com/item?id=48110021"}],"research":[{"title":"Probability Bracket Notation: Multivariable Systems and Static Bayesian Networks","abstract":"We extend Probability Bracket Notation (PBN), inspired by the Dirac notation in quantum mechanics, to multivariable probability systems and static Bayesian networks (BNs). By defining probability distributions and conditional expectations in a unified, basis-independent algebraic form, PBN provides a systematic way to represent and manipulate dependencies among random variables. Using the well-known Student BN as an ","authors":["Wang, Xing M."],"url":"https://arxiv.org/abs/1207.5293","arxiv_id":"1207.5293","published":"2026-05-12"},{"title":"Provable Exactness for Asymmetric Low-Rank SDP Learning","abstract":"Low-rank factorization is a standard way to make structured optimization problems in machine learning more tractable by replacing matrix variables with compact factors. For positive semidefinite (PSD) variables, the symmetric Burer--Monteiro factorization (sBMF) writes $Z=XX^\\top$ with a single low-rank factor $X$. A recent asymmetric alternative (aBMF) writes $Z=XY^\\top$ and adds a quadratic penalty $(γ/2)\\|X-Y\\|_F^","authors":["Hu, Enliang"],"url":"https://arxiv.org/abs/1811.01198","arxiv_id":"1811.01198","published":"2026-05-12"},{"title":"Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions","abstract":"Existing rigorous convergence guarantees for the Hamiltonian Monte Carlo (HMC) algorithm use Gaussian auxiliary momentum variables, which are crucially symmetrically distributed. We present a novel convergence analysis for HMC utilizing new dynamical and probabilistic arguments. The convergence is rigorously established under significantly weaker conditions, which among others allow for general auxiliary distribution","authors":["Ghosh, Soumyadip","Lu, Yingdong","Nowicki, Tomasz"],"url":"https://arxiv.org/abs/2110.12907","arxiv_id":"2110.12907","published":"2026-05-12"},{"title":"Spectrally Adapted Physics-Informed Neural Networks for Solving Unbounded Domain Problems","abstract":"Solving analytically intractable partial differential equations (PDEs) that involve at least one variable defined on an unbounded domain arises in numerous physical applications. Accurately solving unbounded domain PDEs requires efficient numerical methods that can resolve the dependence of the PDE on the unbounded variable over at least several orders of magnitude. We propose a solution to such problems by combining","authors":["Xia, Mingtao","Böttcher, Lucas","Chou, Tom"],"url":"https://arxiv.org/abs/2202.02710","arxiv_id":"2202.02710","published":"2026-05-12"},{"title":"Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control","abstract":"We study projection-free methods for functional constrained optimization with convex or smooth nonconvex objectives. Such problems arise in applications such as portfolio optimization and radiation therapy planning, where risk-aware criteria and sparsity frequently appear together. For the convex setting, we propose a Level Conditional Gradient (LCG) method that combines a level-set outer loop with a conditional grad","authors":["Cheng, Yi","Lan, Guanghui","Masiha, Saeed","Romeijn, H. Edwin"],"url":"https://arxiv.org/abs/2210.05108","arxiv_id":"2210.05108","published":"2026-05-12"},{"title":"Learning Strategic Value and Cooperation in Multi-Player Stochastic Games through Side Payments","abstract":"We study general-sum, multi-player stochastic games with transferable utility, motivated by settings where agents can use side payments to make cooperation individually rational. Building on the Harsanyi--Shapley (HS) value for normal-form games, we introduce two HS-based value notions for stochastic games: HS-S, defined by aggregating dynamic coalition-versus-complement threat powers, and Coco-S, defined as fixed po","authors":["Chen, Yixin","Richley, Jeffrey","Perez-Lavin, Darleen","Syal, Jessica Singh","Kia, Solmaz","Kuhnle, Alan"],"url":"https://arxiv.org/abs/2303.05307","arxiv_id":"2303.05307","published":"2026-05-12"},{"title":"A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning","abstract":"In general, a similarity threshold (i.e., a vigilance parameter) for a node learning process in Adaptive Resonance Theory (ART)-based algorithms has a significant impact on clustering performance. In addition, an edge deletion threshold in a topological clustering algorithm plays an important role in adaptively generating well-separated clusters during a self-organizing process. In this paper, we propose an ART-based","authors":["Masuyama, Naoki","Takebayashi, Takanori","Nojima, Yusuke","Loo, Chu Kiong","Ishibuchi, Hisao","Wermter, Stefan"],"url":"https://arxiv.org/abs/2305.01507","arxiv_id":"2305.01507","published":"2026-05-12"},{"title":"LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning","abstract":"Fine-tuning large language models (LLMs) is crucial for improving their performance on downstream tasks, but full-parameter fine-tuning (Full-FT) is computationally expensive and memory-intensive. Parameter-efficient fine-tuning (PEFT) methods, such as Low-Rank Adaptation (LoRA), address this by optimizing only a small subset of parameters. However, LoRA may underperform Full-FT in certain scenarios due to the intrin","authors":["Zhang, Longteng","Zhang, Lin","Shi, Shaohuai","Chu, Xiaowen","Li, Bo"],"url":"https://arxiv.org/abs/2308.03303","arxiv_id":"2308.03303","published":"2026-05-12"},{"title":"An Insight into Security Code Review with LLMs: Capabilities, Obstacles, and Influential Factors","abstract":"Security code review is a time-consuming and labor-intensive process typically requiring integration with automated security defect detection tools. However, existing security analysis tools struggle with poor generalization, high false positive rates, and coarse detection granularity. Large Language Models (LLMs) have been considered promising candidates for addressing those challenges. In this study, we conducted a","authors":["Yu, Jiaxin","Liang, Peng","Fu, Yujia","Tahir, Amjed","Shahin, Mojtaba","Wang, Chong"],"url":"https://arxiv.org/abs/2401.16310","arxiv_id":"2401.16310","published":"2026-05-12"},{"title":"Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation","abstract":"U-shaped architectures have long dominated the field of medical image segmentation, while Transformers are widely employed for modeling long-range dependencies. The former typically handles scale variations implicitly by aggregating multi-level features, whereas the efficiency of the latter is constrained by its quadratic computational and memory complexity. In this work, we propose an effective alternative to tradit","authors":["Zhang, Yanhua","Zhang, Ke","Wang, Jingyu","Balestra, Gabriella","Rosati, Samanta","Wu, Yulin"],"url":"https://arxiv.org/abs/2402.02286","arxiv_id":"2402.02286","published":"2026-05-12"},{"title":"FunnelNet: An End-to-End Deep Learning Framework to Monitor Digital Heart Murmur in Real-Time","abstract":"Heart murmurs are abnormal sounds caused by turbulent blood flow in the heart. Several diagnostic methods are available to detect heart murmurs and their severity, including cardiac auscultation, echocardiography, and phonocardiography (PCG). However, these methods have limitations, including the need for extensive training among healthcare providers, the cost and accessibility of echocardiography, and noise interfer","authors":["Jobayer, Md","Shawon, Md. Mehedi Hasan","Hossain, Md Zakir","Ghosh, Shreya","Rudas, Imre","Gedeon, Tom"],"url":"https://arxiv.org/abs/2405.09570","arxiv_id":"2405.09570","published":"2026-05-12"},{"title":"Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions","abstract":"Federated Learning (FL) is a distributed and privacy-preserving machine learning paradigm that coordinates multiple clients to train a model while keeping the raw data localized. However, this traditional FL poses some challenges, including privacy risks, data heterogeneity, communication bottlenecks, and system heterogeneity issues. To tackle these challenges, knowledge distillation (KD) has been widely applied in F","authors":["Qin, Laiqiao","Zhu, Tianqing","Zhou, Wanlei","Yu, Philip S."],"url":"https://arxiv.org/abs/2406.10861","arxiv_id":"2406.10861","published":"2026-05-12"},{"title":"Quasi-Linear ICA for Motor Unit Decomposition during Dynamic Contractions","abstract":"Decomposing surface electromyography (EMG) into the spike trains of individual motor neurons is a long-standing inverse problem and a key step toward motor-neuron-driven neural interfaces such as prosthetics and exoskeletons. The standard approach, independent component analysis (ICA) of the multichannel signal, assumes that the mixing from neurons to electrodes is stationary in time. This assumption fails during mov","authors":["Clarke, Alexander Kenneth","Halatsis, Dimitrios","Grison, Agnese","Guerra, Irene Mendez","Ezaz-Nikpay, Noura","Mamidanna, Pranav"],"url":"https://arxiv.org/abs/2406.19581","arxiv_id":"2406.19581","published":"2026-05-12"},{"title":"Bring Your Own Prompts: Use-Case-Specific Bias and Fairness Evaluation for LLMs","abstract":"Bias and fairness risks in Large Language Models (LLMs) vary substantially across deployment contexts, yet existing approaches lack systematic guidance for selecting appropriate evaluation metrics. We present a decision framework that maps LLM use cases, characterized by a model and population of prompts, to relevant bias and fairness metrics based on task type, whether prompts contain protected attribute mentions, a","authors":["Bouchard, Dylan"],"url":"https://arxiv.org/abs/2407.10853","arxiv_id":"2407.10853","published":"2026-05-12"},{"title":"Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis","abstract":"Generative diffusion models have emerged as a powerful tool for high-quality image synthesis, yet their iterative nature demands significant computational resources. This paper proposes an efficient time step sampling method based on an image spectral analysis of the diffusion process, aimed at optimizing the denoising process. Instead of the traditional uniform distribution-based time step sampling, we introduce a B","authors":["Lee, Haeil","Lee, Hansang","Gye, Seoyeon","Kim, Junmo"],"url":"https://arxiv.org/abs/2407.12173","arxiv_id":"2407.12173","published":"2026-05-12"},{"title":"SINDyG: Sparse Identification of Nonlinear Dynamical Systems from Graph-Structured Data, with Applications to Stuart-Landau Oscillator Networks","abstract":"The combination of machine learning (ML) and sparsity-promoting techniques is enabling direct extraction of governing equations from data, revolutionizing computational modeling in diverse fields of science and engineering. The discovered dynamical models could be used to address challenges in climate science, neuroscience, ecology, finance, epidemiology, and beyond. However, most existing sparse identification metho","authors":["Basiri, Mohammad Amin","Khanmohammadi, Sina"],"url":"https://arxiv.org/abs/2409.04463","arxiv_id":"2409.04463","published":"2026-05-12"},{"title":"Efficient Statistics With Unknown Truncation, Polynomial Time Algorithms, Beyond Gaussians","abstract":"We study the estimation of distributional parameters when samples are shown only if they fall in some unknown set $S \\subseteq \\mathbb{R}^d$. Kontonis, Tzamos, and Zampetakis (FOCS'19) gave a $d^{\\mathrm{poly}(1/\\varepsilon)}$ time algorithm for finding $\\varepsilon$-accurate parameters for the special case of Gaussian distributions with diagonal covariance matrix. Recently, Diakonikolas, Kane, Pittas, and Zarifi","authors":["Lee, Jane H.","Mehrotra, Anay","Zampetakis, Manolis"],"url":"https://arxiv.org/abs/2410.01656","arxiv_id":"2410.01656","published":"2026-05-12"},{"title":"Diffusion Models are Evolutionary Algorithms","abstract":"In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms. By considering evolution as a denoising process and reversed evolution as diffusion, we mathematically demonstrate that diffusion models inherently perform evolutionary algorithms, naturally encompassing selection, mutation, and reproductive isolation. Building on this equivalence, we propose the Diffusion E","authors":["Zhang, Yanbo","Hartl, Benedikt","Hazan, Hananel","Levin, Michael"],"url":"https://arxiv.org/abs/2410.02543","arxiv_id":"2410.02543","published":"2026-05-12"},{"title":"Language Conditioned Multi-Finger Dexterous Manipulation Enabled by Physical Compliance and Switching of Controllers","abstract":"Human dexterity arises from combining high-level task reasoning with finger-level dexterity control and physical compliance at the muscle and skin layers. In robotics, large Vision-Language-Action (VLA) models demonstrate text-conditioned high-level planning across diverse manipulation tasks, typically using pincher grippers. Smaller imitation-learning policies, conversely, show success in dexterous tasks using highe","authors":["Pan, Cheng","Junge, Kai","Dai, Benhui","Guan, Qinghua","Hughes, Josie"],"url":"https://arxiv.org/abs/2410.14022","arxiv_id":"2410.14022","published":"2026-05-12"},{"title":"Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA","abstract":"Machine unlearning is an emerging technology that removes a subset of the training data from a trained model without significantly affecting the model performance on the remaining data. This topic is becoming increasingly important in protecting user privacy and eliminating harmful or outdated data. The key challenge lies in effectively and efficiently unlearning specific information without compromising the model&#3","authors":["Qin, Laiqiao","Zhu, Tianqing","Wang, Linlin","Zhou, Wanlei"],"url":"https://arxiv.org/abs/2411.08443","arxiv_id":"2411.08443","published":"2026-05-12"},{"title":"Topological Data Analysis Applications in Natural Language Processing: A Survey","abstract":"The surge of data available on the Internet has driven the adoption of a wide range of computational methods for analyzing and extracting insights from large-scale data. Among these, Machine Learning (ML) has become a central paradigm, offering powerful tools for pattern discovery, prediction, and representation learning across many domains. At the same time, real-world data often exhibit properties such as noise, im","authors":["Uchendu, Adaku","Le, Thai"],"url":"https://arxiv.org/abs/2411.10298","arxiv_id":"2411.10298","published":"2026-05-12"},{"title":"Implicit Neural Compression of Point Clouds","abstract":"Point clouds have gained prominence across numerous applications due to their ability to accurately represent 3D objects and scenes. However, efficiently compressing unstructured, high-precision point cloud data remains a significant challenge. In this paper, we propose NeRC$^3$, a novel point cloud compression framework that leverages implicit neural representations (INRs) to encode both geometry and attributes of d","authors":["Ruan, Hongning","Shao, Yulin","Yang, Qianqian","Zhao, Liang","Zhang, Zhaoyang","Niyato, Dusit"],"url":"https://arxiv.org/abs/2412.10433","arxiv_id":"2412.10433","published":"2026-05-12"},{"title":"Turbo-GS: Accelerating 3D Gaussian Fitting for High-Quality Radiance Fields","abstract":"Novel-view synthesis plays a crucial role in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent approaches, such as 3D Gaussian Splatting (3DGS), have emerged as state-of-the-art solutions, offering high-quality novel view synthesis in real time. However, training 3DGS models remains slow, particularly for high-resolution images, often requiring hours to fit a scene with 200 v","authors":["Dhiman, Ankit","Lu, Tao","Srinath, R","Arslan, Emre","Xing, Angela","Xiangli, Yuanbo"],"url":"https://arxiv.org/abs/2412.13547","arxiv_id":"2412.13547","published":"2026-05-12"},{"title":"Ister: Linear Transformer for Efficient Multivariate Time Series Forecasting","abstract":"Transformer-based models have achieved remarkable success in multivariate time series forecasting (MTSF) by capturing long-range dependencies. However, their widespread adoption is hindered by the quadratic computational complexity of self-attention, which limits scalability on high-dimensional sequences. To address this challenge, we propose the Inverted Seasonal-Trend Decomposition Transformer (Ister), a novel arch","authors":["Cao, Fanpu","Yang, Shu","Chen, Zhengjian","Liu, Ye","Cui, Laizhong"],"url":"https://arxiv.org/abs/2412.18798","arxiv_id":"2412.18798","published":"2026-05-12"},{"title":"PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models","abstract":"Recent text-to-image (T2I) models have exhibited remarkable performance in generating high-quality images from text descriptions. However, these models are vulnerable to misuse, particularly generating not-safe-for-work (NSFW) content, such as sexually explicit, violent, political, and disturbing images, raising serious ethical concerns. In this work, we present PromptGuard, a novel content moderation technique that ","authors":["Yuan, Lingzhi","Li, Xinfeng","Xu, Chejian","Tao, Guanhong","Jia, Xiaojun","Huang, Yihao"],"url":"https://arxiv.org/abs/2501.03544","arxiv_id":"2501.03544","published":"2026-05-12"}],"history":{"events":[{"year":2022,"text":"The Event Horizon Telescope released the first image of Sagittarius A*.","url":"https://en.wikipedia.org/wiki/Event_Horizon_Telescope"},{"year":2017,"text":"The WannaCry ransomware attack affected more than 400,000 computers worldwide, including systems used by the National Health Service and Telefónica.","url":"https://en.wikipedia.org/wiki/WannaCry_ransomware_attack"},{"year":2015,"text":"An earthquake in Nepal killed 218 people and injured more than 3,500 others.","url":"https://en.wikipedia.org/wiki/May_2015_Nepal_earthquake"},{"year":2015,"text":"A train derailment killed eight people and injured more than 200 others in Philadelphia.","url":"https://en.wikipedia.org/wiki/2015_Philadelphia_train_derailment"},{"year":2010,"text":"On arrival at Tripoli International Airport, Afriqiyah Airways Flight 771 crashed into the ground at a speed of 262 kn (485 km/h; 302 mph) and exploded, killing all but one of the 304 people on board.","url":"https://en.wikipedia.org/wiki/Tripoli_International_Airport"},{"year":2008,"text":"In Postville, Iowa, U.S. Immigration and Customs Enforcement conducted the largest-ever raid of a workplace and arrested nearly 400 immigrants for identity theft and document fraud.","url":"https://en.wikipedia.org/wiki/Postville%2C_Iowa"},{"year":1998,"text":"Four students were shot and killed by Indonesian soldiers at Trisakti University in Jakarta, which led to widespread riots and the resignation of President Suharto nine days later.","url":"https://en.wikipedia.org/wiki/Trisakti_shootings"},{"year":1982,"text":"The Coppergate Helmet (pictured), the best preserved of the six known Anglo-Saxon helmets, was discovered.","url":"https://en.wikipedia.org/wiki/Coppergate_Helmet"},{"year":1982,"text":"Juan María Fernández y Krohn attempted to assassinate Pope John Paul II with a bayonet in Fátima, Portugal.","url":"https://en.wikipedia.org/wiki/Juan_Mar%C3%ADa_Fern%C3%A1ndez_y_Krohn"},{"year":1975,"text":"The Cambodian navy seized the American container ship SS Mayaguez in what they claimed to be Cambodian territorial waters.","url":"https://en.wikipedia.org/wiki/Mayaguez_incident"},{"year":1968,"text":"Vietnam War: The 1st Australian Task Force began the defence of Fire Support Base Coral in the largest unit-level action of the war for the Australian Army.","url":"https://en.wikipedia.org/wiki/Vietnam_War"},{"year":1967,"text":"The Jimi Hendrix Experience released the critically acclaimed and widely influential debut album Are You Experienced.","url":"https://en.wikipedia.org/wiki/Jimi_Hendrix"},{"year":1948,"text":"The United Kingdom publicly announced that it was independently developing nuclear weapons, after the US Atomic Energy Act of 1946 ended cooperation on the matter.","url":"https://en.wikipedia.org/wiki/High_Explosive_Research"},{"year":1941,"text":"German engineer Konrad Zuse presented the Z3, the first working programmable and fully automatic computer, to an audience of scientists in Berlin.","url":"https://en.wikipedia.org/wiki/Konrad_Zuse"},{"year":1938,"text":"During an exercise to demonstrate air power, United States Army Air Corps bomber aircraft intercepted the Italian ocean liner SS Rex (pictured) 620 nautical miles (1,100 km) off the US Atlantic coast.","url":"https://en.wikipedia.org/wiki/United_States_Army_Air_Corps"},{"year":1932,"text":"Nazi deputies assaulted journalist Helmuth Klotz in the German parliament building after he publicized the homosexuality of a senior Nazi politician.","url":"https://en.wikipedia.org/wiki/R%C3%B6hm_scandal"},{"year":1926,"text":"The crew of the airship Norge (pictured), led by Roald Amundsen, became the first people to make a verified trip to the North Pole.","url":"https://en.wikipedia.org/wiki/Norge_(airship)"},{"year":1888,"text":"North Borneo was established as a British protectorate.","url":"https://en.wikipedia.org/wiki/North_Borneo"}],"births":[{"year":2006,"text":"Vasilije Adžić, Montenegrin footballer","url":"https://en.wikipedia.org/wiki/Vasilije_Ad%C5%BEi%C4%87"},{"year":2005,"text":"Zach Benson, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Zach_Benson"},{"year":2001,"text":"Issa Kaboré, Burkinabé footballer","url":"https://en.wikipedia.org/wiki/Issa_Kabor%C3%A9"},{"year":1999,"text":"Hiroki Itō, Japanese footballer","url":"https://en.wikipedia.org/wiki/Hiroki_It%C5%8D_(footballer%2C_born_1999)"},{"year":1998,"text":"Mo Bamba, American-Ivorian basketball player","url":"https://en.wikipedia.org/wiki/Mo_Bamba"},{"year":1997,"text":"Frenkie de Jong, Dutch footballer","url":"https://en.wikipedia.org/wiki/Frenkie_de_Jong"},{"year":1996,"text":"Fabrice Olinga, Cameroonian footballer","url":"https://en.wikipedia.org/wiki/Fabrice_Olinga"},{"year":1996,"text":"Kostas Tsimikas, Greek footballer","url":"https://en.wikipedia.org/wiki/Kostas_Tsimikas"}],"deaths":[{"year":2026,"text":"Jason Collins, American basketball player (born 1978)","url":"https://en.wikipedia.org/wiki/Jason_Collins"},{"year":2024,"text":"Mark Damon, American film actor and producer (born 1933)","url":"https://en.wikipedia.org/wiki/Mark_Damon"},{"year":2024,"text":"David Sanborn, American saxophonist (born 1945)","url":"https://en.wikipedia.org/wiki/David_Sanborn"},{"year":2024,"text":"A. J. Smith, American football executive (born 1949)","url":"https://en.wikipedia.org/wiki/A._J._Smith"},{"year":2020,"text":"Aimee Stephens, American funeral director and U.S. Supreme Court litigant (born 1960)","url":"https://en.wikipedia.org/wiki/Aimee_Stephens"},{"year":2018,"text":"Dennis Nilsen, Scottish serial killer (born 1945)","url":"https://en.wikipedia.org/wiki/Dennis_Nilsen"},{"year":2017,"text":"Mauno Koivisto, Finnish banker and politician, ninth President of Finland (born 1923)","url":"https://en.wikipedia.org/wiki/Mauno_Koivisto"},{"year":2016,"text":"Mike Agostini, Trinidadian sprinter (born 1935)","url":"https://en.wikipedia.org/wiki/Mike_Agostini"}]},"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."}