{"date":"2025-12-16","schema_version":1,"captured_at":"2026-08-25T23:05:05.724Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Rob Reiner","views":7784573,"rank":1,"extract":"Robert Reiner was an American filmmaker, actor, and political activist. He directed a series of acclaimed studio films in a career that spanned comedy, drama, romance, and documentary. Reiner received numerous accolades, including winning two Primetime Emmy Aw","url":"https://en.wikipedia.org/wiki/Rob_Reiner","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/8/89/Rob_Reiner_in_2016_%283x4_cropped%29.jpg/330px-Rob_Reiner_in_2016_%283x4_cropped%29.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Tracy Reiner","views":1073375,"rank":3,"extract":"Tracy Reiner is an American former actress. 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hours","points":278,"comments":145,"url":"https://simonwillison.net/2025/Dec/15/porting-justhtml/","discussion":"https://news.ycombinator.com/item?id=46295771"},{"title":"Japan to revise romanization rules for first time in 70 years","points":273,"comments":230,"url":"https://www.japantimes.co.jp/news/2025/08/21/japan/panel-hepburn-style-romanization/","discussion":"https://news.ycombinator.com/item?id=46286292"}],"research":[{"title":"The Optimal Approximation Factor in Density Estimation","abstract":"Consider the following problem: given two arbitrary densities $q_1,q_2$ and a sample-access to an unknown target density $p$, find which of the $q_i$'s is closer to $p$ in total variation. A remarkable result due to Yatracos shows that this problem is tractable in the following sense: there exists an algorithm that uses $O(ε^{-2})$ samples from $p$ and outputs~$q_i$ such that with high probability, $TV(q_i,p) \\le","authors":["Bousquet, Olivier","Kane, Daniel","Moran, Shay"],"url":"https://arxiv.org/abs/1902.05876","arxiv_id":"1902.05876","published":"2025-12-16"},{"title":"Adaptive Risk Mitigation in Demand Learning","abstract":"We study dynamic pricing of a product with an unknown demand distribution over a finite horizon. Departing from the standard no-regret learning environment in which prices can be adjusted at any time, we restrict price changes to predetermined points in time to reflect common retail practice. This constraint, coupled with demand model ambiguity and an unknown customer arrival pattern, imposes a high risk of revenue l","authors":["Pakiman, Parshan","Chen, Boxiao","Nadarajah, Selvaprabu","Jasin, Stefanus"],"url":"https://arxiv.org/abs/2011.10690","arxiv_id":"2011.10690","published":"2025-12-16"},{"title":"We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature","abstract":"Recently, object detection has proven vulnerable to adversarial patch attacks. The attackers holding a specially crafted patch can hide themselves from state-of-the-art detectors, e.g., YOLO, even in the physical world. This attack can bring serious security threats, such as escaping from surveillance cameras. How to effectively detect this kind of adversarial examples to catch potential attacks has become an importa","authors":["Li, Jiachun","Feng, Jianan","Huang, Jianjun","Liang, Bin"],"url":"https://arxiv.org/abs/2106.05261","arxiv_id":"2106.05261","published":"2025-12-16"},{"title":"Comparing concepts of quantum and classical neural network models for image classification task","abstract":"While quantum architectures are still under development, when available, they will only be able to process quantum data when machine learning algorithms can only process numerical data. Therefore, in the issues of classification or regression, it is necessary to simulate and study quantum systems that will transfer the numerical input data to a quantum form and enable quantum computers to use the available methods of","authors":["Potempa, Rafal","Porebski, Sebastian"],"url":"https://arxiv.org/abs/2108.08875","arxiv_id":"2108.08875","published":"2025-12-16"},{"title":"CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer","abstract":"Interval and large invasive breast cancers, which are associated with worse prognosis than other cancers, are usually detected at a late stage due to false negative assessments of screening mammograms. The missed screening-time detection is commonly caused by the tumor being obscured by its surrounding breast tissues, a phenomenon called masking. To study and benchmark mammographic masking of cancer, in this work we ","authors":["Sorkhei, Moein","Liu, Yue","Azizpour, Hossein","Azavedo, Edward","Dembrower, Karin","Ntoula, Dimitra"],"url":"https://arxiv.org/abs/2112.01330","arxiv_id":"2112.01330","published":"2025-12-16"},{"title":"TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression","abstract":"The tree-based ensembles are known for their outstanding performance in classification and regression problems characterized by feature vectors represented by mixed-type variables from various ranges and domains. However, considering regression problems, they are primarily designed to provide deterministic responses or model the uncertainty of the output with Gaussian or parametric distribution. In this work, we intr","authors":["Wielopolski, Patryk","Zięba, Maciej"],"url":"https://arxiv.org/abs/2206.04140","arxiv_id":"2206.04140","published":"2025-12-16"},{"title":"The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks","abstract":"In the logic synthesis stage, structure transformations in the synthesis tool need to be combined into optimization sequences and act on the circuit to meet the specified circuit area and delay. However, logic synthesis optimization sequences are time-consuming to run, and predicting the quality of the results (QoR) against the synthesis optimization sequence for a circuit can help engineers find a better optimizatio","authors":["Yang, Chenghao","Wang, Zhongda","Xia, Yinshui","Chu, Zhufei"],"url":"https://arxiv.org/abs/2207.11437","arxiv_id":"2207.11437","published":"2025-12-16"},{"title":"Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach","abstract":"In this paper we present a neurosymbolic architecture for coupling language-guided visual reasoning with robot manipulation. A non-expert human user can prompt the robot using unconstrained natural language, providing a referring expression (REF), a question (VQA), or a grasp action instruction. The system tackles all cases in a task-agnostic fashion through the utilization of a shared library of primitive skills. Ea","authors":["Tziafas, Georgios","Kasaei, Hamidreza"],"url":"https://arxiv.org/abs/2210.00858","arxiv_id":"2210.00858","published":"2025-12-16"},{"title":"ExReg: Wide-range Photo Exposure Correction via a Multi-dimensional Regressor with Attention","abstract":"Photo exposure correction is widely investigated, but fewer studies focus on correcting under- and over-exposed images simultaneously. Three issues remain open to handle and correct both under- and over-exposed images in a unified way. First, a locally-adaptive exposure adjustment may be more flexible instead of learning a global mapping. Second, it is an ill-posed problem to determine the suitable exposure values lo","authors":["Do, Huu-Phu","Hsueh, Hao-Chien","Chiang, Tzu-Hao","Chen, Chi-Han","Peng, Wen-Hsiao","Huang, Ching-Chun"],"url":"https://arxiv.org/abs/2212.14801","arxiv_id":"2212.14801","published":"2025-12-16"},{"title":"A Survey on Uncertainty Quantification Methods for Deep Learning","abstract":"Deep neural networks (DNNs) have achieved tremendous success in computer vision, natural language processing, and scientific and engineering domains. However, DNNs can make unexpected, incorrect, yet overconfident predictions, leading to serious consequences in high-stakes applications such as autonomous driving, medical diagnosis, and disaster response. Uncertainty quantification (UQ) estimates the confidence of DNN","authors":["He, Wenchong","Jiang, Zhe","Xiao, Tingsong","Xu, Zelin","Li, Yukun"],"url":"https://arxiv.org/abs/2302.13425","arxiv_id":"2302.13425","published":"2025-12-16"},{"title":"WCCNet: Wavelet-context Cooperative Network for Efficient Multispectral Pedestrian Detection","abstract":"Multispectral pedestrian detection is essential to various tasks especially autonomous driving, for which both the accuracy and computational cost are of paramount importance. Most existing approaches treat RGB and infrared modalities equally. They typically adopt two symmetrical backbones for multimodal feature extraction, which ignore the substantial differences between modalities and bring great difficulty for the","authors":["Wang, Xingjian","Chai, Li","Chen, Jiming","Shi, Zhiguo"],"url":"https://arxiv.org/abs/2308.01042","arxiv_id":"2308.01042","published":"2025-12-16"},{"title":"Learning NEAT Emergent Behaviors in Robot Swarms","abstract":"When researching robot swarms, many studies observe complex group behavior emerging from the individual agents' simple local actions. However, the task of learning an individual policy to produce a desired group behavior remains a challenging problem. We present a method of training distributed robotic swarm algorithms to produce emergent behavior. Inspired by the biological evolution of emergent behavior in anim","authors":["Rajbhandari, Pranav","Sofge, Donald"],"url":"https://arxiv.org/abs/2309.14663","arxiv_id":"2309.14663","published":"2025-12-16"},{"title":"A Neural-preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions","abstract":"We introduce a neural-preconditioned iterative solver for Poisson equations with mixed boundary conditions. Typical Poisson discretizations yield large, ill-conditioned linear systems. Iterative solvers can be effective for these problems, but only when equipped with powerful preconditioners. Unfortunately, effective preconditioners like multigrid require costly setup phases that must be re-executed every time domain","authors":["Lan, Kai Weixian","Gueidon, Elias","Kaneda, Ayano","Panetta, Julian","Teran, Joseph"],"url":"https://arxiv.org/abs/2310.00177","arxiv_id":"2310.00177","published":"2025-12-16"},{"title":"Physics-informed neural network for modeling dynamic linear elasticity","abstract":"In this work, we present the physics-informed neural network (PINN) model applied particularly to dynamic problems in solid mechanics. We focus on forward and inverse problems. Particularly, we show how a PINN model can be used efficiently for material identification in a dynamic setting. In this work, we assume linear continuum elasticity. We show results for two-dimensional (2D) plane strain problem and then we pro","authors":["Kag, Vijay","Gopinath, Venkatesh"],"url":"https://arxiv.org/abs/2312.15175","arxiv_id":"2312.15175","published":"2025-12-16"},{"title":"IRG: Modular Synthetic Relational Database Generation with Complex Relational Schemas","abstract":"Relational databases (RDBs) are widely used by corporations and governments to store multiple related tables. Their relational schemas pose unique challenges to synthetic data generation for privacy-preserving data sharing, e.g., for collaborative analytical and data mining tasks, as well as software testing at various scales. Relational schemas typically include a set of primary and foreign key constraints to specif","authors":["Li, Jiayu","Zhao, Zilong","Abdollahzadeh, Milad","Sikdar, Biplab","Tay, Y. C."],"url":"https://arxiv.org/abs/2312.15187","arxiv_id":"2312.15187","published":"2025-12-16"},{"title":"PADS: Plug-and-Play 3D Human Pose Analysis via Diffusion Generative Modeling","abstract":"Diffusion models have demonstrated impressive capabilities in modeling complex data distributions and are increasingly applied in various generative tasks. In this work, we propose Pose Analysis by Diffusion Synthesis PADS, a unified generative modeling framework for 3D human pose analysis. PADS first learns a task-agnostic 3D pose prior via unconditional diffusion synthesis and then performs training-free adaptation","authors":["Ji, Haorui","Li, Hongdong"],"url":"https://arxiv.org/abs/2401.08930","arxiv_id":"2401.08930","published":"2025-12-16"},{"title":"&#34;All of Me&#34;: Mining Users' Attributes from their Public Spotify Playlists","abstract":"In the age of digital music streaming, playlists on platforms like Spotify have become an integral part of individuals' musical experiences. People create and publicly share their own playlists to express their musical tastes, promote the discovery of their favorite artists, and foster social connections. In this work, we aim to address the question: can we infer users' private attributes from their public Sp","authors":["Tricomi, Pier Paolo","Pajola, Luca","Pasa, Luca","Conti, Mauro"],"url":"https://arxiv.org/abs/2401.14296","arxiv_id":"2401.14296","published":"2025-12-16"},{"title":"Foveated Retinotopy Improves Classification and Localization in Convolutional Neural Networks","abstract":"From falcons spotting preys to humans recognizing faces, rapid visual abilities depend on a foveated retinal organization which delivers high-acuity central vision while preserving low-resolution periphery. This organization is conserved along early visual pathways but remains underexplored in machine learning. Here we examine how embedding a foveated retinotopic transformation as a preprocessing layer impacts convol","authors":["Jérémie, Jean-Nicolas","Daucé, Emmanuel","Perrinet, Laurent U"],"url":"https://arxiv.org/abs/2402.15480","arxiv_id":"2402.15480","published":"2025-12-16"},{"title":"An Efficient and Harmonized Framework for Balanced Cross-Domain Feature Integration","abstract":"Despite significant advancements in image generation using advanced generative frameworks, cross-image integration of content and style remains a key challenge. Current generative models, while powerful, frequently depend on vague textual prompts to define styles--creating difficulties in balancing content semantics and style preservation. We propose a novel framework that utilizes customized models to learn style re","authors":["Li, Shaoxu","Pan, Ye"],"url":"https://arxiv.org/abs/2403.18461","arxiv_id":"2403.18461","published":"2025-12-16"},{"title":"A Comprehensive Survey on Self-Supervised Learning for Recommendation","abstract":"Recommender systems play a crucial role in tackling the challenge of information overload by delivering personalized recommendations based on individual user preferences. Deep learning techniques, such as RNNs, GNNs, and Transformer architectures, have significantly propelled the advancement of recommender systems by enhancing their comprehension of user behaviors and preferences. However, supervised learning methods","authors":["Ren, Xubin","Wei, Wei","Xia, Lianghao","Huang, Chao"],"url":"https://arxiv.org/abs/2404.03354","arxiv_id":"2404.03354","published":"2025-12-16"},{"title":"Counterfactual Explanations for Deep Learning-Based Traffic Forecasting","abstract":"Deep learning models are widely used in traffic forecasting and have achieved state-of-the-art prediction accuracy. However, the black-box nature of those models makes the results difficult to interpret by users. This study aims to leverage an Explainable AI approach, counterfactual explanations, to enhance the explainability and usability of deep learning-based traffic forecasting models. Specifically, the goal is t","authors":["Wang, Rushan","Xin, Yanan","Zhang, Yatao","Perez-Cruz, Fernando","Raubal, Martin"],"url":"https://arxiv.org/abs/2405.00456","arxiv_id":"2405.00456","published":"2025-12-16"},{"title":"Fast Wrong-way Cycling Detection in CCTV Videos: Sparse Sampling is All You Need","abstract":"Effective monitoring of unusual transportation behaviors, such as wrong-way cycling (i.e., riding a bicycle or e-bike against designated traffic flow), is crucial for optimizing law enforcement deployment and traffic planning. However, accurately recording all wrong-way cycling events is both unnecessary and infeasible in resource-constrained environments, as it requires high-resolution cameras for evidence collectio","authors":["Xu, Jing","Shi, Wentao","Ren, Sheng","Zhang, Lijuan","Yang, Weikai","Gao, Pan"],"url":"https://arxiv.org/abs/2405.07293","arxiv_id":"2405.07293","published":"2025-12-16"},{"title":"Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation","abstract":"Graph convolutional neural networks (GCNs) are powerful tools for learning graph-based knowledge representations from training data. However, they are vulnerable to small perturbations in the input graph, which makes them susceptible to input faults or adversarial attacks. This poses a significant problem for GCNs intended to be used in critical applications, which need to provide certifiably robust services even in ","authors":["Chen, Boqi","Marussy, Kristóf","Semeráth, Oszkár","Mussbacher, Gunter","Varró, Dániel"],"url":"https://arxiv.org/abs/2405.08645","arxiv_id":"2405.08645","published":"2025-12-16"},{"title":"Tau Anomaly Detection in PET Imaging via Bilateral-Guided Deterministic Diffusion Model","abstract":"The emergence of tau PET imaging over the last decade has enabled Alzheimer's disease (AD) researchers to examine tau pathology in vivo and more effectively characterize the disease trajectories of AD. Current tau PET analysis methods, however, typically perform inferences on large cortical ROIs and are limited in the detection of localized tau pathology that varies across subjects. In this work, we propose a nov","authors":["Zhong, Lujia","Huang, Shuo","Yue, Jiaxin","Zhang, Jianwei","Deng, Zhiwei","Chi, Wenhao"],"url":"https://arxiv.org/abs/2405.13199","arxiv_id":"2405.13199","published":"2025-12-16"},{"title":"Probabilistically Plausible Counterfactual Explanations with Normalizing Flows","abstract":"We present PPCEF, a novel method for generating probabilistically plausible counterfactual explanations (CFs). PPCEF advances beyond existing methods by combining a probabilistic formulation that leverages the data distribution with the optimization of plausibility within a unified framework. Compared to reference approaches, our method enforces plausibility by directly optimizing the explicit density function withou","authors":["Wielopolski, Patryk","Furman, Oleksii","Stefanowski, Jerzy","Zięba, Maciej"],"url":"https://arxiv.org/abs/2405.17640","arxiv_id":"2405.17640","published":"2025-12-16"}],"history":{"events":[{"year":2014,"text":"A hostage crisis in a Lindt chocolate café in Sydney, Australia, ended with police storming the building, killing the perpetrator and one of the hostages.","url":"https://en.wikipedia.org/wiki/Lindt_Cafe_siege"},{"year":2012,"text":"A woman was gang-raped and fatally assaulted on a bus in Delhi, generating protests across India against inadequate security for women.","url":"https://en.wikipedia.org/wiki/2012_Delhi_gang_rape_and_murder"},{"year":1997,"text":"Amid an outbreak of bovine spongiform encephalopathy, the British government banned the sale of beef on the bone for human consumption.","url":"https://en.wikipedia.org/wiki/United_Kingdom_BSE_outbreak"},{"year":1997,"text":"\"Dennō Senshi Porygon\", an episode of the Japanese television series Pokémon, induced epileptic seizures in 685 children.","url":"https://en.wikipedia.org/wiki/Denn%C5%8D_Senshi_Porygon"},{"year":1971,"text":"The surrender of Pakistani forces in Dacca, East Pakistan, concluded the Bangladesh Liberation War and the India-Pakistan War.","url":"https://en.wikipedia.org/wiki/Pakistan"},{"year":1938,"text":"Adolf Hitler instituted the Cross of Honour of the German Mother, an order of merit for German mothers with at least four children.","url":"https://en.wikipedia.org/wiki/Adolf_Hitler"},{"year":1930,"text":"German-American gangster Herman Lamm killed himself during a botched robbery attempt in Clinton, Indiana, to avoid being captured by police.","url":"https://en.wikipedia.org/wiki/Herman_Lamm"},{"year":1922,"text":"Gabriel Narutowicz (pictured), the first president of Poland, was assassinated only five days after having taken office.","url":"https://en.wikipedia.org/wiki/Gabriel_Narutowicz"},{"year":1920,"text":"A magnitude-7.9 earthquake struck Haiyuan County, China, killing more than 250,000 people.","url":"https://en.wikipedia.org/wiki/1920_Haiyuan_earthquake"},{"year":1918,"text":"Vincas Mickevičius-Kapsukas declared the formation of the Lithuanian Soviet Socialist Republic, a puppet state created by Soviet Russia to justify the Lithuanian–Soviet War.","url":"https://en.wikipedia.org/wiki/Vincas_Mickevi%C4%8Dius-Kapsukas"},{"year":1914,"text":"First World War: The Imperial German Navy attacked ports in northern England, resulting in hundreds of civilian casualties.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1901,"text":"English writer Beatrix Potter privately published 250 copies of The Tale of Peter Rabbit (illustration shown) after several publishers' rejections.","url":"https://en.wikipedia.org/wiki/Beatrix_Potter"},{"year":1899,"text":"Thousand Days' War: Columbian Liberal rebels repelled a Conservative government attack at the Battle of Peralonso.","url":"https://en.wikipedia.org/wiki/Thousand_Days'_War"},{"year":1893,"text":"Czech composer Antonín Dvořák's New World Symphony (audio featured) premiered at Carnegie Hall in New York City.","url":"https://en.wikipedia.org/wiki/Anton%C3%ADn_Dvo%C5%99%C3%A1k"},{"year":1850,"text":"Settlers of the Canterbury Association aboard Randolph and Charlotte Jane arrived to establish a colony at Christchurch, New Zealand.","url":"https://en.wikipedia.org/wiki/Canterbury_Association"},{"year":1811,"text":"The first two in a series of four severe earthquakes struck the Midwestern United States and made the Mississippi River appear to run backward.","url":"https://en.wikipedia.org/wiki/1811%E2%80%931812_New_Madrid_earthquakes"},{"year":1773,"text":"American Revolution: A group of colonists threw chests of tea into Boston Harbor (pictured) to protest British taxation without representation.","url":"https://en.wikipedia.org/wiki/American_Revolution"},{"year":1761,"text":"Seven Years' War: After a four-month siege, Russian forces captured Kolberg, the last major Prussian port on the Baltic Sea.","url":"https://en.wikipedia.org/wiki/Seven_Years'_War"}],"births":[{"year":2001,"text":"Kai Cenat, American streamer","url":"https://en.wikipedia.org/wiki/Kai_Cenat"},{"year":1998,"text":"Mira Antonitsch, Austrian tennis player","url":"https://en.wikipedia.org/wiki/Mira_Antonitsch"},{"year":1998,"text":"Zhou Jieqiong, Chinese singer and actress","url":"https://en.wikipedia.org/wiki/Zhou_Jieqiong"},{"year":1997,"text":"Zara Larsson, Swedish singer and songwriter","url":"https://en.wikipedia.org/wiki/Zara_Larsson"},{"year":1996,"text":"Wilfred Ndidi, Nigerian footballer","url":"https://en.wikipedia.org/wiki/Wilfred_Ndidi"},{"year":1996,"text":"Sergio Reguilón, Spanish footballer","url":"https://en.wikipedia.org/wiki/Sergio_Reguil%C3%B3n"},{"year":1996,"text":"Henry Thornton, Australian cricketer","url":"https://en.wikipedia.org/wiki/Henry_Thornton_(cricketer)"},{"year":1994,"text":"Nigel Hayes, American basketball player","url":"https://en.wikipedia.org/wiki/Nigel_Hayes-Davis"}],"deaths":[{"year":2025,"text":"Lusanda Dumke, South African professional rugby union player who played as a flanker (born 1996)","url":"https://en.wikipedia.org/wiki/Lusanda_Dumke"},{"year":2024,"text":"Dick Van Arsdale, American basketball player (born 1943)","url":"https://en.wikipedia.org/wiki/Dick_Van_Arsdale"},{"year":2024,"text":"Tulsi Gowda, Indian environmentalist (born 1937/1938)","url":"https://en.wikipedia.org/wiki/Tulsi_Gowda"},{"year":2023,"text":"Nawaf Al-Ahmad Al-Jaber Al-Sabah, Emir of Kuwait (born 1937)","url":"https://en.wikipedia.org/wiki/Nawaf_Al-Ahmad_Al-Jaber_Al-Sabah"},{"year":2017,"text":"Keely Smith, American singer and actress (born 1928)","url":"https://en.wikipedia.org/wiki/Keely_Smith"},{"year":2015,"text":"Peter Dickinson, Rhodesian-English author and poet (born 1927)","url":"https://en.wikipedia.org/wiki/Peter_Dickinson"},{"year":2015,"text":"Lizmark, Mexican wrestler (born 1950)","url":"https://en.wikipedia.org/wiki/Lizmark"},{"year":2015,"text":"George Earl Ortman, American painter and sculptor (born 1926)","url":"https://en.wikipedia.org/wiki/George_Earl_Ortman"}]},"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."}