{"date":"2025-11-08","schema_version":1,"captured_at":"2026-08-25T22:55:44.501Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":17},"attention":[{"title":"Zohran Mamdani","views":704212,"rank":4,"extract":"Zohran Kwame Mamdani is an American politician who has served since 2026 as the 112th mayor of New York City. A member of the Democratic Party and the Democratic Socialists of America, he represented the 36th district in the New York State Assembly from 2021 t","url":"https://en.wikipedia.org/wiki/Zohran_Mamdani","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/5/59/Zohran_Mamdani_05.25.25_%28b%29_%28cropped%29.jpg/330px-Zohran_Mamdani_05.25.25_%28b%29_%28cropped%29.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Google Chrome","views":335359,"rank":5,"extract":"Google Chrome is a cross-platform web browser developed by Google. 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The votes were counted and the results were declared on 16 May 2025.","url":"https://en.wikipedia.org/wiki/2025_Bihar_Legislative_Assembly_election","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Deputy_CM_Samrat_Chaudhary_congratulating_Nitish_Kumar_on_his_birthday_%28cropped%29.jpg/330px-Deputy_CM_Samrat_Chaudhary_congratulating_Nitish_Kumar_on_his_birthday_%28cropped%29.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Lio Tipton","views":89511,"rank":33,"extract":"Lio Tipton is an American actor and fashion model. 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AI","points":156,"comments":208,"url":"https://gizmodo.com/1-trillion-in-tech-stocks-sold-off-as-market-grows-skeptical-of-ai-2000683226","discussion":"https://news.ycombinator.com/item?id=45857099"},{"title":"Cloudflare scrubs Aisuru botnet from top domains list","points":156,"comments":34,"url":"https://krebsonsecurity.com/2025/11/cloudflare-scrubs-aisuru-botnet-from-top-domains-list/","discussion":"https://news.ycombinator.com/item?id=45857836"}],"research":[{"title":"LATTLE: LLM Attention Transplant for Transfer Learning of Tabular Data Across Disparate Domains","abstract":"Transfer learning on tabular data is challenging due to disparate feature spaces across domains, in contrast to the homogeneous structures of image and text. Large language models (LLMs) offer a knowledge base to improve the limited effectiveness of cross-domain transfer learning for tabular data. However, LLM performance often stagnates due to subjective text prompts and the computational limitations of in-context l","authors":["Ibna Kowsar","Kazi F. Akhter","Manar D. Samad"],"url":"http://arxiv.org/abs/2511.06161v2","arxiv_id":"2511.06161v2","published":"2025-11-08T23:05:31Z"},{"title":"Evaluating Implicit Biases in LLM Reasoning through Logic Grid Puzzles","abstract":"While recent safety guardrails effectively suppress overtly biased outputs, subtler forms of social bias emerge during complex logical reasoning tasks that evade current evaluation benchmarks. To fill this gap, we introduce a new evaluation framework, PRIME (Puzzle Reasoning for Implicit Biases in Model Evaluation), that uses logic grid puzzles to systematically probe the influence of social stereotypes on logical re","authors":["Fatima Jahara","Mark Dredze","Sharon Levy"],"url":"http://arxiv.org/abs/2511.06160v2","arxiv_id":"2511.06160v2","published":"2025-11-08T22:51:59Z"},{"title":"Models Got Talent: Identifying High Performing Wearable Human Activity Recognition Models Without Training","abstract":"A promising alternative to the computationally expensive Neural Architecture Search (NAS) involves the development of Zero Cost Proxies (ZCPs), which correlate well with trained performance, but can be computed through a single forward/backward pass on a randomly sampled batch of data. In this paper, we investigate the effectiveness of ZCPs for HAR on six benchmark datasets, and demonstrate that they discover network","authors":["Richard Goldman","Varun Komperla","Thomas Ploetz","Harish Haresamudram"],"url":"http://arxiv.org/abs/2511.06157v2","arxiv_id":"2511.06157v2","published":"2025-11-08T22:38:14Z"},{"title":"Large Language Models Develop Novel Social Biases Through Adaptive Exploration","abstract":"As large language models (LLMs) are adopted into frameworks that grant them the capacity to make real decisions, it is increasingly important to ensure that they are unbiased. In this paper, we argue that the predominant approach of simply removing existing biases from models is not enough. Using a paradigm from the psychology literature, we demonstrate that LLMs can spontaneously develop novel social biases about ar","authors":["Addison J. Wu","Ryan Liu","Xuechunzi Bai","Thomas L. Griffiths"],"url":"http://arxiv.org/abs/2511.06148v4","arxiv_id":"2511.06148v4","published":"2025-11-08T21:58:26Z"},{"title":"Referring Expressions as a Lens into Spatial Language Grounding in Vision-Language Models","abstract":"Spatial Reasoning is an important component of human cognition and is an area in which the latest Vision-language models (VLMs) show signs of difficulty. The current analysis works use image captioning tasks and visual question answering. In this work, we propose using the Referring Expression Comprehension task instead as a platform for the evaluation of spatial reasoning by VLMs. This platform provides the opportun","authors":["Akshar Tumu","Varad Shinde","Parisa Kordjamshidi"],"url":"http://arxiv.org/abs/2511.06146v1","arxiv_id":"2511.06146v1","published":"2025-11-08T21:43:09Z"},{"title":"MTTR-A: Measuring Cognitive Recovery Latency in Multi-Agent Systems","abstract":"Reliability in multi-agent systems (MAS) built on large language models is increasingly limited by cognitive failures rather than infrastructure faults. Existing observability tools describe failures but do not quantify how quickly distributed reasoning recovers once coherence is lost. We introduce MTTR-A (Mean Time-to-Recovery for Agentic Systems), a runtime reliability metric that measures cognitive recovery latenc","authors":["Barak Or"],"url":"http://arxiv.org/abs/2511.20663v5","arxiv_id":"2511.20663v5","published":"2025-11-08T21:29:18Z"},{"title":"MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning","abstract":"Monte Carlo Tree Search (MCTS), which leverages Upper Confidence Bound for Trees (UCTs) to balance exploration and exploitation through randomized sampling, is instrumental to solving complex planning problems. However, for multi-agent planning, MCTS is confronted with a large combinatorial action space that often grows exponentially with the number of agents. As a result, the branching factor of MCTS during tree exp","authors":["Sizhe Tang","Jiayu Chen","Tian Lan"],"url":"http://arxiv.org/abs/2511.06142v1","arxiv_id":"2511.06142v1","published":"2025-11-08T21:27:09Z"},{"title":"When Object-Centric World Models Meet Policy Learning: From Pixels to Policies, and Where It Breaks","abstract":"Object-centric world models (OCWM) aim to decompose visual scenes into object-level representations, providing structured abstractions that could improve compositional generalization and data efficiency in reinforcement learning. We hypothesize that explicitly disentangled object-level representations, by localizing task-relevant information, can enhance policy performance across novel feature combinations. To test t","authors":["Stefano Ferraro","Akihiro Nakano","Masahiro Suzuki","Yutaka Matsuo"],"url":"http://arxiv.org/abs/2511.06136v2","arxiv_id":"2511.06136v2","published":"2025-11-08T21:09:44Z"},{"title":"The Polite Liar: Epistemic Pathology in Language Models","abstract":"Large language models exhibit a peculiar epistemic pathology: they speak as if they know, even when they do not. This paper argues that such confident fabrication, what I call the polite liar, is a structural consequence of reinforcement learning from human feedback (RLHF). Building on Frankfurt's analysis of bullshit as communicative indifference to truth, I show that this pathology is not deception but structural i","authors":["Bentley DeVilling"],"url":"http://arxiv.org/abs/2511.07477v1","arxiv_id":"2511.07477v1","published":"2025-11-08T21:02:52Z"},{"title":"Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs","abstract":"Multi-agent systems (MAS) built on Large Language Models (LLMs) are being used to approach complex problems and can surpass single model inference. However, their success hinges on navigating a fundamental cognitive tension: the need to balance broad, divergent exploration of the solution space with a principled, convergent synthesis to the optimal solution. Existing paradigms often struggle to manage this duality, l","authors":["Wei Yang","Jiacheng Pang","Shixuan Li","Paul Bogdan","Stephen Tu","Jesse Thomason"],"url":"http://arxiv.org/abs/2511.06134v1","arxiv_id":"2511.06134v1","published":"2025-11-08T21:01:27Z"},{"title":"Evaluation of retrieval-based QA on QUEST-LOFT","abstract":"Despite the popularity of retrieval-augmented generation (RAG) as a solution for grounded QA in both academia and industry, current RAG methods struggle with questions where the necessary information is distributed across many documents or where retrieval needs to be combined with complex reasoning. Recently, the LOFT study has shown that this limitation also applies to approaches based on long-context language model","authors":["Nathan Scales","Nathanael Schärli","Olivier Bousquet"],"url":"http://arxiv.org/abs/2511.06125v1","arxiv_id":"2511.06125v1","published":"2025-11-08T20:30:45Z"},{"title":"Secure Autonomous Agent Payments: Verifying Authenticity and Intent in a Trustless Environment","abstract":"Artificial intelligence (AI) agents are increasingly capable of initiating financial transactions on behalf of users or other agents. This evolution introduces a fundamental challenge: verifying both the authenticity of an autonomous agent and the true intent behind its transactions in a decentralized, trustless environment. Traditional payment systems assume human authorization, but autonomous, agent-led payments re","authors":["Vivek Acharya"],"url":"http://arxiv.org/abs/2511.15712v1","arxiv_id":"2511.15712v1","published":"2025-11-08T19:53:51Z"},{"title":"SynthAgent: Adapting Web Agents with Synthetic Supervision","abstract":"Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored synthetic data generation to address this challenge, however, they suffer from data quality issues where synthesized tasks contain hallucinations that cannot be executed, and collected trajectories are noisy with redundant or misaligned actions. In this paper, we propose SynthA","authors":["Zhaoyang Wang","Yiming Liang","Xuchao Zhang","Qianhui Wu","Siwei Han","Anson Bastos"],"url":"http://arxiv.org/abs/2511.06101v3","arxiv_id":"2511.06101v3","published":"2025-11-08T18:45:33Z"},{"title":"SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?","abstract":"Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce runtime while preserving program correctness. However, most benchmarks emphasize what to fix rather than how to fix code. We introduce SWE-fficiency, a benchmark for evaluating repository-level performance optimization on real workloads. Our suite contains 498 tasks across nine ","authors":["Jeffrey Jian Ma","Milad Hashemi","Amir Yazdanbakhsh","Kevin Swersky","Ofir Press","Enhui Li"],"url":"http://arxiv.org/abs/2511.06090v3","arxiv_id":"2511.06090v3","published":"2025-11-08T17:55:09Z"},{"title":"Hybrid CNN-ViT Framework for Motion-Blurred Scene Text Restoration","abstract":"Motion blur in scene text images severely impairs readability and hinders the reliability of computer vision tasks, including autonomous driving, document digitization, and visual information retrieval. Conventional deblurring approaches are often inadequate in handling spatially varying blur and typically fall short in modeling the long-range dependencies necessary for restoring textual clarity. To overcome these li","authors":["Umar Rashid","Muhammad Arslan Arshad","Ghulam Ahmad","Muhammad Zeeshan Anjum","Rizwan Khan","Muhammad Akmal"],"url":"http://arxiv.org/abs/2511.06087v1","arxiv_id":"2511.06087v1","published":"2025-11-08T17:48:58Z"},{"title":"Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI","abstract":"Simulated Students offer a valuable methodological framework for evaluating pedagogical approaches and modelling diverse learner profiles, tasks which are otherwise challenging to undertake systematically in real-world settings. Recent research has increasingly focused on developing such simulated agents to capture a range of learning styles, cognitive development pathways, and social behaviours. Among contemporary s","authors":["Luis Marquez-Carpintero","Alberto Lopez-Sellers","Miguel Cazorla"],"url":"http://arxiv.org/abs/2511.06078v1","arxiv_id":"2511.06078v1","published":"2025-11-08T17:23:13Z"},{"title":"Stemming Hallucination in Language Models Using a Licensing Oracle","abstract":"Language models exhibit remarkable natural language generation capabilities but remain prone to hallucinations, generating factually incorrect information despite producing syntactically coherent responses. This study introduces the Licensing Oracle, an architectural solution designed to stem hallucinations in LMs by enforcing truth constraints through formal validation against structured knowledge graphs. Unlike sta","authors":["Simeon Emanuilov","Richard Ackermann"],"url":"http://arxiv.org/abs/2511.06073v1","arxiv_id":"2511.06073v1","published":"2025-11-08T17:07:57Z"},{"title":"ScRPO: From Errors to Insights","abstract":"We introduce Self-correction Relative Policy Optimization (ScRPO), a novel reinforcement learning framework designed to empower large language models with advanced mathematical reasoning capabilities through iterative self-reflection and error correction. The ScRPO framework operates in two distinct phases: (1) Trial-and-error learning stage, where the model is trained via GRPO, and incorrect responses are collected ","authors":["Lianrui Li","Dakuan Lu","Jiawei Shao","Xuelong Li"],"url":"http://arxiv.org/abs/2511.06065v3","arxiv_id":"2511.06065v3","published":"2025-11-08T16:30:44Z"},{"title":"A Privacy-Preserving Federated Learning Method with Homomorphic Encryption in Omics Data","abstract":"Omics data is widely employed in medical research to identify disease mechanisms and contains highly sensitive personal information. Federated Learning (FL) with Differential Privacy (DP) can ensure the protection of omics data privacy against malicious user attacks. However, FL with the DP method faces an inherent trade-off: stronger privacy protection degrades predictive accuracy due to injected noise. On the other","authors":["Yusaku Negoya","Feifei Cui","Zilong Zhang","Miao Pan","Tomoaki Ohtsuki","Aohan Li"],"url":"http://arxiv.org/abs/2511.06064v1","arxiv_id":"2511.06064v1","published":"2025-11-08T16:18:42Z"},{"title":"How Particle-System Random Batch Methods Enhance Graph Transformer: Memory Efficiency and Parallel Computing Strategy","abstract":"Attention mechanism is a significant part of Transformer models. It helps extract features from embedded vectors by adding global information and its expressivity has been proved to be powerful. Nevertheless, the quadratic complexity restricts its practicability. Although several researches have provided attention mechanism in sparse form, they are lack of theoretical analysis about the expressivity of their mechanis","authors":["Hanwen Liu","Yixuan Ma","Shi Jin","Yuguang Wang"],"url":"http://arxiv.org/abs/2511.06044v1","arxiv_id":"2511.06044v1","published":"2025-11-08T15:34:15Z"},{"title":"Advancing Ocean State Estimation with efficient and scalable AI","abstract":"Accurate and efficient global ocean state estimation remains a grand challenge for Earth system science, hindered by the dual bottlenecks of computational scalability and degraded data fidelity in traditional data assimilation (DA) and deep learning (DL) approaches. Here we present an AI-driven Data Assimilation Framework for Ocean (ADAF-Ocean) that directly assimilates multi-source and multi-scale observations, rang","authors":["Yanfei Xiang","Yuan Gao","Hao Wu","Quan Zhang","Ruiqi Shu","Xiao Zhou"],"url":"http://arxiv.org/abs/2511.06041v1","arxiv_id":"2511.06041v1","published":"2025-11-08T15:24:23Z"},{"title":"S2ML: Spatio-Spectral Mutual Learning for Depth Completion","abstract":"The raw depth images captured by RGB-D cameras using Time-of-Flight (TOF) or structured light often suffer from incomplete depth values due to weak reflections, boundary shadows, and artifacts, which limit their applications in downstream vision tasks. Existing methods address this problem through depth completion in the image domain, but they overlook the physical characteristics of raw depth images. It has been obs","authors":["Zihui Zhao","Yifei Zhang","Zheng Wang","Yang Li","Kui Jiang","Zihan Geng"],"url":"http://arxiv.org/abs/2511.06033v1","arxiv_id":"2511.06033v1","published":"2025-11-08T15:01:55Z"},{"title":"ITPP: Learning Disentangled Event Dynamics in Marked Temporal Point Processes","abstract":"Marked Temporal Point Processes (MTPPs) provide a principled framework for modeling asynchronous event sequences by conditioning on the history of past events. However, most existing MTPP models rely on channel-mixing strategies that encode information from different event types into a single, fixed-size latent representation. This entanglement can obscure type-specific dynamics, leading to performance degradation an","authors":["Wang-Tao Zhou","Zhao Kang","Ke Yan","Ling Tian"],"url":"http://arxiv.org/abs/2511.06032v1","arxiv_id":"2511.06032v1","published":"2025-11-08T15:00:25Z"},{"title":"Retrieval-Augmented Multi-LLM Ensemble for Industrial Part Specification Extraction","abstract":"Industrial part specification extraction from unstructured text remains a persistent challenge in manufacturing, procurement, and maintenance, where manual processing is both time-consuming and error-prone. This paper introduces a retrieval-augmented multi-LLM ensemble framework that orchestrates nine state-of-the-art Large Language Models (LLMs) within a structured three-phase pipeline. RAGsemble addresses key limit","authors":["Muzakkiruddin Ahmed Mohammed","John R. Talburt","Leon Claasssens","Adriaan Marais"],"url":"http://arxiv.org/abs/2601.05266v1","arxiv_id":"2601.05266v1","published":"2025-11-08T14:43:20Z"},{"title":"MiVID: Multi-Strategic Self-Supervision for Video Frame Interpolation using Diffusion Model","abstract":"Video Frame Interpolation (VFI) remains a cornerstone in video enhancement, enabling temporal upscaling for tasks like slow-motion rendering, frame rate conversion, and video restoration. While classical methods rely on optical flow and learning-based models assume access to dense ground-truth, both struggle with occlusions, domain shifts, and ambiguous motion. This article introduces MiVID, a lightweight, self-super","authors":["Priyansh Srivastava","Romit Chatterjee","Abir Sen","Aradhana Behura","Ratnakar Dash"],"url":"http://arxiv.org/abs/2511.06019v1","arxiv_id":"2511.06019v1","published":"2025-11-08T14:10:04Z"}],"history":{"events":[{"year":2020,"text":"Second Nagorno-Karabakh War: Azerbaijani forces defeated the self-proclaimed Republic of Artsakh in the Battle of Shusha, reclaiming the town after 28 years.","url":"https://en.wikipedia.org/wiki/Second_Nagorno-Karabakh_War"},{"year":2017,"text":"The Louvre Abu Dhabi was inaugurated by the French president Emmanuel Macron and then-crown prince of Abu Dhabi Mohamed bin Zayed Al Nahyan.","url":"https://en.wikipedia.org/wiki/Louvre_Abu_Dhabi"},{"year":2013,"text":"Typhoon Haiyan made landfall in the Visayas region of the Philippines, killing at least 6,300 people, making it the deadliest Philippine typhoon recorded in modern history.","url":"https://en.wikipedia.org/wiki/Typhoon_Haiyan"},{"year":1999,"text":"German newspaper Der Spiegel publishes a report by the Federal Intelligence Service accusing figures in Liechtenstein of cooperating with organized crime.","url":"https://en.wikipedia.org/wiki/Der_Spiegel"},{"year":1987,"text":"A Provisional Irish Republican Army bomb exploded during a Remembrance Sunday ceremony in Enniskillen, Northern Ireland, killing 12 people and injuring 63 others.","url":"https://en.wikipedia.org/wiki/Provisional_Irish_Republican_Army"},{"year":1974,"text":"British peer Lord Lucan disappeared without a trace, a day after allegedly murdering Sandra Rivett, his children's nanny.","url":"https://en.wikipedia.org/wiki/John_Bingham%2C_7th_Earl_of_Lucan"},{"year":1971,"text":"English rock group Led Zeppelin released their fourth album, which became one of the best-selling albums worldwide.","url":"https://en.wikipedia.org/wiki/Led_Zeppelin"},{"year":1966,"text":"Former Massachusetts attorney general Edward Brooke became the first African American elected to the United States Senate since Reconstruction.","url":"https://en.wikipedia.org/wiki/Massachusetts"},{"year":1965,"text":"Vietnam War: In the Battle of Gang Toi, one of the earliest battles between the two sides, Viet Cong forces repelled an Australian attack.","url":"https://en.wikipedia.org/wiki/Vietnam_War"},{"year":1957,"text":"En route from San Francisco to Honolulu, Pan Am Flight 7 crashed into the Pacific Ocean due to unknown causes, killing all 44 people on board.","url":"https://en.wikipedia.org/wiki/Pan_Am_Flight_7"},{"year":1940,"text":"The Italian invasion of Greece failed as outnumbered Greek units repulsed the Italians at the Battle of Elaia–Kalamas.","url":"https://en.wikipedia.org/wiki/Greco-Italian_War"},{"year":1932,"text":"The Australian military withdrew from their \"war against emus\" in Western Australia, due to negative press coverage of the operation.","url":"https://en.wikipedia.org/wiki/Australian_Defence_Force"},{"year":1644,"text":"The Shunzhi Emperor (portrait shown), the third emperor of the Qing dynasty, was enthroned in Beijing after the collapse of the Ming dynasty as the first Qing emperor to rule over China.","url":"https://en.wikipedia.org/wiki/Shunzhi_Emperor"},{"year":1520,"text":"After his coronation as king of Sweden, Christian II (pictured) gave the order to execute nearly 100 people, mostly noblemen, despite promises of general amnesty.","url":"https://en.wikipedia.org/wiki/Monarchy_of_Sweden"},{"year":1291,"text":"A law was passed that confined most of Venice's glassmaking industry to nearby Murano.","url":"https://en.wikipedia.org/wiki/Venetian_glass"},{"year":1278,"text":"Trần Thánh Tông, the second emperor of Vietnam's Trần dynasty, took up the title of retired emperor, but continued to co-rule with his son Nhân Tông for eleven more years.","url":"https://en.wikipedia.org/wiki/Tr%E1%BA%A7n_Th%C3%A1nh_T%C3%B4ng"},{"year":960,"text":"Arab–Byzantine wars: Having been the target of many raids by the Emirate of Aleppo, Byzantine forces led by Leo Phokas the Younger ambushed the Hamdanids and annihilated their army.","url":"https://en.wikipedia.org/wiki/Arab%E2%80%93Byzantine_wars"}],"births":[{"year":2004,"text":"Ilyas Ansah, German footballer","url":"https://en.wikipedia.org/wiki/Ilyas_Ansah"},{"year":2000,"text":"Jade Pettyjohn, American actress","url":"https://en.wikipedia.org/wiki/Jade_Pettyjohn"},{"year":2000,"text":"Jasmine Thompson, English singer","url":"https://en.wikipedia.org/wiki/Jasmine_Thompson"},{"year":1999,"text":"Isaac Bonga, German basketball player","url":"https://en.wikipedia.org/wiki/Isaac_Bonga"},{"year":1999,"text":"Katherine Uchida, Canadian rhythmic gymnast","url":"https://en.wikipedia.org/wiki/Katherine_Uchida"},{"year":1997,"text":"Leonardo Fernández, Uruguayan footballer","url":"https://en.wikipedia.org/wiki/Leonardo_Fern%C3%A1ndez_(Uruguayan_footballer)"},{"year":1997,"text":"Akram Tawfik, Egyptian footballer","url":"https://en.wikipedia.org/wiki/Akram_Tawfik"},{"year":1996,"text":"Jens Stage, Danish footballer","url":"https://en.wikipedia.org/wiki/Jens_Stage"}],"deaths":[{"year":2025,"text":"Graham Richardson, Australian politician (born 1949)","url":"https://en.wikipedia.org/wiki/Graham_Richardson"},{"year":2024,"text":"Elizabeth Nunez, American novelist (born 1944)","url":"https://en.wikipedia.org/wiki/Elizabeth_Nunez"},{"year":2024,"text":"June Spencer, English actress (born 1919)","url":"https://en.wikipedia.org/wiki/June_Spencer"},{"year":2024,"text":"Trevor Sorbie, Scottish hairdresser (born 1949)","url":"https://en.wikipedia.org/wiki/Trevor_Sorbie"},{"year":2020,"text":"Alex Trebek, Canadian-American television personality and longtime host of Jeopardy! (born 1940)","url":"https://en.wikipedia.org/wiki/Alex_Trebek"},{"year":2018,"text":"Dennis Wrong, Canadian-born American sociologist (born 1923)","url":"https://en.wikipedia.org/wiki/Dennis_Wrong"},{"year":2015,"text":"Rhea Chiles, American philanthropist, founded the Polk Museum of Art (born 1930)","url":"https://en.wikipedia.org/wiki/Rhea_Chiles"},{"year":2015,"text":"Joseph Cure, American ice hockey player and actor (born 1984)","url":"https://en.wikipedia.org/wiki/Joseph_Cure"}]},"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."}