Record 01112025 · captured 2026-08-25
The world looked up Andrew Mountbatten-Windsor. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
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What the most people looked up, ranked by Wikipedia pageviews for that day.
Andrew Albert Christian Edward Mountbatten-Windsor, formerly Prince Andrew, Duke of York, is the third child and second son of Queen Elizabeth II and Prince Philip, Duke of Edinburgh, and a younger brother of King Charles III. Andrew was born second in the lin
Google Chrome is a cross-platform web browser developed by Google. It was launched in September 2008 for Microsoft Windows and was built with free software components from Apple WebKit and Mozilla Firefox. Versions for Linux, macOS, iOS, iPadOS, and Android we
Jemimah Jessica Rodrigues is an Indian international cricketer who plays for the India women's national team as a middle-order batter. She was part of the squad that won the 2025 Women's Cricket World Cup, the Women's Asia Cup in 2022, the gold medal at the 20
Virginia Lee Roberts Giuffre was an American and Australian advocate for survivors of sex trafficking and one of the most prominent accusers of Jeffrey Epstein. Giuffre provided detailed allegations to media outlets about Epstein and Ghislaine Maxwell. She all
Halloween, also known as All Hallows' Eve, or All Saints' Eve, is a celebration observed in many countries on 31 October, the eve of the Western Christian feast of All Hallows' Day. It is at the beginning of the observance of Allhallowtide, the time in the Chr
The ICC Women's Cricket World Cup is the quadrennial international championship of the One Day International format with 50 overs per team. It is organised by the International Cricket Council.
6-7 was an Internet meme, slang term, and gesture that became popular in 2025 on TikTok and Instagram Reels. It has no fixed meaning.
Edward Theodore Gein, also known as the Butcher of Plainfield and the Plainfield Ghoul, was an American murderer and body snatcher. His crimes, committed around his hometown of Plainfield, Wisconsin, gathered widespread notoriety in 1957 after authorities disc
Aileen Carol Wuornos was an American serial killer. Between 1989 and 1990, while engaging in street prostitution along highways in Florida, Wuornos shot, killed, and robbed seven of her male clients. She initially claimed that her victims had either raped or a
This is a list of lists of deaths of significant people, organized by year. New deaths articles are added to their respective month and then linked below.
Fuck is a profanity in the English language. It often refers to the act of sexual intercourse, but it is most commonly used as an intensifier or to convey disdain. While its origin is obscure, it is usually considered to be first attested to around 1475. In mo
It: Welcome to Derry is an American supernatural horror television series based on Stephen King's 1986 novel It. Serving as a prequel to the films It (2017) and It Chapter Two (2019), the series was developed by Andy Muschietti, Barbara Muschietti and Jason Fu
Early general elections were held in the Netherlands on 29 October 2025 to elect the members of the House of Representatives. The elections had been expected to be held in 2028, but a snap election was called after the Schoof cabinet collapsed due to the Party
Kantara: A Legend – Chapter 1 is a 2025 Indian Kannada-language epic mythological action drama film co-written and directed by Rishab Shetty, and produced by Vijay Kiragandur and Chaluve Gowda under Hombale Films. The film stars Rishab Shetty in a quadruple ro
Sydney Bernice Sweeney is an American actress. She gained early recognition for her roles in Everything Sucks!, The Handmaid's Tale, and Sharp Objects in 2018. She received wider acclaim for her performances in the drama series Euphoria (2019–2026) and the fir
Bugonia is a 2025 dark comedy film directed by Yorgos Lanthimos and written by Will Tracy. An English-language remake of the 2003 South Korean film Save the Green Planet! by Jang Joon-hwan, the film follows two young men who kidnap a powerful CEO, suspecting t
A House of Dynamite is a 2025 American political thriller film directed by Kathryn Bigelow and written by Noah Oppenheim. The film dramatizes the perspectives and responses of various U.S. government officials, both civilian and military, after an unknown adve
The Three Christs of Ypsilanti
The Three Christs of Ypsilanti: A Narrative Study of Three Lost Men is an American book-length psychiatric case study by Milton Rokeach, concerning his experiment on a group of three males with paranoid schizophrenia at Ypsilanti State Hospital in Ypsilanti, M
Jeffrey Edward Epstein was an American financier and child sex offender. He began his career as a math teacher at the Dalton School in New York City, before entering the banking and finance sector. Over several decades, he made much of his fortune providing ta
1xBet is an online gambling company founded in 2007 and licensed by Curaçao eGaming License. 1xBet is one of the largest online casinos in the world. According to Forbes, its turnover exceeded $2 billion in 2020. The company sponsors major professional footbal
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
Sarah Margaret Ferguson, formerly Sarah, Duchess of York, and commonly known as Fergie, is a British author, spokesperson, and television personality. She is the ex-wife of Andrew Mountbatten-Windsor, the former Prince Andrew, Duke of York, who is the second s
Michael Lee McDaniel is an American professional football coach who is the offensive coordinator for the Los Angeles Chargers of the National Football League (NFL). A branch of the Shanahan coaching tree, McDaniel began his NFL coaching career as an intern for
Lokah Chapter 1: Chandra is a 2025 Indian Malayalam-language fantasy superhero film written and directed by Dominic Arun and produced by Dulquer Salmaan for Wayfarer Films. It stars Kalyani Priyadarshan and Naslen, with Sandy, Chandu Salim Kumar and Arun Kuria
The Witcher is a fantasy drama television series created by Lauren Schmidt Hissrich for Netflix. It is based on the book series by Polish author Andrzej Sapkowski. Set on a fictional, medieval-inspired landmass known as the Continent, The Witcher explores the
Baahubali: The Epic is a 2025 Indian Telugu-language epic action film directed by S. S. Rajamouli, who co-wrote the script with V. Vijayendra Prasad. Produced by Shobu Yarlagadda and Prasad Devineni under Arka Media Works, the film stars Prabhas in dual roles
Rob Arnoldus Adrianus Jetten is a Dutch politician who has served as prime minister of the Netherlands since February 2026. He has also served as leader of the Democrats 66 (D66) since August 2023. Previously, he served in the fourth Rutte cabinet as Minister
The Rapid Support Forces (RSF) are a Sudanese paramilitary force formerly operated by the Sudanese government. They originated as auxiliary force militias known as the Janjaweed used by the Sudanese government during the War in Darfur, which the government lat
Trey David Yesavage is an American professional baseball pitcher for the Toronto Blue Jays of Major League Baseball (MLB). He played college baseball for the East Carolina Pirates, and was selected by the Blue Jays in the first round of the 2024 MLB draft. He
Weapons is a 2025 American supernatural mystery horror film directed, written, produced, and co-scored by Zach Cregger. It stars an ensemble cast including Josh Brolin, Julia Garner, Alden Ehrenreich, Austin Abrams, Cary Christopher, Toby Huss, Benedict Wong,
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective
Agentic AI serving converts monolithic LLM-based inference to autonomous problem-solvers that can plan, call tools, perform reasoning, and adapt on the fly. Due to diverse task execution need, such serving heavily rely on heterogeneous CPU-GPU systems with majority of the external tools responsible for agentic capability, either run on or are orchestrated by the CPU. Towards having a deeper understanding of its role,
While homomorphic encryption (HE) provides strong privacy protection, its high computational cost has restricted its application to simple tasks. Recently, hyperdimensional computing (HDC) applied to HE has shown promising performance for privacy-preserving machine learning (PPML). However, when applied to more realistic scenarios such as batch inference, the HDC-based HE has still very high compute time as well as h
FeNN-DMA: A RISC-V SoC for SNN acceleration
Spiking Neural Networks (SNNs) are a promising, energy-efficient alternative to standard Artificial Neural Networks (ANNs) and are particularly well-suited to spatio-temporal tasks such as keyword spotting and video classification. However, SNNs have a much lower arithmetic intensity than ANNs and are therefore not well-matched to standard accelerators like GPUs and TPUs. Field Programmable Gate Arrays (FPGAs) are de
Fibbinary-Based Compression and Quantization for Efficient Neural Radio Receivers
Neural receivers have shown outstanding performance compared to the conventional ones but this comes with a high network complexity leading to a heavy computational cost. This poses significant challenges in their deployment on hardware-constrained devices. To address the issue, this paper explores two optimization strategies: quantization and compression. We introduce both uniform and non-uniform quantization such a
TRISKELION-1: Unified Descriptive-Predictive-Generative AI
TRISKELION-1 is a unified descriptive-predictive-generative architecture that integrates statistical, mechanistic, and generative reasoning within a single encoder-decoder framework. The model demonstrates how descriptive representation learning, predictive inference, and generative synthesis can be jointly optimized using variational objectives. Experiments on MNIST validate that descriptive reconstruction, predicti
Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language Models
Recent studies posit that Reinforcement Learning with Verifiable Rewards (RLVR) primarily amplifies behaviors inherent to the pre-training distribution rather than inducing new capabilities, but these insights are predominantly limited to language-only domains, leaving the dynamics of visual-centric spatial reasoning under-explored. To examine the impact of RLVR on the capability boundaries of Vision-Language Models
A Voice-Enabled Virtual Patient System for Interactive Training in Standardized Clinical Assessment
Training mental health clinicians to conduct standardized clinical assessments is challenging due to a lack of scalable, realistic practice opportunities, which can impact data quality in clinical trials. To address this gap, we introduce a voice-enabled virtual patient simulation system powered by a large language model (LLM). This study describes the system's development and validates its ability to generate virtua
Agentic Educational Content Generation for African Languages on Edge Devices
Addressing educational inequity in Sub-Saharan Africa, this research presents an autonomous agent-orchestrated framework for decentralized, culturally adaptive educational content generation on edge devices. The system leverages four specialized agents that work together to generate contextually appropriate educational content. Experimental validation on platforms including Raspberry Pi 4B and NVIDIA Jetson Nano demo
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or specialized information. A natural strategy to increase the likelihood of retrieving relevant information is to expand the number of retrieved documents. However, involving more documents could introduce significant noise, as many documents may be
Evolve to Inspire: Novelty Search for Diverse Image Generation
Text-to-image diffusion models, while proficient at generating high-fidelity images, often suffer from limited output diversity, hindering their application in exploratory and ideation tasks. Existing prompt optimization techniques typically target aesthetic fitness or are ill-suited to the creative visual domain. To address this shortcoming, we introduce WANDER, a novelty search-based approach to generating diverse
Metadata-Aligned 3D MRI Representations for Contrast Understanding and Quality Control
Magnetic Resonance Imaging suffers from substantial data heterogeneity and the absence of standardized contrast labels across scanners, protocols, and institutions, which severely limits large-scale automated analysis. A unified representation of MRI contrast would enable a wide range of downstream utilities, from automatic sequence recognition to harmonization and quality control, without relying on manual annotatio
In this paper, we introduce a model for analyzing deep learning optimization over a single iteration by leveraging the matrix structure of the weights. We derive the model by assuming isotropy of curvature, including the second-order Hessian and higher-order terms, of the loss function across all perturbation directions; hence, we call it the isotropic curvature model. This model is a convex optimization program amen
Lifted Successor Generation in Numeric Planning
Most planners ground numeric planning tasks, given in a first-order-like language, into a ground task representation. However, this can lead to an exponential blowup in task representation size, which occurs in practice for hard-to-ground tasks. We extend a state-of-the-art lifted successor generator for classical planning to support numeric precondition applicability. The method enumerates maximum cliques in a subst
ShadowLogic: Backdoors in Any Whitebox LLM
Large language models (LLMs) are widely deployed across various applications, often with safeguards to prevent the generation of harmful or restricted content. However, these safeguards can be covertly bypassed through adversarial modifications to the computational graph of a model. This work highlights a critical security vulnerability in computational graph-based LLM formats, demonstrating that widely used deployme
Automated Invoice Data Extraction: Using LLM and OCR
Conventional Optical Character Recognition (OCR) systems are challenged by variant invoice layouts, handwritten text, and low-quality scans, which are often caused by strong template dependencies that restrict their flexibility across different document structures and layouts. Newer solutions utilize advanced deep learning models such as Convolutional Neural Networks (CNN) as well as Transformers, and domain-specific
The advances and availability of technologies involving Generative Artificial Intelligence (AI) are evolving clearly and explicitly, driving immediate changes in various work activities. Software Engineering (SE) is no exception and stands to benefit from these new technologies, enhancing productivity and quality in its software development processes. However, although the use of Generative AI in SE practices is stil
Test-time Scaling of LLMs: A Survey from A Subproblem Structure Perspective
With this paper, we survey techniques for improving the predictive accuracy of pretrained large language models by allocating additional compute at inference time. In categorizing test-time scaling methods, we place special emphasis on how a problem is decomposed into subproblems and on the topological organization of these subproblems whether sequential, parallel, or tree-structured. This perspective allows us to un
Telecom networks are rapidly growing in scale and complexity, making effective management, operation, and optimization increasingly challenging. Although Artificial Intelligence (AI) has been applied to many telecom tasks, existing models are often narrow in scope, require large amounts of labeled data, and struggle to generalize across heterogeneous deployments. Consequently, network troubleshooting continues to rel
More Than A Shortcut: A Hyperbolic Approach To Early-Exit Networks
Deploying accurate event detection on resource-constrained devices is challenged by the trade-off between performance and computational cost. While Early-Exit (EE) networks offer a solution through adaptive computation, they often fail to enforce a coherent hierarchical structure, limiting the reliability of their early predictions. To address this, we propose Hyperbolic Early-Exit networks (HypEE), a novel framework
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
Large Reasoning Models (LRMs) achieve remarkable inference-time improvements through parallel thinking. However, existing methods rely on redundant sampling of reasoning trajectories, failing to effectively explore the reasoning space to uncover high-quality solutions. To address these limitations, we propose Decoding Tree Sketching (DTS), a plug-and-play decoding framework for structural multi-trajectory exploration
Node Preservation and its Effect on Crossover in Cartesian Genetic Programming
While crossover is a critical and often indispensable component in other forms of Genetic Programming, such as Linear- and Tree-based, it has consistently been claimed that it deteriorates search performance in CGP. As a result, a mutation-alone $(1+λ)$ evolutionary strategy has become the canonical approach for CGP. Although several operators have been developed that demonstrate an increased performance over the can
AgentGit: A Version Control Framework for Reliable and Scalable LLM-Powered Multi-Agent Systems
With the rapid progress of large language models (LLMs), LLM-powered multi-agent systems (MAS) are drawing increasing interest across academia and industry. However, many current MAS frameworks struggle with reliability and scalability, especially on complex tasks. We present AgentGit, a framework that brings Git-like rollback and branching to MAS workflows. Built as an infrastructure layer on top of LangGraph, Agent
Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
Large language models (LLMs) can be controlled at inference time through prompts (in-context learning) and internal activations (activation steering). Different accounts have been proposed to explain these methods, yet their common goal of controlling model behavior raises the question of whether these seemingly disparate methodologies can be seen as specific instances of a broader framework. Motivated by this, we de
PreferThinker: Reasoning-based Personalized Image Preference Assessment
Personalized image preference assessment aims to evaluate an individual user's image preferences by relying only on a small set of reference images as prior information. Existing methods mainly focus on general preference assessment, training models with large-scale data to tackle well-defined tasks such as text-image alignment. However, these approaches struggle to handle personalized preference because user-specifi
EPARA: Parallelizing Categorized AI Inference in Edge Clouds
With the increasing adoption of AI applications such as large language models and computer vision AI, the computational demands on AI inference systems are continuously rising, making the enhancement of task processing capacity using existing hardware a primary objective in edge clouds. We propose EPARA, an end-to-end AI parallel inference framework in edge, aimed at enhancing the edge AI serving capability. Our key
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