Record 20112025 · captured 2026-08-25
The world looked up 2026 FIFA World Cup qualification. 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.
2026 FIFA World Cup qualification
The 2026 FIFA World Cup qualification decided the 45 teams that joined hosts Canada, Mexico, and the United States at the 2026 FIFA World Cup.
The 2026 FIFA World Cup was the 23rd FIFA World Cup, the quadrennial international men's soccer championship contested by the national teams of the member associations of FIFA. The tournament began on June 11, 2026, and concluded on July 19 with Spain winning
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
The Epstein files are a partially released collection of millions of documents, images, videos, and emails related to the activities of American financier and convicted child sex offender Jeffrey Epstein, including his social circle of public figures, politici
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
2026 FIFA World Cup qualification (UEFA)
The European section of the 2026 FIFA World Cup qualification competition acted as qualifiers for the 2026 FIFA World Cup, that was held in Canada, Mexico and the United States, for national teams that were members of the Union of European Football Association
2026 FIFA World Cup qualification (inter-confederation play-offs)
The inter-confederation play-offs of the 2026 FIFA World Cup qualification tournament determined two qualification spots for the 2026 FIFA World Cup, played in Canada, Mexico, and the United States. The play-offs took place on 26 and 31 March 2026 at two venue
Dancing with the Stars (American TV series) season 34
Season thirty-four of Dancing with the Stars premiered on ABC and Disney+ on September 16, 2025, and concluded on December 2, 2025. This season, marking the twentieth anniversary of the series, was the third to air live on both networks simultaneously and the
Lawrence Henry Summers is an American economist. He served as the 71st United States Secretary of the Treasury from 1999 to 2001, the 27th president of Harvard University from 2001 to 2006, and the eighth director of the National Economic Council from 2009 to
Princess Alexandrine of Prussia (1915–1980)
Princess Alexandrine Irene of Prussia was the elder daughter and fifth child of Wilhelm, German Crown Prince, and Cecilie of Mecklenburg-Schwerin. Her grandparents were Wilhelm II, German Emperor and his wife Augusta Victoria of Schleswig-Holstein, and Frederi
International Men's Day (IMD) is a global awareness day for many issues that men face, including abuse, homelessness, suicide, and violence, celebrated annually on 19 November. The objectives of celebrating an International Men's Day are set out in "All the Si
Ryan James Wedding is a Canadian former Olympic snowboarder and alleged drug lord. He represented Canada at the 2002 Winter Olympics in the men's parallel giant slalom event. After retiring from snowboarding, he allegedly became an international drug trafficke
Alice and Ellen Kessler, usually credited as the Kessler Twins, were twin German singers, dancers and actresses who were popular in Europe, especially Germany and Italy, during the 1950s and 1960s.
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.
Jamal Ahmad Hamza Khashoggi was a Saudi journalist, dissident, author, columnist and editor. Khashoggi was assassinated at the Saudi consulate in Istanbul on 2 October 2018 by agents of the Saudi government at the behest of Crown Prince Mohammed bin Salman.
Curaçao, officially the Country of Curaçao, is a constituent country within the Kingdom of the Netherlands. It is an island country located in the southern Caribbean Sea, specifically the Dutch Caribbean region, about 65 km (40 mi) north of Venezuela and 80 km
Glen Clay Higgins is an American politician and reserve law enforcement officer from the state of Louisiana. A Republican, Higgins is the U.S. representative for Louisiana's 3rd congressional district. The district, which contains much of the territory once re
Mohammed bin Salman Al Saud, also known as MbS, is the de facto ruler of the Kingdom of Saudi Arabia, formally serving as Crown Prince and Prime Minister. He is the heir apparent to the Saudi throne, the son of King Salman, and the grandson of the nation's fou
Bruce Lee was a Hong Kong and American martial artist, actor, and filmmaker. He was the founder of Jeet Kune Do, a hybrid martial arts philosophy, which was formed from his experiences in unarmed fighting and self-defense—as well as eclectic, Zen Buddhist, and
2026 FIFA World Cup qualification (CONCACAF)
The North, Central American and Caribbean section of the 2026 FIFA World Cup qualification acted as the qualifiers for the 2026 FIFA World Cup, held in Canada, Mexico, and the United States, for national teams which were members of the Confederation of North,
2026 FIFA World Cup qualification – UEFA second round
The UEFA second round of the qualification tournament for the 2026 FIFA World Cup, also known as the UEFA play-offs or European play-offs, was contested by sixteen teams from the UEFA segment of qualifying. The play-offs determined the final four European team
Wicked: For Good is a 2025 musical fantasy film directed by Jon M. Chu and written by Winnie Holzman and Dana Fox. The sequel to Wicked (2024), it adapts the second act of the 2003 stage musical by Stephen Schwartz and Holzman, which was loosely based on Grego
1989 Tiananmen Square protests and massacre
Protests led by students and workers, known in China as the June Fourth Incident, were held in Tiananmen Square in Beijing, China, from 15 April to 4 June 1989. After weeks of unsuccessful attempts between the demonstrators and the Chinese government to find a
Curaçao national football team
The Curaçao national football team represents Curaçao in men's international football. The team is governed by the Federashon Futbòl Kòrsou.
James Abram Garfield was the 20th president of the United States, serving from March 1881 until his death in September that year after being shot in July. A preacher, lawyer, and Civil War general, Garfield served nine terms in the United States House of Repre
Dhurandhar is a 2025 Indian Hindi-language spy action thriller film written and directed by Aditya Dhar. It is produced by Aditya Dhar, Lokesh Dhar and Jyoti Deshpande under Jio Studios and B62 Studios. The film features an ensemble cast consisting of Ranveer
The Beast in Me is an American psychological crime thriller television miniseries for Netflix, starring Claire Danes and Matthew Rhys. Created by Gabe Rotter, the series follows an author (Danes) who begins writing a book about her new next-door neighbor (Rhys
Prince Rogers Nelson was an American singer, songwriter, musician, dancer, actor, and filmmaker. Often credited as one of the greatest musicians of his generation, he pioneered the Minneapolis sound and was influential in the evolution of various other genres.
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.
Claire Catherine Danes is an American actor. Prolific in film and television since her teens, she is the recipient of three Primetime Emmy Awards and four Golden Globe Awards. In 2012 and 2026, Time named her one of the 100 most influential people in the world
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Background: Mentalization integrates cognitive, affective, and intersubjective components. Large Language Models (LLMs) display an increasing ability to generate reflective texts, raising questions regarding the relationship between linguistic form and mental representation. This study assesses the extent to which a single LLM can reproduce the linguistic structure of mentalization according to the parameters of Ment
A Multi-objective Optimization Approach for Feature Selection in Gentelligent Systems
The integration of advanced technologies, such as Artificial Intelligence (AI), into manufacturing processes is attracting significant attention, paving the way for the development of intelligent systems that enhance efficiency and automation. This paper uses the term "Gentelligent system" to refer to systems that incorporate inherent component information (akin to genes in bioinformatics-where manufacturing operatio
Parkinson's disease (PD) is a progressive neurodegenerative disorder that, in addition to directly impairing functional mobility, is frequently associated with vocal impairments such as hypophonia and dysarthria, which typically manifest in the early stages. The use of vocal biomarkers to support the early diagnosis of PD presents a non-invasive, low-cost, and accessible alternative in clinical settings. Thus, the ob
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
High-resolution (HR) magnetic resonance imaging (MRI) is crucial for many clinical and research applications. However, achieving it remains costly and constrained by technical trade-offs and experimental limitations. Super-resolution (SR) presents a promising computational approach to overcome these challenges by generating HR images from more affordable low-resolution (LR) scans, potentially improving diagnostic acc
Hybrid coupling with operator inference and the overlapping Schwarz alternating method
This paper presents a novel hybrid approach for coupling subdomain-local non-intrusive Operator Inference (OpInf) reduced order models (ROMs) with each other and with subdomain-local high-fidelity full order models (FOMs) with using the overlapping Schwarz alternating method (O-SAM). The proposed methodology addresses significant challenges in multiscale modeling and simulation, particularly the long runtime and comp
Sex and age determination in European lobsters using AI-Enhanced bioacoustics
Monitoring aquatic species, especially elusive ones like lobsters, presents challenges. This study focuses on Homarus gammarus (European lobster), a key species for fisheries and aquaculture, and leverages non-invasive Passive Acoustic Monitoring (PAM). Understanding lobster habitats, welfare, reproduction, sex, and age is crucial for management and conservation. While bioacoustic emissions have classified various aq
ConCISE: A Reference-Free Conciseness Evaluation Metric for LLM-Generated Answers
Large language models (LLMs) frequently generate responses that are lengthy and verbose, filled with redundant or unnecessary details. This diminishes clarity and user satisfaction, and it increases costs for model developers, especially with well-known proprietary models that charge based on the number of output tokens. In this paper, we introduce a novel reference-free metric for evaluating the conciseness of respo
Fantastic Bugs and Where to Find Them in AI Benchmarks
Benchmarks are pivotal in driving AI progress, and invalid benchmark questions frequently undermine their reliability. Manually identifying and correcting errors among thousands of benchmark questions is not only infeasible but also a critical bottleneck for reliable evaluation. In this work, we introduce a framework for systematic benchmark revision that leverages statistical analysis of response patterns to flag po
Goal-Directed Search Outperforms Goal-Agnostic Memory Compression in Long-Context Memory Tasks
How to enable human-like long-term memory in large language models (LLMs) has been a central question for unlocking more general capabilities such as few-shot generalization. Existing memory frameworks and benchmarks focus on finding the optimal memory compression algorithm for higher performance in tasks that require recollection and sometimes further reasoning. However, such efforts have ended up building more huma
AI-based framework to predict animal and pen feed intake in feedlot beef cattle
Advances in technology are transforming sustainable cattle farming practices, with electronic feeding systems generating big longitudinal datasets on individual animal feed intake, offering the possibility for autonomous precision livestock systems. However, the literature still lacks a methodology that fully leverages these longitudinal big data to accurately predict feed intake accounting for environmental conditio
Purpose: Heart failure (HF) discharge planning depends on identifying patients at risk of deterioration or death, yet accurate prediction from routinely collected electronic health records (EHRs) remains challenging. Methods: We develop trajectory-guided discharge stratification for heart failure (TGDS-HF), a methodology that reads the patient in-hospital trajectory of diagnoses, vital signs, laboratories, medication
Cognitive BASIC: An In-Model Interpreted Reasoning Language for LLMs
Cognitive BASIC is a minimal, BASIC-style prompting language and in-model interpreter that structures large language model (LLM) reasoning into explicit, stepwise execution traces. Inspired by the simplicity of retro BASIC, we repurpose numbered lines and simple commands as an interpretable cognitive control layer. Modern LLMs can reliably simulate such short programs, enabling transparent multi-step reasoning inside
ManifoldFormer: Geometric Deep Learning for Neural Dynamics on Riemannian Manifolds
Existing EEG foundation models mainly treat neural signals as generic time series in Euclidean space, ignoring the intrinsic geometric structure of neural dynamics that constrains brain activity to low-dimensional manifolds. This fundamental mismatch between model assumptions and neural geometry limits representation quality and cross-subject generalization. ManifoldFormer addresses this limitation through a novel ge
PromptTailor: Multi-turn Intent-Aligned Prompt Synthesis for Lightweight LLMs
Lightweight language models remain attractive for on-device and privacy-sensitive applications, but their responses are highly sensitive to prompt quality. For open-ended generation, non-expert users often lack the knowledge or time to consistently craft high-quality prompts, leading them to rely on prompt optimization tools. However, a key challenge is ensuring the optimized prompts genuinely align with users' origi
WorldGen: From Text to Traversable and Interactive 3D Worlds
We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descriptions into traversable, fully textured environments that can be immediately explored or edited within standard game engines. By combining LLM-driven scene layout reasoning, procedural generation, diffusion-based 3D generation, and object-
Monte Carlo Expected Threat (MOCET) Scoring
Evaluating and measuring AI Safety Level (ASL) threats are crucial for guiding stakeholders to implement safeguards that keep risks within acceptable limits. ASL-3+ models present a unique risk in their ability to uplift novice non-state actors, especially in the realm of biosecurity. Existing evaluation metrics, such as LAB-Bench, BioLP-bench, and WMDP, can reliably assess model uplift and domain knowledge. However,
In the context of the growing proliferation of user devices and the concurrent surge in data volumes, the complexities arising from the substantial increase in data have posed formidable challenges to conventional machine learning model training. Particularly, this is evident within resource-constrained and security-sensitive environments such as those encountered in networks associated with the Internet of Things (I
Stable diffusion models reveal a persisting human and AI gap in visual creativity
While recent research suggests Large Language Models match human creative performance in divergent thinking tasks, visual creativity remains underexplored. This study compared image generation in human participants (Visual Artists and Non Artists) and using an image generation AI model (two prompting conditions with varying human input: high for Human Inspired, low for Self Guided). Human raters (N=255) and GPT4o eva
Mesh RAG: Retrieval Augmentation for Autoregressive Mesh Generation
3D meshes are a critical building block for applications ranging from industrial design and gaming to simulation and robotics. Traditionally, meshes are crafted manually by artists, a process that is time-intensive and difficult to scale. To automate and accelerate this asset creation, autoregressive models have emerged as a powerful paradigm for artistic mesh generation. However, current methods to enhance quality t
Statistical Arbitrage in Polish Equities Market Using Deep Learning Techniques
We study a systematic approach to a popular Statistical Arbitrage technique: Pairs Trading. Instead of relying on two highly correlated assets, we replace the second asset with a replication of the first using risk factor representations. These factors are obtained through Principal Components Analysis (PCA), exchange traded funds (ETFs), and, as our main contribution, Long Short Term Memory networks (LSTMs). Residua
Frugality in second-order optimization: floating-point approximations for Newton's method
Minimizing loss functions is central to machine-learning training. Although first-order methods dominate practical applications, higher-order techniques such as Newton's method can deliver greater accuracy and faster convergence, yet are often avoided due to their computational cost. This work analyzes the impact of finite-precision arithmetic on Newton steps and establishes a convergence theorem for mixed-precision
Revisiting Multimodal KV Cache Compression: A Frequency-Domain-Guided Outlier-KV-Aware Approach
Multimodal large language models suffer from substantial inference overhead since multimodal KV Cache grows proportionally with the visual input length. Existing multimodal KV Cache compression methods mostly rely on attention score to reduce cache size, which makes them are incompatible with established efficient attention kernels (e.g., FlashAttention) and ignores the contribution of value vectors to the attention
Generative Augmented Reality: Paradigms, Technologies, and Future Applications
This paper introduces Generative Augmented Reality (GAR) as a next-generation paradigm that reframes augmentation as a process of world re-synthesis rather than world composition by a conventional AR engine. GAR replaces the conventional AR engine's multi-stage modules with a unified generative backbone, where environmental sensing, virtual content, and interaction signals are jointly encoded as conditioning inputs f
Predicting Healthcare Provider Engagement in SMS Campaigns
As digital communication grows in importance when connecting with healthcare providers, traditional behavioral and content message features are imbued with renewed significance. If one is to meaningfully connect with them, it is crucial to understand what drives them to engage and respond. In this study, the authors analyzed several million text messages sent through the Impiricus platform to learn which factors infl
Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation
Audio-language pretraining (ALP) holds promise for learning general-purpose audio representation, yet remains underexplored. Crucially, there is no consensus on whether audio-language models can build effective general-purpose audio encoders, nor a systematic understanding of how pretraining objectives behave across diverse tasks and scales. We identify three key barriers: limited scale of audio-text corpora, limited
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