Record 19062026 · captured 2026-08-25
The world looked up Daveigh Chase. 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.
Daveigh Elizabeth Chase was an American actress.
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
.xyz is a top-level domain name that was proposed in ICANN's new generic top-level domain (gTLD) Program for consisting of the last three letters of the Latin-script alphabet. XYZ.com and CentralNic are the registries for the domain, which was created by entre
Oliver Tree Nickell was an American singer-songwriter, rapper, and record producer. Born in Santa Cruz, California, Tree signed to Atlantic Records in 2017 after his song "When I'm Down" went viral. He released his debut studio album Ugly Is Beautiful in July
Juneteenth, officially Juneteenth National Independence Day, is a federal holiday in the United States. It is celebrated annually on June 19 to commemorate the end of slavery in the United States. The holiday's name, first used in the 1890s, is a portmanteau o
Lionel Andrés "Leo" Messi is an Argentine professional footballer who plays as a forward for and captains both Major League Soccer (MLS) club Inter Miami and the Argentina national team. Widely regarded as one of the greatest players in history, Messi has set
The FIFA World Cup is an international association football competition among the senior men's national teams of the members of the Fédération Internationale de Football Association (FIFA), the sport's global governing body. The tournament has been held every
The Gilgo Beach serial killings were a series of murders on Long Island, New York, between 1993 and 2010. The case gained national attention in late 2010 and 2011, when police searching for a missing woman, Shannan Gilbert, discovered the remains of ten victim
Brytavious Lakeith Chambers, known professionally as Tay Keith, was an American record producer. He produced eleven Billboard Hot 100 top ten hits, including the 2018 singles "Look Alive" by BlocBoy JB and "Nonstop" by Drake, which peaked at five and two on th
Cristiano Ronaldo dos Santos Aveiro is a Portuguese professional footballer who plays as a forward for and captains the Saudi Pro League club Al-Nassr and the Portugal national team. Nicknamed CR7, he is widely regarded as one of the greatest players in histor
Since 28 February 2026, the United States and Israel have been at war with Iran and its regional allies. Hostilities broke out after US–Israeli airstrikes killed several Iranian officials, including Supreme Leader Ali Khamenei. The strikes were launched amid o
Obsession is a 2025 American supernatural horror film written, directed, and edited by Curry Barker. The film follows Bear, a music store employee who buys a supernatural toy that grants his wish for his friend Nikki to fall in love with him, which makes her b
Uzbekistan, officially the Republic of Uzbekistan, is a sovereign, doubly landlocked country located in Central Asia. It is bordered by Kazakhstan to the north, Kyrgyzstan to the northeast, Tajikistan to the southeast, Afghanistan to the south, and Turkmenista
Víctor Muñoz (footballer, born 2003)
Víctor Muñoz Villanueva is a Spanish professional footballer who plays as a left winger or forward for Premier League club Liverpool and the Spain national team.
The following notable deaths occurred in 2026. Names are reported under the date of death, in alphabetical order. A typical entry reports information in the following sequence:Name, age, country of citizenship at birth, subsequent nationality, what subject was
Murder of Reagan Simmons-Hancock
On October 9, 2020, 21-year-old Reagan Simmons-Hancock was murdered by 27-year-old Taylor Rene Parker in New Boston, Texas, United States. Parker then cut from Reagan's body her unborn daughter, Braxlynn Sage Hancock, who died the same day. Parker had previous
Harry Edward Kane is an English professional footballer who plays as a striker for Bundesliga club Bayern Munich and captains the England national team. He is regarded as one of the best players in the world, one of the best strikers of his generation, and one
Toy Story 5 is a 2026 American animated comedy-drama film produced by Pixar Animation Studios for Walt Disney Pictures. Directed by Andrew Stanton and written by Stanton and Kenna Harris, it is the fifth main installment in the Toy Story film series and the se
James David Rodríguez Rubio is a Colombian footballer who plays as an attacking midfielder. As of July 2026, he is a free agent, and his last team was Minnesota United FC of Major League Soccer (MLS). He is a international for the Colombia national football te
The FIFA Men's World Ranking is a ranking system for men's national teams in association football, first introduced in December 1992. The men's teams of the member nations of FIFA, football's world governing body, are ranked based on their game results with th
Geeta and Sanjay Chopra kidnapping case
The Geeta and Sanjay Chopra kidnapping case was a kidnapping and murder crime in New Delhi in 1978. It involved the kidnapping and subsequent murder of siblings Geeta and Sanjay by Kuljeet Singh and Jasbir Singh. Although the children were kidnapped for ransom
Widow's Bay is an American comedy horror television series created by Katie Dippold for Apple TV, and starring Matthew Rhys, Kate O'Flynn, Kevin Carroll, Dale Dickey, Kingston Rumi Southwick, and Stephen Root. The series is set in the fictional New England isl
List of FIFA World Cup top goalscorers
Players have scored more than 3,000 goals in the 23 men's FIFA World Cup tournaments, the goal record includes own goals scored, but not counting penalty shoot-outs. Since the first goal, by French player Lucien Laurent in 1930, nearly 1,300 footballers have s
Disclosure Day is a 2026 American science fiction thriller film directed and produced by Steven Spielberg from a screenplay by David Koepp, based on a story by Spielberg. The film stars an ensemble cast, including Emily Blunt, Josh O'Connor, Colin Firth, Eve H
The FIFA World Cup is an international association football competition contested by the senior men's national teams of the Fédération Internationale de Football Association (FIFA), the sport's global governing body. The championship has been awarded every fou
Spider-Man: Brand New Day is a 2026 American superhero film based on the Marvel Comics character Spider-Man. Produced by Columbia Pictures, Marvel Studios, and Pascal Pictures, and distributed by Sony Pictures Releasing, it is the 38th film in the Marvel Cinem
Tellement proches is a 2009 French film directed by Éric Toledano and Olivier Nakache, starring Vincent Elbaz, Isabelle Carré, François-Xavier Demaison, Audrey Dana, Omar Sy, and Joséphine de Meaux.
Thomas Tuchel is a German professional football manager and former player who is the manager of the England national team.
Jalen Marquis Brunson, nicknamed "Captain Clutch", and the "King of New York" is an American professional basketball player for the New York Knicks of the National Basketball Association (NBA). The son of former NBA guard Rick Brunson, he played college basket
Neatsville is an unincorporated community in Adair County, in the U.S. state of Kentucky. It is located at the junction of Kentucky Route 206 and Kentucky Route 76. Its elevation is 705 feet (215 m). For unknown reasons, the town's name was spelled as Neetsvil
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Topological and Statistical Behavior Classifiers for Tracking Applications
We introduce the first unified theory for target tracking using Multiple Hypothesis Tracking, Topological Data Analysis, and machine learning. Our string of innovations are 1) robust topological features are used to encode behavioral information, 2) statistical models are fitted to distributions over these topological features, and 3) the target type classification methods of Wigren and Bar Shalom et al. are employed
Using Persistent Homology to Quantify a Diurnal Cycle in Hurricane Felix
The diurnal cycle of tropical cyclones (TCs) is a daily cycle in clouds that appears in satellite images and may have implications for TC structure and intensity. The diurnal pattern can be seen in infrared (IR) satellite imagery as cyclical pulses in the cloud field that propagate radially outward from the center of nearly all Atlantic-basin TCs. These diurnal pulses, a distinguishing characteristic of the TC diurna
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Unstructured text provides decision-makers with a rich data source in many domains, ranging from product reviews in retail to nursing notes in healthcare. To leverage this information, words are typically translated into word embeddings -- vectors that encode the semantic relationships between words -- through unsupervised learning algorithms such as matrix factorization. However, learning word embeddings from new do
IdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models
The field of vision-and-language (VL) understanding has made unprecedented progress with end-to-end large pre-trained VL models (VLMs). However, they still fall short in zero-shot reasoning tasks that require multi-step inferencing. To achieve this goal, previous works resort to a divide-and-conquer pipeline. In this paper, we argue that previous efforts have several inherent shortcomings: 1) They rely on domain-spec
Constructing Colloquial Dataset for Persian Sentiment Analysis of Social Microblogs
Introduction: Microblogging websites have massed rich data sources for sentiment analysis and opinion mining. In this regard, sentiment classification has frequently proven inefficient because microblog posts typically lack syntactically consistent terms and representatives since users on these social networks do not like to write lengthy statements. Also, there are some limitations to low-resource languages. The Per
Benign overfitting beyond prediction: The ordinary least squares interpolator
Recent advances in deep learning have highlighted the phenomenon of benign overfitting in overparameterized statistical models, sparking significant interest in understanding its foundations. Owing to its simplicity and practical relevance, the ordinary least squares (OLS) interpolator has become a key object of study for gaining theoretical insight into this phenomenon. While the properties of OLS are well understoo
Analysing Rescaling, Discretisation, and Linearisation in RNNs for Neural System Modelling
Recurrent Neural Networks (RNNs) are widely used to model neural activity in Computational Neuroscience. Here, we explore the mathematical foundations of three fundamental procedures that can be implemented: temporal rescaling, discretisation, and linearisation. These techniques provide crucial tools for characterising the behaviour of RNNs, offering insights into their temporal dynamics, facilitating practical compu
Representing Piecewise-Linear Functions by Functions with Minimal Arity
Any continuous piecewise-linear function $F\colon \mathbb{R}^{n}\to \mathbb{R}$ can be represented as a linear combination of $\max$ functions of at most $n+1$ affine-linear functions. In our previous paper [``Representing piecewise linear functions by functions with small arity'', AAECC, 2023], we showed that this upper bound of $n+1$ arguments is tight. In the present paper, we extend this result by establi
Multimode optical fibres are hair-thin strands of glass that efficiently transport light. They promise next-generation medical endoscopes that provide unprecedented sub-cellular image resolution deep inside the body. However, confining light to such fibres means that images are inherently scrambled in transit. Conventionally, this scrambling has been compensated by pre-calibrating how a specific fibre scrambles light
Annually and globally, over three billion radiography examinations and computer tomography scans result in mostly unstructured radiology reports containing free text. Despite the potential benefits of structured reporting, its adoption is limited by factors such as established processes, resource constraints and potential loss of information. However, structured information would be necessary for various use cases, i
Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinations
Multi-view learning often struggles to effectively leverage images captured from diverse angles and locations. Learning methods for unstructured multi-view images remain largely underexplored. We propose a novel Hierarchical Mutual Distillation for Multi-View Fusion (HMDMV) method, which can handle both structured and unstructured multi-view scenarios. It makes predictions utilizing all possible view combinations: si
Uncertainty-aware deep learning (DL) models recently gained attention in fault diagnosis as a way to promote the reliable detection of faults when out-of-distribution (OOD) data arise from unseen faults (epistemic uncertainty) or the presence of noise (aleatoric uncertainty). In this paper, we present the first comprehensive comparative study of state-of-the-art uncertainty-aware DL architectures for fault diagnosis
An Experimental Study on Fairness-aware Machine Learning for Credit Scoring Problems
The digitalization of credit scoring has become essential for financial institutions and commercial banks, especially in the era of digital transformation. Machine learning techniques are commonly used to evaluate customers' creditworthiness. However, the predicted outcomes of machine learning models can be biased toward protected attributes, such as race or gender. Numerous fairness-aware machine learning models
UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the primary challenges include behavioral multimodality and closed-loop distributional shifts. In this study, we formulate a unified mixture model (UniMM) framework for generating multimodal agent behaviors, which can cover the mainstream methods
A Unified Perspective on the Dynamics of Deep Transformers
Transformers, which are state-of-the-art in most machine learning tasks, represent the data as sequences of vectors called tokens. This representation is then exploited by the attention function, which learns dependencies between tokens and is key to the success of Transformers. However, the iterative application of attention across layers induces complex dynamics that remain to be fully understood. To analyze these
Adversarial Dependence Minimization
Minimally redundant representations are typically learned by minimizing feature covariance. However, covariance-based methods fail to eliminate all dependencies/redundancies, as linearly uncorrelated variables can still exhibit nonlinear relationships. To address this, we introduce ADM, a differentiable algorithm that minimizes statistical dependence between feature dimensions through an adversarial game: auxiliary n
The drastic changes in the global economy, geopolitical conditions, and disruptions such as the COVID-19 pandemic have impacted the cost of living and quality of life. It is essential to comprehend the long-term implications of the cost of living and quality of life in major economies. A transparent and comprehensive living index must include multiple dimensions of living conditions. In this study, we present an appr
Social media platforms frequently impose restrictive policies to moderate user content, prompting the emergence of creative evasion language strategies. This paper presents a multi-agent framework based on Large Language Models (LLMs) to simulate the iterative evolution of language strategies under regulatory constraints. In this framework, participant agents, as social media users, continuously evolve their language
MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing
We introduce MeshPad, a generative approach that creates 3D meshes from sketch inputs. Building on recent advances in artist-reminiscent triangle mesh generation, our approach addresses the need for interactive mesh creation. To this end, we focus on enabling consistent edits by decomposing editing into 'deletion' of regions of a mesh, followed by 'addition' of new mesh geometry. Both operations are i
A Deep Generative Model for Resting-State EEG Synthesis and Transferable Representation Learning
Resting-state EEG provides a non-invasive view of spontaneous brain activity, but extracting meaningful patterns is often limited by scarce high-quality data and reliance on manually engineered features. Generative adversarial networks (GANs) can synthesize neural signals and learn transferable representations directly from raw data, a dual capability that remains underexplored in EEG research. Here, we introduce RES
The Morse Transform for Discrete Shape Analysis
The geometry of an object plays a vital role in modulating its interactions with the physical world. It nevertheless remains difficult to describe geometric information numerically for the purposes of statistical inference or classification tasks. Here, we introduce a new topological transform which leverages directional piecewise-linear Morse theory to quantify the geometry of an embedded object by cataloguing criti
Crashworthiness is a key performance measure in the design of safety-critical vehicle panel components such as B-pillars. Finite element (FE) simulations are widely used to evaluate crash responses but remain computationally expensive for large-scale, nonlinear impact scenarios, particularly when integrated into iterative design and optimisation processes. Although machine learning-based surrogate models have been de
OncoReg: Medical Image Registration for Oncological Challenges
In modern cancer research, the vast volume of medical data generated is often underutilised due to challenges related to patient privacy. The OncoReg Challenge addresses this issue by enabling researchers to develop and validate image registration methods through a two-phase framework that ensures patient privacy while fostering the development of more generalisable AI models. Phase one involves working with a public
Med-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation
Automated medical report generation (MRG) is increasingly used to reduce the burden of manual reporting and for decision support. Large vision-language models (LVLMs) hold great promise for automated MRG due to their fine-grained image-text alignment and advanced text-generation capabilities. Currently, state-of-the-art MRGs primarily focus on adapting pre-trained LVLMs with direct supervised fine-tuning (SFT), a fin
TerraMind: Large-Scale Generative Multimodality for Earth Observation
We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale representations combining both token-level and pixel-level data across modalities. On a token level, TerraMind encodes high-level contextual information to learn cross-modal relationships, while on a pixel level, TerraMind leverages fine-g
Notable events recorded on this day and month across all years.