Record 18062026 · captured 2026-08-25
The world looked up List of FIFA World Cup top goalscorers. 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.
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
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 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
Daveigh Elizabeth Chase was an American actress.
Luca Zinedine Zidane is a professional footballer who plays as a goalkeeper for Segunda División club Leganés. Born in France, he plays for the Algeria national team.
.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
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
Zinedine Yazid Zidane, popularly known as Zizou, is a French professional football manager and former player who played as an attacking midfielder. He is the head coach of the France national team. Widely regarded as one of the greatest players of all time, Zi
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
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
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
Kylian Mbappé Lottin is a French professional footballer who plays as a forward for La Liga club Real Madrid and captains the France national team. Widely regarded as one of the best players in the world and one of the greatest French players of all time, he i
Luka Modrić is a Croatian professional footballer who plays as a central midfielder for Serie A club AC Milan and captains the Croatia national team. He is widely regarded as one of the greatest midfielders of all time and as the greatest Croatian footballer i
DR Congo national football team
The DR Congo national football team, recognised by FIFA as Congo DR and by CAF as DR Congo, represents the Democratic Republic of the Congo in men's international football. It is controlled by the Congolese Association Football Federation. They are nicknamed L
Erling Braut Haaland is a Norwegian professional footballer who plays as a striker for Premier League club Manchester City and the Norway national team. Regarded as one of the best players in the world and the greatest Norwegian player of all time, he is known
Democratic Republic of the Congo
The Democratic Republic of the Congo (DRC), also known as the DR Congo, Congo-Kinshasa, or simply the Congo, and formerly named Zaire, is a country in Central Africa. By land area, it is the second-largest country in Africa and the eleventh-largest in the worl
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
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
Thomas Tuchel is a German professional football manager and former player who is the manager of the England national team.
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
Jeremy Charles Robert Clarkson is an English television presenter, journalist, author and farmer who is best known for hosting the motoring television programmes Top Gear (2002–2015) and The Grand Tour (2016–2024) alongside Richard Hammond and James May. He ho
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
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
Cape Verde, also referred to in English by its Portuguese name Cabo Verde, and known officially as the Republic of Cabo Verde, is an archipelagic country in the eastern Atlantic Ocean, off the coast of West Africa. It consists of ten volcanic islands with a co
Jude Victor William Bellingham is an English professional footballer who plays as a midfielder for La Liga club Real Madrid and the England national team. Regarded as one of the best players in the world, he is known for his athleticism and ball-winning abilit
The 2022 FIFA World Cup was the 22nd FIFA World Cup, the quadrennial world championship for national football teams organised by FIFA. It took place in Qatar from 20 November to 18 December 2022, after the country was awarded the hosting rights in 2010. It was
Algeria, officially the People's Democratic Republic of Algeria, is a country in the Maghreb region of North Africa. Spanning over 2,381,741 square kilometres (919,595 sq mi), it is the largest country in Africa and the tenth largest in the world. It is border
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 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
Miroslav Josef Klose is a professional football manager and former player who is head coach of 2. Bundesliga club 1. FC Nürnberg. Born in Poland, Klose played as a striker for the Germany national team.
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Learning transport cost from subset correspondence
Learning to align multiple datasets is an important problem with many applications, and it is especially useful when we need to integrate multiple experiments or correct for confounding. Optimal transport (OT) is a principled approach to align datasets, but a key challenge in applying OT is that we need to specify a transport cost function that accurately captures how the two datasets are related. Reliable cost funct
The automated analysis of heterogeneous natural textures is frequently hindered by physical damage and data loss, presenting a significant challenge to computer vision. While deep learning has shown success in controlled environments, its application to complex geological materials under conditions of incomplete information remains underexplored. This study presents an integrated framework for the inpainting and clas
Going Beyond the Cookie Theft Picture Test: Detecting Cognitive Impairments using Acoustic Features
Standardized tests play a crucial role in the detection of cognitive impairment. Previous work demonstrated that automatic detection of cognitive impairment is possible using audio data from a standardized picture description task. The presented study goes beyond that, evaluating our methods on data taken from two standardized neuropsychological tests, namely the German SKT and a German version of the CERAD-NB, and a
RNN(p) for Power Consumption Forecasting
An elementary Recurrent Neural Network that operates on p time lags, called an RNN(p), is the natural generalisation of a linear autoregressive model ARX(p). It is a powerful forecasting tool for variables displaying inherent seasonal patterns across multiple time scales, as is often observed in energy, economic, and financial time series. The architecture of RNN(p) models, characterised by structured feedbacks acros
FingerFlex: Inferring Finger Trajectories from ECoG signals
Motor brain-computer interface (BCI) development relies critically on neural time series decoding algorithms. Recent advances in deep learning architectures allow for automatic feature selection to approximate higher-order dependencies in data. This article presents the FingerFlex model - a convolutional encoder-decoder architecture adapted for finger movement regression on electrocorticographic (ECoG) brain data. St
Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization
In real-world applications, a machine learning model is required to handle an open-set recognition (OSR), where unknown classes appear during the inference, in addition to a domain shift, where the data distribution differs between the training and inference phases. Domain generalization (DG) aims to handle the domain shift situation where the target domain of the inference phase is inaccessible during the model trai
A DeepLearning Framework for Dynamic Estimation of Origin-Destination Sequence
OD matrix estimation is a critical problem in the transportation domain. The principle method uses the traffic sensor measured information such as traffic counts to estimate the traffic demand represented by the OD matrix. The problem is divided into two categories: static OD matrix estimation and dynamic OD matrices sequence(OD sequence for short) estimation. The above two face the underdetermination problem caused
Large-Scale OD Matrix Estimation with A Deep Learning Method
The estimation of origin-destination (OD) matrices is a crucial aspect of Intelligent Transport Systems (ITS). It involves adjusting an initial OD matrix by regressing the current observations like traffic counts of road sections (e.g., using least squares). However, the OD estimation problem lacks sufficient constraints and is mathematically underdetermined. To alleviate this problem, some researchers incorporate a
Recursive Joint Simulation in Games
Game-theoretic dynamics between AI agents could differ from traditional human-human interactions in various ways. One such difference is that it may be possible to accurately simulate an AI agent, for example because its source code is known. Such an agent would then be fundamentally uncertain whether it is in the real world or in a simulation. Our aim is to explore ways of leveraging this possibility to achieve more
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
The development of Time-Series Forecasting (TSF) models is often constrained by the lack of comprehensive datasets, especially in Global Station Weather Forecasting (GSWF), where existing datasets are small, temporally short, and spatially sparse. To address this, we introduce WEATHER-5K, a large-scale observational weather dataset that better reflects real-world conditions, supporting improved model training and eva
R&B -- Rhythm and Brain: Cross-subject Decoding of Music from Human Brain Activity
Music is a universal phenomenon that profoundly influences human experiences across cultures. This study investigates whether music can be decoded from human brain activity measured with functional MRI (fMRI) during its perception. Leveraging recent advancements in extensive datasets and pre-trained computational models, we construct mappings between neural data and latent representations of musical stimuli. Our appr
Real-world application models are commonly deployed in dynamic environments, where the target domain distribution undergoes temporal changes. Continual Test-Time Adaptation (CTTA) has recently emerged as a promising technique to gradually adapt a source-trained model to continually changing target domains. Despite recent advancements in addressing CTTA, two critical issues remain: 1) Fixed thresholds for pseudo-label
Optimizing Incomplete, Large-Scale and Sparse Multi-Graph Matching in Bioimaging
Multi-graph matching is a fundamental problem in computer vision. Our work is motivated by a challenging application in bioimaging, where dozens or even hundreds of 3D microscopy images of worms must be brought into correspondence. Existing datasets do not cover this large-scale regime, and virtually all existing methods are inapplicable because they assume a complete or dense problem setting. To support further rese
Fully tensorial approach to hypercomplex-valued neural networks
A fully tensorial theoretical framework for hypercomplex-valued neural networks is presented. The proposed approach enables neural network architectures to operate on data defined over arbitrary finite-dimensional algebras. The central observation is that algebra multiplication can be represented by a rank-three tensor, which allows all algebraic operations in neural network layers to be formulated in terms of standa
VGGHeads: 3D Multi Head Alignment with a Large-Scale Synthetic Dataset
Human head detection, keypoint estimation, and 3D head model fitting are essential tasks with many applications. However, traditional real-world datasets often suffer from bias, privacy, and ethical concerns, and they have been recorded in laboratory environments, which makes it difficult for trained models to generalize. Here, we introduce \method -- a large-scale synthetic dataset generated with diffusion models fo
Recognizing and Reconstructing a Multi-Unit Floor Plan
Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, due to a lack of 3D-representations, which are available only in limited amounts for some new building
Media Framing through the Lens of Event-Centric Narratives
From a communications perspective, a frame defines the packaging of the language used in such a way as to encourage certain interpretations and to discourage others. For example, a news article can frame immigration as either a boost or a drain on the economy, and thus communicate very different interpretations of the same phenomenon. In this work, we argue that to explain framing devices we have to look at the way n
With the rapid advancement of large language models (LLMs), aligning policy models with human preferences has become increasingly critical. Direct Preference Optimization (DPO) has emerged as a promising approach for alignment, acting as an RL-free alternative to Reinforcement Learning from Human Feedback (RLHF). Despite DPO's various advancements and inherent limitations, an in-depth review of these aspects is c
Provable quantum speedups for computing persistence in topological data analysis
Topological data analysis (TDA) aims to extract noise-robust features from a data set by examining the number and persistence of holes in its topology. We provide an efficient quantum algorithm for a computational problem closely related to a core task in TDA -- determining whether a given hole persists across different length scales. Further, we prove the problem itself is $\mathsf{BQP}_1$-hard, implying that a clas
This paper presents the development of machine learning (ML) models to predict hypoxemia severity during emergency triage, especially in Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) events, using physiological data from medical-grade sensors. Gradient Boosting Models (XGBoost, LightGBM, CatBoost) and sequential models (LSTM, GRU) were trained on physiological and demographic data from the MIMIC-
Scalable Batch Bayesian Optimization Via Subspace Acquisition Functions
Extending Bayesian optimization to batch evaluation can enable the designer to make the most use of parallel computing technology. However, most of current batch approaches do not scale well with the batch size. That is, their optimization efficiencies often deteriorate as the batch size increases. To address this issue, we propose a simple and efficient approach to extend Bayesian optimization to large-scale batch e
Online Episodic Memory Visual Query Localization with Egocentric Streaming Object Memory
Episodic memory retrieval enables wearable cameras to recall objects or events previously observed in video. However, existing formulations assume an "offline" setting with full video access at query time, limiting their applicability in real-world scenarios with power and storage-constrained wearable devices. Towards more application-ready episodic memory systems, we introduce Online Visual Query 2D (OVQ2D),
MORTAR: Multi-turn Metamorphic Testing for LLM-based Dialogue Systems
With the widespread application of LLM-based dialogue systems in daily life, quality assurance has become more important than ever. Recent research has successfully introduced methods to identify unexpected behaviour in single-turn testing scenarios. However, multi-turn interaction is the common real-world usage of dialogue systems, yet testing methods for such interactions remain underexplored. This is largely due t
The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment
The emergence of large language models (LLMs) has sparked discussion on Artificial Superintelligence (ASI), a hypothetical AI system that surpasses human intelligence. Although ASI remains hypothetical and far beyond current AI capabilities, discussing its potential and exploring its feasibility and potential risks is critical for the development of future AI systems. The idea of superalignment originates from scalab
ScholaWrite: A Dataset of End-to-End Scholarly Writing Process
Writing is a cognitively demanding activity that requires constant decision-making, heavy reliance on working memory, and frequent shifts between tasks of different goals. To build writing assistants that truly align with writers' cognition, we must capture and decode the complete thought process behind how writers transform ideas into final texts. We present ScholaWrite, the first dataset of end-to-end scholarly
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