Record 07072026 · captured 2026-08-25
The world looked up Erling Haaland. 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.
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
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
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
Folarin Jerry Balogun is a professional soccer player who plays as a striker for Ligue 1 club Monaco and the United States national team.
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
Neymar da Silva Santos Júnior, known mononymously as Neymar, is a Brazilian professional footballer who plays as an attacking midfielder or a forward for Campeonato Brasileiro Série A club Santos. A goalscorer and playmaker, he is known for his dribbling, tech
Arthur Fery is a British professional tennis player. He has a career-high ATP singles ranking of world No. 36 achieved on 13 July 2026 and a doubles ranking of No. 201 achieved on 29 July 2024. His breakthrough came at the 2026 Wimbledon Championships, reachin
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
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
Julián Andrés Quiñones Quiñones is a professional footballer who plays as a forward or winger for Saudi Pro League club Al-Qadsiah. Born in Colombia, he represents the Mexico national team.
Lamine Yamal Nasraoui Ebana, commonly known as Lamine Yamal, is a Spanish professional footballer who plays as a right winger for the La Liga club Barcelona and the Spain national team. He is widely regarded as one of the best players in the world.
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
Estadio Azteca, officially known as Estadio Banorte for sponsorship reasons, is a football stadium located in Coyoacán, Mexico City. At an elevation of 2,241 meters (7,352 ft) above sea level it is the official home of Club América of Liga MX and the Mexico na
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
Giovanni Vincenzo "Gianni" Infantino is a Swiss football administrator who has served as the president of FIFA since 2016. He was previously Secretary General of UEFA from 2009 to 2016, where he formalised the body's financial regulations and oversaw tournamen
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
Raúl Alonso Jiménez Rodríguez is a Mexican professional footballer who plays as a striker for EFL Championship club Wolverhampton Wanderers and the Mexico national team.
Jarell Amorin Quansah is an English professional footballer who plays as a centre-back for Bundesliga club Bayer Leverkusen and the England national team.
Anthony Michael Gordon is an English professional footballer who plays as a left winger for La Liga club Barcelona and the England national team.
Lauren Diane Bennett-Wormald was an English singer from Meopham, Kent. She was a member of Paradiso Girls, who were known for the song "Patron Tequila", and G.R.L., who were featured on Pitbull's "Wild Wild Love" and were known for their song "Ugly Heart". She
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
Yandex LLC is a Russian technology company that provides Internet-related products and services including a web browser, search engine, cloud computing, web mapping, online food ordering, streaming media, online shopping, and a ridesharing company.
Jaswant Singh Khalra (1952–1995) was an Indian human rights activist. He was one of the most prominent human rights activists in Punjab. He gained international recognition after uncovering evidence of thousands of alleged extrajudicial killings, enforced disa
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
.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
England national football team
The England national football team have represented England in men's international football since the first international match in 1872. They are governed by The Football Association (FA), the governing body for football in England, which is affiliated with UE
Thomas Tuchel is a German professional football manager and former player who is the manager of the England national team.
Alfie Haaland is a Norwegian former professional footballer who played as a right-back or midfielder. Haaland played in England with Nottingham Forest, Leeds United, and Manchester City, and earned 34 caps for Norway. He is the father of Manchester City and No
The 2030 FIFA World Cup is scheduled to be the 24th FIFA World Cup, the quadrennial international football tournament that is contested by the men's national teams of the member associations of FIFA. The tournament is planned to be jointly hosted by Morocco, P
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Accuracy, Uncertainty, and Adaptability of Automatic Myocardial ASL Segmentation using Deep CNN
PURPOSE: To apply deep CNN to the segmentation task in myocardial arterial spin labeled (ASL) perfusion imaging and to develop methods that measure uncertainty and that adapt the CNN model to a specific false positive vs. false negative tradeoff. METHODS: The Monte Carlo dropout (MCD) U-Net was trained on data from 22 subjects and tested on data from 6 heart transplant recipients. Manual segmentation and regional myo
Linear stability analysis for large dynamical systems on directed random graphs
We present a linear stability analysis of stationary states (or fixed points) in large dynamical systems defined on random directed graphs with a prescribed distribution of indegrees and outdegrees. We obtain two remarkable results for such dynamical systems: First, infinitely large systems on directed graphs can be stable even when the degree distribution has unbounded support; this result is surprising since their
In this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of facts, and a priority relation between conflicting facts. In the database setting, a closely related scenario has been studied and led to the definition of three different notions of optimal repairs (global, Pareto, and completion) of a prioritized inconsistent database. After t
EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentation
We study multi-sensor fusion for 3D semantic segmentation that is important to scene understanding for many applications, such as autonomous driving and robotics. Existing fusion-based methods, however, may not achieve promising performance due to the vast difference between the two modalities. In this work, we investigate a collaborative fusion scheme called perception-aware multi-sensor fusion (PMF) to effectively
The probabilistic linguistic term has been proposed to deal with probability distributions in provided linguistic evaluations. However, because it has some fundamental defects, it is often difficult for decision-makers to get reasonable information of linguistic evaluations for group decision making. In addition, weight information plays a significant role in dynamic information fusion and decision making process. Ho
Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment
Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout form naturally requires estimating human's body pose. However, off-the-shelf pose estimators struggle to perform well on the videos recorded in gym scenarios due to factors such as camera angles, occlusion from gym equipment, illumination, and clothing. To aggravate the probl
An Accelerated Stochastic Variance-Reduced Algorithm for Entropic Wasserstein Barycenters
Fixed-support Wasserstein barycenters average probability distributions while accounting for the geometry of the support. We study the entropically regularized Wasserstein barycenter problem with a fixed regularization parameter and propose an accelerated stochastic variance-reduced primal-dual algorithm. The proposed algorithm uses a semi-dual finite-sum structure in which each stochastic gradient requires only one
Structure-Guided Self-Supervised Matching for One-Shot Medical Landmark Detection
Medical landmark detection usually requires accurate expert annotations, which are laborious and difficult to scale across anatomical regions. In this work, we study an extreme annotation-efficient setting where only a single annotated template image is available. We propose SGB-Match, a structure-guided coarse-to-fine self-supervised matching framework for one-shot medical landmark detection. The framework first lea
Building detection and change detection using remote sensing images can help urban and rescue planning. Moreover, they can be used for building damage assessment after natural disasters. Currently, most of the existing models for building detection use only one image (pre-disaster image) to detect buildings. This is based on the idea that post-disaster images reduce the model's performance because of presence of
Reliability measures associated with the prediction of the machine learning models are critical to strengthening user confidence in artificial intelligence. Therefore, those models that provide not only predictions, but also reliability, enjoy greater popularity. In the field of recommender systems, reliability is crucial, since users tend to prefer those recommendations that are sure to interest them, that is, high
Observable Perfect Equilibrium
While Nash equilibrium has emerged as the central game-theoretic solution concept, many important games contain several Nash equilibria and we must determine how to select between them in order to create real strategic agents. Several Nash equilibrium refinement concepts have been proposed and studied for sequential imperfect-information games, the most prominent being trembling-hand perfect equilibrium, quasi-perfec
Analyzing the behavior of complex interdependent networks requires complete information about the network topology and the interdependent links across networks. For many applications such as critical infrastructure systems, understanding network interdependencies is crucial to anticipate cascading failures and plan for disruptions. However, data on the topology of individual networks are often publicly unavailable du
Cross-validation is one of the most widely used tools for risk estimation and model selection in statistics and machine learning, yet its theoretical properties when embedded in a learning procedure remain insufficiently understood. This paper develops a general, distribution-free framework for learning via model selection with cross-validation risk estimation within classical statistical learning theory. We establis
Proportionally Representative Clustering
In recent years, there has been a surge in effort to formalize notions of fairness in machine learning. We focus on centroid clustering--one of the fundamental tasks in unsupervised machine learning. We propose a new axiom ``proportionally representative fairness'' (PRF) that is designed for clustering problems where the selection of centroids reflects the distribution of data points and how tightly they are
Efficient Cross-Validation for Sparse Linear Regression
Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that explains the relationship between covariates and the response in an interpretable manner. To choose hyperparameters that control the sparsity level and amount of regularization, practitioners commonly use k-fold cross-validation. However, cross-validation substantially increase
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
Benchmarks are crucial in the development of machine learning algorithms, with available environments significantly influencing reinforcement learning (RL) research. Traditionally, RL environments run on the CPU, which limits their scalability with typical academic compute. However, recent advancements in JAX have enabled the wider use of hardware acceleration, enabling massively parallel RL training pipelines and en
Towards Trustworthy AI Software Development Assistance
It is expected that in the near future, AI software development assistants will play an important role in the software industry. However, current software development assistants tend to be unreliable, often producing incorrect, unsafe, or low-quality code. We seek to resolve these issues by introducing a holistic architecture for constructing, training, and using trustworthy AI software development assistants. In the
NU-Class Net: A Novel Approach for Video Quality Enhancement
Video content has experienced a surge in popularity, asserting its dominance over internet traffic and Internet of Things (IoT) networks. Video compression has long been regarded as the primary means of efficiently managing the substantial multimedia traffic generated by video-capturing devices. Nevertheless, video compression algorithms entail significant computational demands in order to achieve substantial compres
DrawTalking: Building Interactive Worlds by Sketching and Speaking
We introduce DrawTalking, an approach to building and controlling interactive worlds by sketching and speaking while telling stories. It emphasizes user control and flexibility, and gives programming-like capability without requiring code. An early open-ended study with our prototype shows that the mechanics resonate and are applicable to many creative-exploratory use cases, with the potential to inspire and inform r
Learning to Visually Connect Actions and their Effects
We introduce the novel concept of visually Connecting Actions and Their Effects (CATE) in video understanding. CATE can have applications in areas like task planning and learning from demonstration. We identify and explore two different aspects of the concept of CATE: Action Selection (AS) and Effect-Affinity Assessment (EAA), where video understanding models connect actions and effects at semantic and fine-grained l
TERC: A Transfer Entropy Redundancy Criterion for State Variable Selection in Reinforcement Learning
Identifying the most suitable variables to represent the state is a fundamental challenge in Reinforcement Learning (RL). These variables must efficiently capture the information necessary for making optimal decisions. In order to address this problem, in this paper, we introduce the Transfer Entropy Redundancy Criterion (TERC), an information-theoretic criterion, which determines if there is entropy transferred from
Unitarity is a useful principle for stabilizing deep neural networks, but in graph neural networks (GNNs) instability is induced not only by learnable parameters but also by the graph propagation operator. Motivated by this distinction, we propose Graph Unitary Message Passing (GUMP), a message-passing framework that uses a unitary propagation operator on a transformed graph to avoid graph-induced exponential decay u
Causal video question answering (QA) has garnered increasing interest, yet existing datasets often lack depth in causal reasoning. To address this gap, we capitalize on the unique properties of cartoons and construct CausalChaos!, a novel, challenging causal Why-QA dataset built upon the iconic "Tom and Jerry" cartoon series. Cartoons use the principles of animation that allow animators to create expressive,
Super-Resolution (SR) is a time-hallowed image processing problem that aims to improve the quality of a Low-Resolution (LR) sample up to the standard of its High-Resolution (HR) counterpart. We aim to address this by introducing Super-Resolution Generator (SuRGe), a fully-convolutional Generative Adversarial Network (GAN)-based architecture for SR. We show that distinct convolutional features obtained at increasing d
Nonparametric Control Koopman Operators
This paper presents a novel Koopman composition operator representation framework for control systems in reproducing kernel Hilbert spaces (RKHSs) that is free of explicit dictionary or input parametrizations. By establishing fundamental equivalences between different model representations, we are able to close the gap of control system operator learning and infinite-dimensional regression, enabling various empirical
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