Record 20072026 · captured 2026-08-25
The world looked up Lamine Yamal. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
Complete record JSON
What the most people looked up, ranked by Wikipedia pageviews for that day.
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 Odyssey is a 2026 epic action fantasy film written and directed by Christopher Nolan, who produced it with his wife Emma Thomas. An adaptation of Homer's ancient Greek epic poem the Odyssey, it stars an ensemble cast including Matt Damon, Tom Holland, Anne
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
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 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
Shakira Isabel Mebarak Ripoll, known mononymously as Shakira, is a Colombian singer-songwriter, dancer, and record producer. Referred to as the "Queen of Latin Music", she has had a significant impact on the musical landscape of Latin America and has been cred
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
Ferran Torres García is a Spanish professional footballer who plays as a forward or winger for Ligue 1 club Paris Saint-Germain and the Spain national team.
Nicholas Williams Arthuer is a Spanish professional footballer who plays as a winger for La Liga club Athletic Bilbao and the Spain national team. He is recognised for his speed and dribbling skills.
Ryan Fox is a New Zealand professional golfer who plays on the European Tour and the PGA Tour. He has won one major championship, the 2026 Open Championship.
The final match of the 2026 FIFA World Cup—the 23rd edition of the FIFA competition for men's national soccer teams—was played at MetLife Stadium in East Rutherford, New Jersey, part of the New York metropolitan area, on July 19, 2026. It was contested by Spai
The Odyssey is one of two major epics of ancient Greek literature attributed to Homer. It is one of the oldest surviving works of literature and remains popular with modern audiences. Like the Iliad, the Odyssey is divided into 24 books. It follows the heroic
The Spain national football team have represented Spain in men's international football competition since 1920, and are governed by the Royal Spanish Football Federation. They are the reigning World and European champions, having won the most recent FIFA World
Emory Andrew Tate III is an American and British social media personality and former professional kickboxer who built a webcam pornography business before gaining notoriety for promoting various highly controversial positions in the manosphere. His commentary
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
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
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
MetLife Stadium is a multi-purpose stadium located at the Meadowlands Sports Complex in East Rutherford, New Jersey, five miles (8 km) west of New York City. Opened in 2010, it replaced Giants Stadium and serves as the home for the New York Giants and New York
Rodrigo Hernández Cascante, known simply as Rodri or Rodrigo, is a Spanish professional footballer who plays as a defensive midfielder for La Liga club Barcelona and captains the Spain national team. Widely regarded as one of the best midfielders in the world,
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
Marc Cucurella Saseta is a Spanish professional footballer who plays as a left-back or left wing-back for La Liga club Real Madrid and the Spain national team. He is considered to be one of the best left-backs in the world.
Matthew Paige Damon is an American actor, film producer, and screenwriter. He was ranked among Forbes's most bankable stars in 2007, and in 2010 was one of the highest-grossing actors of all time. He has received various awards and nominations, including an Ac
Leandro Daniel Paredes is an Argentine professional footballer who plays as a defensive midfielder for Argentine Primera División club Boca Juniors and the Argentina national team. He previously played for Roma, Zenit Saint Petersburg and Paris Saint-Germain,
Alexis Mac Allister is an Argentine professional footballer who plays as a midfielder for Premier League club Liverpool and the Argentina national team. He has been praised for his passing range, tactical awareness, and ability to control the tempo of play.
Pau Cubarsí Paredes is a Spanish professional footballer who plays as a centre-back for La Liga club Barcelona and the Spain national team. He is considered one of the best young defenders in the world.
Argentina, officially the Argentine Republic, is a country in the far south of South America. It covers an area of 2,780,085 km2 (1,073,397 mi2), making it the second-largest country in South America after Brazil, the fourth-largest country in the Americas, an
Gerard Piqué Bernabeu is a Spanish former professional footballer who played as a centre-back. He is considered to be one of the greatest defenders of his generation and is one of the most decorated players with 37 trophies. In 2022, he founded the Kings Leagu
Damián Emiliano Martínez Romero, also known as Dibu Martínez, is an Argentine professional footballer who plays as a goalkeeper for Premier League club Aston Villa and the Argentina national team. Known as a specialist in saving penalty kicks, he is often rega
Luis de la Fuente (footballer, born 1961)
Luis de la Fuente Castillo is a Spanish professional football manager and former player who played as a left-back. He is the manager of the Spain national team.
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Representation Recycling for Streaming Video Analysis
We present StreamDEQ, a method that aims to infer frame-wise representations on videos with minimal per-frame computation. Conventional deep networks perform feature extraction from scratch at each frame in the absence of ad-hoc solutions. We instead aim to build streaming recognition models that can natively exploit temporal smoothness between consecutive video frames. We observe that the recently emerging implicit
Explainable Artificial Intelligence (XAI) is essential for trustworthy AI in healthcare, yet many existing methods rely on technical explanations that are difficult for clinicians and patients to interpret. We introduce Visualized Learning for Machine Learning (VL4ML), a human-centered explainability framework that communicates model predictions and uncertainty through intuitive visual representations rather than num
Semiparametric language models (LMs) have shown promise in various Natural Language Processing (NLP) tasks. However, they utilize non-parametric memory as static storage, which lacks learning capability and remains disconnected from the internal information flow of the parametric models, limiting scalability and efficiency. Based on recent interpretability theories of LMs, we reconceptualize the non-parametric memory
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content
The mobile cloud gaming industry has been rapidly growing over the last decade. When streaming gaming videos are transmitted to customers' client devices from cloud servers, algorithms that can monitor distorted video quality without having any reference video available are desirable tools. However, creating No-Reference Video Quality Assessment (NR VQA) models that can accurately predict the quality of streaming
We present a first of its kind dataset of overhead imagery for development and evaluation of forensic tools. Our dataset consists of real, fully synthetic and partially manipulated overhead imagery generated from a custom diffusion model trained on two sets of different zoom levels and on two sources of pristine data. We developed our model to support controllable generation of multiple manipulation categories includ
Why do CNNs excel at feature extraction? A mathematical explanation
Over the past decade deep learning has revolutionized the field of computer vision, with convolutional neural network models proving to be very effective for image classification benchmarks. However, a fundamental theoretical questions remain answered: why can they solve discrete image classification tasks that involve feature extraction? We address this question in this paper by introducing a novel mathematical mode
A central question of network science is how functional properties of systems emerge from their structure. For networked dynamical systems, structure is typically captured through network measures. We investigate the relationship between these measures and stability metrics across non-linear and linear oscillators, as well as real-world power grid topologies and dynamics. We find that this relationship is highly sens
Decoupled Alignment for Robust Plug-and-Play Adaptation
We introduce a training-free safety enhancement method for aligning large language models (LLMs) without the need for supervised fine-tuning or reinforcement learning from human feedback. Our main idea is to provide a robust plug-and-play approach to prevent shadow alignment when models are adapted to downstream tasks. Specifically, we leverage knowledge distillation to extract alignment signals from well-aligned LLM
AutoSpec: Automated Generation of Neural Network Specifications
The increasing adoption of neural networks in learning-augmented systems highlights the growing need for model safety and robustness, especially in safety-critical domains. While recent advances in neural network verification offer formal guarantees on worst-case behavior, existing approaches require users to manually define model specifications, an error-prone, incomplete, and time-consuming process. In this paper,
Robust Random Graph Matching in Dense Graphs via an Approximate Message Passing Type Algorithm
In this paper, we focus on the matching recovery problem between a pair of correlated Gaussian Wigner matrices with a latent vertex correspondence. We are particularly interested in a robust version of this problem such that our observation is a perturbed input $(A+E,B+F)$ where $(A,B)$ is a pair of correlated Gaussian Wigner matrices and $E,F$ are adversarially chosen matrices supported on an unknown $εn * εn$ princ
Deep Learning systems excel in complex tasks but often lack transparency, limiting their use in critical applications. Counterfactual explanations, a core tool within eXplainable Artificial Intelligence (XAI), offer insights into model decisions by identifying minimal changes to an input to alter its predicted outcome. However, existing methods for time series data are limited by univariate assumptions, rigid constra
We derive explicit equations governing the cumulative biases and weights in Deep Learning with ReLU activation function, based on gradient descent for the Euclidean loss in the input layer, and under the assumption that the weights are, in a precise sense, adapted to the coordinate system distinguished by the activations. We show that gradient descent corresponds to a dynamical process in the input layer, whereby clu
CTC: The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning
The critical role of division of labor (DOL) in enhancing cooperation is well-recognized in real-world applications. Consequently, many cooperative multi-agent reinforcement learning (MARL) methods have incorporated DOL mechanisms to improve cooperation among agents. However, the lack of benchmark tasks specifically designed to evaluate and promote DOL and cooperation has limited the effective development and deploym
Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation
Recent works modify CLIP to perform open-vocabulary semantic segmentation in a training-free manner (TF-OVSS). In vanilla CLIP, patch-wise image representations mainly encode homogeneous image-level properties, which hinders the application of CLIP to the dense prediction task. Previous TF-OVSS works sacrifice globality to enhance the locality of CLIP features, by making each patch mainly attend to itself or its neig
MAnchors: Memorization-Based Acceleration of Anchors via Rule Reuse and Transformation
Anchors is a popular local model-agnostic explanation technique whose applicability is limited by its computational inefficiency. To address this limitation, we propose a memorization-based framework that accelerates Anchors while preserving explanation fidelity and interpretability. Our approach leverages the iterative nature of Anchors' algorithm which gradually refines an explanation until it is precise enough
Background: Recruitment for cohorts involving complex liver diseases, such as hepatocellular carcinoma and liver cirrhosis, often requires interpreting semantically complex criteria. Traditional manual screening methods are time-consuming and prone to errors. While AI-powered pre-screening offers potential solutions, challenges remain regarding accuracy, efficiency, and data privacy. Methods: We developed a novel pat
The classification of electrocardiogram (ECG) signals is crucial for early detection of arrhythmias and other cardiac conditions. However, despite advances in machine learning, many studies fail to follow standardization protocols, leading to inconsistencies in performance evaluation and real-world applicability. Additionally, hardware constraints essential for practical deployment, such as in pacemakers, Holter moni
Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs
Seamless operation of mobile robots in challenging environments requires low-latency local motion estimation and accurate global localization. While most sensor-fusion approaches are designed for specific scenarios, this work introduces a flexible open-source solution for task- and setup-agnostic multimodal sensor fusion distinguished by its generality and usability. Holistic Fusion formulates sensor fusion as a comb
A Scaffolded GenAI Lab in Early Undergraduate CS: A Mixed-Methods, Multi-Course Evaluation
Background and Context. Generative AI (GenAI) tools are increasingly used in programming courses, but we have limited evidence about how brief instruction can foster responsible, learning-oriented use. Objectives. We evaluate "AI-Lab", a scaffolded GenAI literacy intervention, asking how students' self-reported GenAI usage and their openness and comfort using GenAI for conceptual, debugging, and homework
SLAC: Safe and Efficient Real-Robot Reinforcement Learning via Unsupervised Simulation Pre-Training
Building capable household and industrial robots requires mastering the control of versatile, high-degree-of-freedom (DoF) systems such as mobile manipulators. While reinforcement learning (RL) holds promise for autonomously acquiring robot control policies, scaling it to high-DoF embodiments remains challenging. Direct RL in the real world demands both safe exploration and high sample efficiency, which are difficult
Honesty in Causal Forests: When It Helps and When It Hurts
Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and public policy. A standard practice is honest estimation: dividing the data into two samples, one to define subgroups and another to estimate treatment effects within them. This is intended to reduce overfitting and is the default in many software packages. But is it the ri
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
Video Scene Parsing (VSP) studies dense video understanding, where every pixel in each frame must be segmented, each region must be named, and each object identity must remain coherent over time. This survey reviews recent progress in VSP across five tasks, spanning Video Semantic Segmentation (VSS), Video Instance Segmentation (VIS), Video Panoptic Segmentation (VPS), Video Tracking \& Segmentation (VTS), and Op
Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection
Detecting deceptive conversations on dynamic platforms is increasingly difficult due to evolving language patterns and Concept Drift (CD)-i.e., semantic or topical shifts that alter the context or intent of interactions over time. These shifts can obscure malicious intent or mimic normal dialogue, making accurate classification challenging. While Large Language Models (LLMs) show strong performance in natural languag
Interpretable Role-Based Clustering in Multi-Layer Financial Networks
Understanding the functional roles of financial institutions within interconnected markets is critical for effective supervision, systemic risk assessment, and resolution planning. We propose an interpretable role-based clustering approach for multi-layer financial networks, designed to identify the functional positions of institutions across different market segments. Our method follows a general clustering framewor
EGO: a Recursive and Self-Referential Cognitive Architecture for Artificial General Intelligence
Artificial General Intelligence (AGI) is interpreted as an emergent property of autonomous and self-organizing systems, grounded in the principles of autopoiesis and embodied cognition, overcoming the structural limitations of current Large Language Models (LLMs). We introduce EGO (Environment Generative Operator), a software architecture based on the formal E-language, capable of self-referentiality and of maintaini
Notable events recorded on this day and month across all years.