Record 08072026 · captured 2026-08-25
The world looked up 2026 FIFA World Cup. 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.
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
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
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
Addison Mitchell McConnell III is an American politician and attorney who has been a United States senator from Kentucky since 1985 and has been Kentucky's senior U.S. senator since 1999. A member of the Republican Party, McConnell is in his seventh Senate ter
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.
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
Folarin Jerry Balogun is a professional soccer player who plays as a striker for Ligue 1 club Monaco and the United States 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
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
.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
Christian Mate Pulisic is an American professional soccer player who plays as a winger, attacking midfielder and forward for Serie A club AC Milan and the United States national team. Regarded as one of the best North American players of all time, he is nickna
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
Mauricio Roberto Pochettino Trossero is an Argentine professional football manager and former player who is the head coach of the United States men's national team.
Félix Auger-Aliassime, sometimes referred to as "FAA", is a Canadian professional tennis player. His career-high ATP singles ranking is world No. 4 achieved on 8 June 2026. He has been ranked No. 60 in doubles, reached in November 2021. Auger-Aliassime has won
Romelu Lukaku Bolingoli is a Belgian professional footballer who plays as a striker for Süper Lig club Fenerbahçe and the Belgium national team. Lukaku ranks second for the all-time European men's top goalscorers in international football, with 93 goals.
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
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
Charles Marc S. De Ketelaere is a Belgian professional footballer who plays as an attacking midfielder or forward for Serie A club Atalanta and the Belgium national team.
Mohamed Salah Hamed Mahrous Ghaly is an Egyptian professional footballer who plays as a right winger for Süper Lig club Trabzonspor and captains the Egypt national team. He is widely regarded as one of the best players of his generation and one of the greatest
Graham Cunningham Platner is an American oyster farmer, Marine Corps veteran, and politician. Platner was the Democratic nominee in the 2026 US Senate election in Maine until he ended his campaign in July.
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
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
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
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
Roblox is an online game platform and game creation system developed by Roblox Corporation that allows users to program and play games created by themselves or other users. It was developed by David Baszucki and Erik Cassel in 2004, and released to the public
Malik Leon Tillman is a professional soccer player who plays as an attacking midfielder for Bundesliga club Bayer Leverkusen. Born in Germany, he represents the United States national team. He is known for his creativity, ball control, and dribbling.
Matthew Andrew Geary Freese is an American professional soccer player who plays as a goalkeeper for Major League Soccer club New York City FC and the United States national team.
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
United States men's national soccer team
The United States men's national soccer team (USMNT), universally designated as USA by FIFA, represents the United States in men's international soccer, which is governed by the United States Soccer Federation. The team has been an affiliate member of FIFA sin
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python
Despite impressive success of machine learning algorithms in clinical natural language processing (cNLP), rule-based approaches still have a prominent role. In this paper, we introduce medspaCy, an extensible, open-source cNLP library based on spaCy framework that allows flexible integration of rule-based and machine learning-based algorithms adapted to clinical text. MedspaCy includes a variety of components that me
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers
Hierarchical classification aims to sort the object into a hierarchical structure of categories. For example, a bird can be categorized according to a three-level hierarchy of order, family, and species. Existing methods commonly address hierarchical classification by decoupling it into a series of multi-class classification tasks. However, such a multi-task learning strategy fails to fully exploit the correlation am
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks
To understand the training dynamics of neural networks, prior studies have considered the mean-field limit of two-layer neural networks as the width tends to infinity, establishing theoretical guarantees for its convergence under gradient flow training as well as approximation and generalization capabilities. In this work, we study the infinite-width limit of a type of three-layer neural network where the first-layer
Game of Tones: Faculty detection of GPT-4 generated content in university assessments
This study explores the robustness of university assessments against the use of Open AI's Generative Pre-Trained Transformer 4 (GPT-4) generated content and evaluates the ability of academic staff to detect its use when supported by the Turnitin Artificial Intelligence (AI) detection tool. The research involved twenty-two GPT-4 generated submissions being created and included in the assessment process to be marke
Talking head generation has progressed rapidly from landmark- and GAN-based facial animation to diffusion models, neural rendering, 3D-aware avatars, and foundation-model-assisted systems. This progress has enabled increasingly realistic audio-, image-, and video-driven talking heads, but it has also made the field difficult to navigate because methods differ substantially in their inputs, assumptions, controllabilit
DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised
Autonomous systems (AS) often rely on Deep Neural Network (DNN) classifiers to operate in complex and dynamically changing environments. However, during operation, these classifiers may encounter domains that differ from those seen during development, causing performance degradation under distribution shift. Removing systems from operation for labelled data collection and retraining is often impractical, particularly
Recent developments in Generative Artificial Intelligence (GenAI) have created a paradigm shift in multiple areas of society, and the use of these technologies is likely to become a defining feature of education in coming decades. GenAI offers transformative pedagogical opportunities, while simultaneously posing ethical and academic challenges. Against this backdrop, we outline a practical, simple, and sufficiently c
Detecting partial extrinsic symmetry in 3D geometry is a fundamental yet persistent challenge in computer vision and graphics, critical for tasks ranging from shape completion to procedural generation. Classical transformation-space voting methods rely on pairwise matching, scaling as O(n^2) and struggling to resolve coherent multi-instance groups. Recent learning approaches advance global symmetry detection but rest
The rapid adoption of Generative Artificial Intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices, and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. This paper presents the findings of a pilot study conducted at British University Vietnam (BUV) exp
GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content that has been modified using techniques designed to evade detection by these tools (n=805). The results demonstrate that the detectors' already low accuracy rates (39.5%) show major reductions in accuracy (17.4%) when faced with manipulated content, with some techniques proving mor
Deepfakes and Higher Education: A Research Agenda and Scoping Review of Synthetic Media
The availability of software which can produce convincing yet synthetic media poses both threats and benefits to tertiary education globally. While other forms of synthetic media exist, this study focuses on deepfakes, which are advanced Generative AI (GenAI) fakes of real people. This conceptual paper assesses the current literature on deepfakes across multiple disciplines by conducting an initial scoping review of
RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
Recent advances in Multimodal Large Language Models (MLLMs) have shown promise for remote sensing tasks such as visual question answering and scene understanding. However, existing models remain limited to basic instruction-following and struggle with real-world scenarios that require multi-source data integration, fine-grained spatial reasoning, and domain expertise. To address this gap, we propose RS-Agent, a domai
Replication in Visual Diffusion Models: A Survey and Outlook
Visual diffusion models have revolutionized the field of creative AI, producing high-quality and diverse content. However, they inevitably memorize training images or videos, subsequently replicating their concepts, content, or styles during inference. This phenomenon raises significant concerns about privacy, security, and copyright within generated outputs. In this survey, we provide the first comprehensive review
The EAP-AIAS: Adapting the AI Assessment Scale for English for Academic Purposes
The rapid advancement of Generative Artificial Intelligence (GenAI) presents both opportunities and challenges for English for Academic Purposes (EAP) instruction. This paper proposes an adaptation of the AI Assessment Scale (AIAS) specifically tailored for EAP contexts, termed the EAP-AIAS. This framework aims to provide a structured approach for integrating GenAI tools into EAP assessment practices while maintainin
MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
Previous studies on federated learning (FL) often encounter performance degradation due to data heterogeneity among different clients. In light of the recent advances in multimodal large language models (MLLMs), such as GPT-4v and LLaVA, which demonstrate their exceptional proficiency in multimodal tasks, such as image captioning and multimodal question answering. We introduce a novel federated learning framework, na
Trust-free Personalized Decentralized Learning
Personalized collaborative learning in federated settings faces a critical trade-off between customization and participant trust. Existing approaches typically rely on centralized coordinators or trusted peer groups, limiting their applicability in open, trust-averse environments. While recent decentralized methods explore anonymous knowledge sharing, they often lack global scalability and robust mechanisms against m
Adaptive and Stratified Subsampling for High-Dimensional Robust Estimation
We study robust high-dimensional sparse regression under finite-variance heavy-tailed noise, epsilon-contamination, and alpha-mixing dependence via two subsampling estimators: Adaptive Importance Sampling (AIS) and Stratified Sub-sampling (SS). Under sub-Gaussian design whose scopeis precisely delimited and finite-variance noise, a subsample of size m achieves the minimax-optimal rate. We close the theory-algorithm g
The decision-making process to rule R&D relies on information related to current trends in particular research areas. In this work, we investigated how one can use large language models (LLMs) to transfer the dataset and its annotation from one language to another. This is crucial since sharing knowledge between different languages could boost certain underresourced directions in the target language, saving lots
Reconstructing continuous surfaces from unoriented and unordered 3D points is a fundamental challenge in computer vision and graphics. Recent advancements address this problem by training neural signed distance functions to pull 3D location queries to their closest points on a surface, following the predicted signed distances and the analytical gradients computed by the network. In this paper, we introduce NumGrad-Pu
Tuned Reverse Distillation: Enhancing Multimodal Industrial Anomaly Detection with Crossmodal Tuners
Knowledge distillation (KD) has been widely studied in unsupervised image Anomaly Detection (AD), but its application to unsupervised multimodal AD remains underexplored. Existing KD-based methods for multimodal AD that use fused multimodal features to obtain teacher representations face challenges. Anomalies that only exist in one modality may not be effectively captured in the fused teacher features, leading to det
Classification of Financial Data Using Quantum Support Vector Machine
Quantum Support Vector Machine is a kernel-based approach to classification problems. We study the applicability of quantum kernels to financial data, specifically our self-curated Dhaka Stock Exchange (DSEx) Broad Index dataset. To the best of our knowledge, this is the first systematic study of quantum kernels applied to this dataset. Working within the empirical quantum advantage (EQA) framework of Krunic et al.,
Leveraging Metamemory Agent for Enhanced Data-Free Code Generation in Large Language Models
Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicity and effectiveness. However, few-shot methods depend on curated or manually crafted reference examples, limiting their applicability in data-free coding scenarios such as real-world data-free coding scenarios and benchmarks without training sets. Existing methods that generate
Universality of Benign Overfitting in Binary Linear Classification
The practical success of deep learning has led to the discovery of several surprising phenomena. One of these phenomena, that has spurred intense theoretical research, is ``benign overfitting'': deep neural networks seem to generalize well in the over-parametrized regime even though the networks show a perfect fit to noisy training data. It is now known that benign overfitting also occurs in various classical
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they attain high scores on many popular visual benchmarks, with headroom rapidly eroded by model progress. This creates a need for difficult benchmarks that remain relevant for longer. We introduce ZeroBench - a lightweight visual reasoning bench
Large language models have demonstrated remarkable progress in mathematical reasoning, leveraging chain-of-thought and reinforcement learning. However, many open questions remain regarding the interplay between reasoning token usage and accuracy gains. In particular, when comparing models across generations, it is unclear whether improved performance results from longer reasoning chains or more efficient reasoning. W
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