Record 16072026 · captured 2026-08-25
The world looked up Lionel Messi. 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.
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
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
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
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.
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 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
Argentina–England football rivalry
The Argentina–England football rivalry is a sports rivalry between the national football teams of Argentina and England. Exacerbated by historical political tensions, it is widely considered one of the most intense rivalries in international sport. Fixtures be
The Falklands War was a ten-week war in the South Atlantic in 1982 between Argentina and the United Kingdom over possession of the Falkland Islands and its dependencies of South Georgia and the South Sandwich Islands. The conflict began on 2 April 1982 when Ar
Thomas Tuchel is a German professional football manager and former player who is the manager of 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.
Sir Nigel John Dermot "Sam" Neill was a New Zealand actor. Known as a leading man in film and television, he received nominations for three Primetime Emmy Awards and two Golden Globe Awards. He was appointed an Officer of the Order of the British Empire in the
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 Falkland Islands, commonly referred to as the Falklands, is an archipelago in the South Atlantic Ocean on the Patagonian Shelf. The principal islands are about 300 mi (500 km) east of South America's southern Patagonian coast and 752 mi (1,210 km) from Cap
Diop Tehuti Djed-Hotep Spence is an English professional footballer who plays as a full-back for Serie A club Inter Milan and the England national team.
Sonam Wangchuk is an Indian engineer, educator, and activist. He is the founding director of the Students' Educational and Cultural Movement of Ladakh (SECMOL), which was founded in 1988 by a group of students who struggled with the public education system. He
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.
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
Giuliano Simeone Baldini is an Argentine professional footballer who plays as a right midfielder or winger for La Liga club Atlético Madrid and the Argentina national team.
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
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
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
Lindsey Olin Graham was an American politician, attorney, and military officer who represented South Carolina in the United States Senate from 2003 until his death in 2026. A member of the Republican Party, he represented South Carolina's 3rd congressional dis
Argentina national football team
The Argentina national football team, nicknamed la Albiceleste, represents Argentina in men's international football and is administered by the Argentine Football Association, the governing body of football in Argentina. It has been a member of FIFA since 1912
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.
The England national football team did not enter the first three FIFA World Cup tournaments as they were not members of FIFA, but have entered all 20 subsequent ones, beginning with that of 1950. They have failed to qualify for the tournament on three occasion
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
Diego Armando Maradona was an Argentine professional football player and manager. Widely regarded as one of the greatest players in history, he was one of the two joint winners of the FIFA Player of the Century award, alongside Pelé.
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
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Large Language Models are In-Context Molecule Learners
Large Language Models (LLMs) have demonstrated exceptional performance in biochemical tasks, especially the molecule caption translation task, which aims to bridge the gap between molecules and natural language texts. However, previous methods in adapting LLMs to the molecule-caption translation task required extra domain-specific pre-training stages, suffered weak alignment between molecular and textual spaces, or i
EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenes
We present a novel machine-learning (ML) approach (EM-GANSim) for real-time electromagnetic (EM) propagation that is used for wireless communication simulation in 3D indoor environments. Our approach uses a modified conditional Generative Adversarial Network (GAN) that incorporates encoded geometry and transmitter location while adhering to the electromagnetic propagation theory. The overall physically-inspired learn
Multi-view Hand Reconstruction with a Point-Embedded Transformer
This work introduces a novel and generalizable multi-view Hand Mesh Reconstruction (HMR) model, named POEM, designed for practical use in real-world hand motion capture scenarios. The advances of the POEM model consist of two main aspects. First, concerning the modeling of the problem, we propose embedding a static basis point within the multi-view stereo space. A point represents a natural form of 3D information and
Koopman-driven grip force prediction through EMG sensing
Loss of hand function due to conditions like stroke or multiple sclerosis significantly impacts daily activities. Robotic rehabilitation provides tools to restore hand function, while novel methods based on surface electromyography (sEMG) enable the adaptation of the device's force output according to the user's condition, thereby improving rehabilitation outcomes. This study aims to achieve accurate force es
Defining and Evaluating Physical Safety for Large Language Models
Large Language Models (LLMs) are increasingly used to control robotic systems such as drones, but their risks of causing physical threats and harm in real-world applications remain unexplored. Our study addresses the critical gap in evaluating LLM physical safety by developing a comprehensive benchmark for drone control. We classify the physical safety risks of drones into four categories: (1) human-targeted threats,
MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
Molecule discovery is a pivotal research field, impacting everything from medicine to materials. Recently, Large Language Models (LLMs) have been widely adopted in molecular understanding and generation, serving as a bridge between the molecular space and the natural language space, yet the alignment between molecules and their corresponding captions remains a significant challenge. Previous endeavors typically treat
FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks
Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critical concern. While LLMs are trained to refuse explicitly biased requests, bias can be leaked implicitly during LLM planning and reasoning process. As code becomes the primary medium for LLM internal logic-writing, we introduce FairCoder, a benchmark that frames decision-ma
Large Language Model (LLM)-based systems, i.e. interconnected elements that include an LLM as a central component, such as conversational agents, are usually designed with monolithic, static architectures that rely on a single, general-purpose LLM to handle all user queries. However, these systems may be inefficient as different queries may require different levels of reasoning, domain knowledge or pre-processing. Wh
DarwinLM: Evolutionary Structured Pruning of Large Language Models
Large Language Models (LLMs) have achieved significant success across various NLP tasks. However, their massive computational costs limit their widespread use, particularly in real-time applications. Structured pruning offers an effective solution by compressing models and directly providing end-to-end speed improvements, regardless of the hardware environment. Meanwhile, different components of the model exhibit var
On the Sublinear Regret of Continuous K-Max Bandits
The $K$-Max combinatorial multi-armed bandit problem arises in applications such as recommendation and distributed decision making, where the reward is determined by the maximum outcome among $K$ selected arms. When outcomes are continuous and only the maximum value together with the winner's index is observed, this problem introduces unprecedented difficulties including discretization errors, non-deterministic t
Diffusion models (DMs) have advanced text-to-image (T2I) synthesis, yet their personalization capabilities raise serious privacy and copyright concerns. Malicious actors can misuse these models to generate unauthorized portraits or artistic style replicas. Existing proactive defenses primarily rely on applying adversarial perturbations to reference images to disrupt training. However, these approaches face limitation
Fully AI-Generated Image Detection: Definition, Recent Advances and Challenges
Recent advances in visual generative models have enabled the creation of highly realistic, fully AI-generated images without relying on real source content. While beneficial for many applications, these models also pose significant societal risks, as they can be easily exploited to produce convincing Deepfakes. Detecting them represents a foundational yet challenging problem in AI media forensics, requiring detectors
Robust Palm-Vein Recognition Using the MMD Filter: Improving SIFT-Based Feature Matching
A major challenge with palm vein images is that slight movements of the fingers and thumb, or variations in hand posture, can stretch the skin in different areas and alter the vein patterns. This can result in an infinite number of variations in palm vein images for a given individual. This paper introduces a novel filtering technique for SIFT-based feature matching, known as the Mean and Median Distance (MMD) Filter
New universal operator approximation theorem for encoder-decoder architectures
Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator approximation theorem for broad classes of encoder-decoder architectures and a wide range of input and output spaces. In this study, we focus on the approximation of continuous operators between infinite-dimensional normed or metric spaces in the topology of uniform convergence
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
Sparse observations and coarse-resolution climate models limit effective regional decision-making, underscoring the need for robust downscaling. However, existing AI methods struggle with generalization across variables and geographies and are constrained by the quadratic complexity of Vision Transformer (ViT) self-attention. We introduce ORBIT-2, a scalable foundation model for global, hyper-resolution climate downs
Efficient LiDAR Reflectance Compression via Scanning Serialization
Reflectance attributes in LiDAR point clouds provide essential information for downstream tasks but remain underexplored in neural compression methods. To address this, we introduce SerLiC, a serialization-based neural compression framework to fully exploit the intrinsic characteristics of LiDAR reflectance. SerLiC first transforms 3D LiDAR point clouds into 1D sequences via scan-order serialization, offering a devic
Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer
Using Resistive Random Access Memory (RRAM) crossbars in Computing-in-Memory (CIM) architectures offers a promising solution to overcome the von Neumann bottleneck. Due to non-idealities like cell variability, RRAM crossbars are often operated in binary mode, utilizing only two states: Low Resistive State (LRS) and High Resistive State (HRS). Binary Neural Networks (BNNs) and Ternary Neural Networks (TNNs) are well-s
Large Language Model (LLM) inference is typically memory-intensive, especially when processing large batch sizes and long sequences, due to the large size of key-value (KV) cache. Vector Quantization (VQ) is recently adopted to alleviate this issue, but we find that the existing approach is susceptible to distribution shift due to its reliance on calibration datasets. To address this limitation, we introduce NSNQuant
Global and Local Contrastive Learning for Joint Representations from Cardiac MRI and ECG
An electrocardiogram (ECG) is a widely used, cost-effective tool for detecting electrical abnormalities in the heart. However, it cannot directly measure functional parameters, such as ventricular volumes and ejection fraction, which are crucial for assessing cardiac function. Cardiac magnetic resonance (CMR) is the gold standard for these measurements, providing detailed structural and functional insights, but is ex
Uniform Approximation of Functions with Asymmetric Growth and Decay by Deep Weighted Polynomials
Functions that grow without bound on one side of the real line and decay to zero on the other cannot be approximated uniformly by ordinary polynomials on unbounded domains. Motivated by classical weighted polynomial approximation, we introduce a class of one-sided weighted \emph{deep} (composite) polynomial approximants for such asymmetric targets. The weight suppresses polynomial growth on the decaying side, while t
Distributed acoustic sensing (DAS) has attracted considerable attention across various fields and artificial intelligence (AI) technology plays an important role in DAS applications to realize event recognition and denoising. Existing AI models require real-world data (RWD), whether labeled or not, for training, which is contradictory to the fact of limited available event data in real-world scenarios. Here, a physic
Efficiency, Feasibility, and Incentive-Awareness in Constrained Online Resource Allocation
We study the dynamic allocation of indivisible resources to strategic agents under long-term constraints, where the planner aims to maximize social welfare, satisfy multiple constraints, and elicit near-truthful reports. We find standard primal-dual methods fragile in this setting: agents easily manipulate their reports to distort dual variables, sacrificing social efficiency for individual utility. To address this,
We propose a vision transformer (ViT)-based deep learning framework to refine disaster-affected area segmentation from remote sensing imagery, aiming to support and enhance the Emergent Value Added Product (EVAP) developed by the Taiwan Space Agency (TASA). The process starts with a small set of manually annotated regions. We then apply principal component analysis (PCA)-based feature space analysis and construct a c
Classical game-theoretic models typically assume rational agents, complete information, and common knowledge of payoffs - assumptions that are often violated in real-world MAS characterized by uncertainty, misaligned perceptions, and nested beliefs. To overcome these limitations, researchers have proposed extensions that incorporate models of cognitive constraints, subjective beliefs, and heterogeneous reasoning. Amo
Hierarchical Scoring for Machine Learning Classifier Error Impact Evaluation
A common use of machine learning (ML) models is predicting the class of a sample. Object detection is an extension of classification that includes localization of the object via a bounding box within the sample. Classification, and by extension object detection, is typically evaluated by counting a prediction as incorrect if the predicted label does not match the ground truth label. This pass/fail scoring treats all
Notable events recorded on this day and month across all years.