Record 17082026 · captured 2026-08-25
The world looked up Jason Arday. 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.
Jason Atta Kwei Arday was a British academic who was a professor of sociology of education at the University of Cambridge from 2023 to 2026. Arday received international attention and resigned amid accusations of plagiarism, false claims in his research, and f
Spider-Man: Brand New Day is a 2026 American superhero film based on the Marvel Comics character Spider-Man. Produced by Columbia Pictures, Marvel Studios, and Pascal Pictures, and distributed by Sony Pictures Releasing, it is the 38th film in the Marvel Cinem
UFC 330: Makhachev vs. Machado Garry was a mixed martial arts event produced by the Ultimate Fighting Championship that took place on August 15, 2026, at the Xfinity Mobile Arena in Philadelphia, Pennsylvania, United States. It was the twenty-sixth UFC event o
Awarapan 2 is a 2026 Indian Hindi-language action thriller film directed by Nitin Kakkar, written by Kakkar, Bilal Siddiqui and Vishesh Bhatt, and produced under his banner Vishesh Films. A sequel to the 2007 film Awarapan, the film stars Emraan Hashmi, Disha
Islam Ramazanovich Makhachev is a Russian professional mixed martial artist and former sambo competitor. He currently competes in the Welterweight division of the Ultimate Fighting Championship (UFC), where he is the current UFC Welterweight Champion and forme
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
.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
Ian David Machado Garry is an Irish professional mixed martial artist who currently competes in the Welterweight division of the Ultimate Fighting Championship (UFC). Prior to signing with the UFC, Garry was a Cage Warriors Welterweight Champion. As of 20 June
Joshua Emanuel Báez is a Dominican-American professional baseball outfielder for the St. Louis Cardinals of Major League Baseball (MLB). In his MLB debut on August 15, 2026, he hit home runs in his first three MLB plate appearances, becoming the first player t
The End of Oak Street is a 2026 American science fiction survival film written, co-produced, and directed by David Robert Mitchell. It stars Anne Hathaway, Ewan McGregor, Maisy Stella and Christian Convery as a family whose suburban neighborhood has been trans
Thomas Edward John Jr., nicknamed "the Bionic Man", was an American professional baseball pitcher who played in Major League Baseball (MLB) for 26 seasons between 1963 and 1989. He played for the Cleveland Indians, Chicago White Sox, Los Angeles Dodgers, New Y
Vishwanath & Sons is a 2026 Indian Tamil language romance and family drama film written and directed by Venky Atluri. Produced by Sithara Entertainments and Fortune Four Cinemas, the film stars Suriya, alongside Mamitha Baiju, Raadhika Sarathkumar, and Raveena
2026 European Athletics Championships
The 27th European Athletics Championships were held from 10 to 16 August 2026 at the Alexander Stadium in Birmingham, United Kingdom.
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
Batwara 1947 is a 2026 Indian Hindi-language period drama film co-written and directed by Rajkumar Santoshi, and produced by Aamir Khan under the banner of Aamir Khan Productions. Set in Lahore against the backdrop of the 1947 Partition of British India and th
Mackenzie Lynne Dern is an American and Brazilian professional mixed martial artist and Brazilian Jiu-Jitsu practitioner currently competing in the women's strawweight division of the Ultimate Fighting Championship (UFC), where she is the current UFC Women's S
Amy Hunt is an English sprinter. She won the gold medal in the 100 metres, 200 metres, 4 × 100 metres relay, and 4 x 100 metres mixed relay at the 2026 European Championships, becoming the first athlete to win four gold medals at a single European Championship
List of highest-grossing films
Films generate income from several revenue streams, including theatrical exhibition, home video, television broadcast rights, and merchandising. However, theatrical box-office earnings are the primary metric for trade publications in assessing the success of a
The Football Association Community Shield is an annual match in English football contested at Wembley Stadium between the champions of the previous Premier League season and the holders of the FA Cup. If the same team wins both the league and the FA Cup, the m
Danielle Fabiola "Inde" Navarrette is an American actress and former online streamer. She began her acting career as a teenager with roles in short films, before landing roles in the Netflix drama series 13 Reasons Why (2020) and The CW's superhero drama serie
Georgia Hunter Bell is an English track and field athlete who competes as a middle distance runner. She is the reigning World Indoor Champion and European Champion in the 1500 metres, having won the titles in a British indoor record time at the 2026 World Indo
List of Marvel Cinematic Universe films
The Marvel Cinematic Universe (MCU) centers on American superhero films produced by Marvel Studios, based on characters that appear in publications by Marvel Comics. The MCU is the shared universe in which all of the films are set. Marvel Studios has released
The Last House is a 2026 American science fiction horror film written by Matthew Robinson, and directed by Louis Leterrier. It stars Greta Lee and Wagner Moura. The film follows a family that finds themselves inexplicably sealed in their home, with the whole w
Avengers: Doomsday is an upcoming American superhero film based on the Marvel Comics superhero team the Avengers. Produced by Marvel Studios and distributed by Walt Disney Studios Motion Pictures, it is intended to be the sequel to Avengers: Endgame (2019) and
Madonna Louise Ciccone is an American singer, songwriter, record producer, and actress. Dubbed the "Queen of Pop", she is known for her continual reinvention and versatility in music production, songwriting, and visual presentation. Her works, which concern so
Aspic or meat jelly is a savoury gelatin made with a meat stock or broth, set in a mold to encase other ingredients. These often include pieces of meat, seafood, vegetable, or eggs. Aspic is also sometimes referred to as aspic gelée or aspic jelly. In its simp
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
Nathan Cofnas is an American postdoctoral researcher at Ghent University in Belgium. He is known for controversies surrounding his advocacy of scientific racism.
Zendaya Maree Stoermer Coleman, known mononymously as Zendaya, is an American actress and singer-songwriter. Known for her work in television and blockbusters, her films as a leading actress have grossed over $9.8 billion worldwide. Her accolades include two P
Christos Tzolis is a Greek professional footballer who plays as a left winger for Premier League club Arsenal and the Greece national team.
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Active Regression via Linear-Sample Sparsification
We present an approach that improves the sample complexity for a variety of curve fitting problems, including active learning for linear regression, polynomial regression, and continuous sparse Fourier transforms. In the active linear regression problem, one would like to estimate the least squares solution $β^*$ minimizing $\|Xβ- y\|_2$ given the entire unlabeled dataset $X \in \mathbb{R}^{n \times d}$ but only obse
Holdout predictive checks for Bayesian model criticism
Bayesian modeling helps applied researchers articulate assumptions about their data and develop models tailored for specific applications. Thanks to good methods for approximate posterior inference, researchers can now easily build, use, and revise complicated Bayesian models for large and rich data. These capabilities, however, bring into focus the problem of model criticism. Researchers need tools to diagnose the f
I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling
Reconstructing a high-precision and high-fidelity 3D human hand from a color image plays a central role in replicating a realistic virtual hand in human-computer interaction and virtual reality applications. The results of current methods are lacking in accuracy and fidelity due to various hand poses and severe occlusions. In this study, we propose an I2UV-HandNet model for accurate hand pose and shape estimation as
Investigating individual writing style as a contributor to gender gaps in science and technology
Gender gaps in how scientific work is evaluated are well documented, but their sources remain debated. We ask whether an overlooked factor---the linguistic style of the writing itself---is gendered and consequential. Drawing on a framework that distinguishes informational features (which emphasize facts) from involved features (which emphasize relationships), we analyze single-authored abstracts of academic papers an
DAA: A Delta Age AdaIN operation for age estimation via binary code transformer
Naked eye recognition of age is usually based on comparison with the age of others. However, this idea is ignored by computer tasks because it is difficult to obtain representative contrast images of each age. Inspired by the transfer learning, we designed the Delta Age AdaIN (DAA) operation to obtain the feature difference with each age, which obtains the style map of each age through the learned values representing
Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation
Clothes grasping and unfolding is a core step in robotic-assisted dressing. Most existing works leverage depth images of clothes to train a deep learning-based model to recognize suitable grasping points. These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection. However, the natural domain gap between synthetic and real images often leads to poor perfor
Logarithmic Mathematical Morphology: Theory and applications
In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring function is translated over the image domain and summed to the image. However, in an image presenting lighting variations, when the structuring function is added to this image, the amplitude of this translated structuring function should vary according to the image intensity. Suc
Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges
Graph-based message-passing neural networks (MPNNs) have achieved remarkable success in both node and graph-level learning tasks. However, several identified problems, including over-smoothing (OSM), limited expressive power, and over-squashing (OSQ), still limit the performance of MPNNs. In particular, OSQ serves as the latest identified problem, where MPNNs gradually lose their learning accuracy when long-range dep
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Spatial sound reasoning is a fundamental human skill, enabling us to navigate and interpret our surroundings based on sound. In this paper we present BAT, which combines the spatial sound perception ability of a binaural acoustic scene analysis model with the natural language reasoning capabilities of a large language model (LLM) to replicate this innate ability. To address the lack of existing datasets of in-the-wil
Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex and age. While these standards provide useful guidelines and help identify at-risk patients, they are not fully reliable for diagnosis due to the lack of demographic considerations. This study aims to
MLCC: A Congestion Control Technique to Accelerate ML Training
We present MLCC, a novel technique to augment today's congestion control algorithms to accelerate DNN training jobs in shared GPU clusters in a fully distributed manner. At the heart of MLCC lies a straightforward principle: DNN training flows should scale their sending rate to shift other flows' communication into their compute periods, achieving interleaving. We show that integrating this principle into tod
Automated Inference of Graph Transformation Rules
The explosion of data available in life sciences is fueling an increasing demand for expressive models and computational methods. Graph transformation is a model for dynamic systems with a large variety of applications. We introduce a novel method of the graph transformation model construction, combining generative and dynamical viewpoints to give a fully automated data-driven model inference method. The method takes
Overparameterized Multiple Linear Regression as Hyper-Curve Fitting
This work demonstrates that applying a fixed-effect multiple linear regression (MLR) model to an overparameterized dataset is mathematically equivalent to fitting a hyper-curve parameterized by a single scalar. This reformulation shifts the focus from global coefficients to individual predictors, allowing each to be modeled as a function of a common parameter. We prove that this overparameterized linear framework can
Separation capacity of linear reservoirs with random connectivity matrix
A natural hypothesis for the success of reservoir computing in generic tasks is the ability of the untrained reservoir to map distinct input time series to separable reservoir states, a property we term separation capacity. In this work, we develop a rigorous mathematical framework for analysing the separation capacity of random linear reservoirs. We show that the expected separation induced by a random reservoir is
Numerous applications have resulted from the automation of agricultural disease segmentation using deep learning techniques. However, when applied to new conditions, these applications frequently face the difficulty of overfitting, resulting in lower segmentation performance. In the context of potato farming, where diseases have a large influence on yields, it is critical for the agricultural economy to quickly and p
A Probabilistic Framework for Learnable Optimization Algorithms
We propose a statistical-learning framework for optimization algorithms. The framework is based on probability distributions over optimization trajectories induced by a distribution of optimization problems and a learnable optimization algorithm. Within this setting, optimization performance is represented through measurable performance functionals, including stopping times, contraction factors, and trajectory-level
OTIS: Learning High-Quality Time Series Features With Tiny Encoders
We introduce OTIS, an open time series encoder that yields high-quality time series features for downstream deployment on any system, including resource-constrained wearables and industrial sensors. Currently, the development of powerful general-purpose encoders relies on the scaling laws hypothesis, using large encoder sizes to memorise the heterogeneous distributions of multi-domain training data. However, this rel
Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directions
Automated vehicles (AVs) promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due to rare and unexpected situations known as edge cases. While numerous approaches exist for detecting edge cases, a comprehensive survey reviewing these techniques is lacking. This paper bridges this gap by presenting a hierarchical review
Ordinal-Aware Calibration for Ordinal Classification
Deep neural networks frequently produce overconfident, miscalibrated predictions. In ordinal classification, predictions must also adhere to a unimodal and order-consistent structure, a requirement that has dominated prior work while overlooking calibration. We formalize this joint challenge as ordinal calibration for the first time and propose the Ordinal loss for Calibration and Unimodality (ORCU). Unlike increment
LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction
Large language models (LLMs) are increasingly being used in materials science. However, little attention has been given to benchmarking and standardized evaluation for LLM-based materials property prediction, which hinders progress. We present LLM4Mat-Bench, the largest benchmark to date for evaluating the performance of LLMs in predicting the properties of crystalline materials. LLM4Mat-Bench contains about 1.9M cry
Efficient transformer adaptation for analog in-memory computing via low-rank adapters
Analog In-Memory Computing (AIMC) offers a promising solution to the von Neumann bottleneck. However, deploying transformer models on AIMC remains challenging due to their inherent need for flexibility and adaptability across diverse tasks. For the benefits of AIMC to be fully realized, weights of static vector-matrix multiplications must be mapped and programmed to analog devices in a weight-stationary manner. This
Musical Agent Systems: MACAT and MACataRT
Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces. We introduce MACAT and MACataRT, two distinct musical agent systems crafted to enhance interactive music-making between human musicians and AI. MACAT is optimized for agent-led performance, employing real-time synthesis and
Generative Modeling with Bayesian Sample Inference
We present a novel view of diffusion-like generative modeling from the perspective of iterative Gaussian posterior inference. By treating the generated sample as an unknown variable, we formulate the sampling process in the language of Bayesian probability: at each step, a model predicts the unknown sample from our current belief state and we compute a posterior belief from that prediction. Based on this formulation,
AI Models Still Lag Behind Traditional Numerical Models in Predicting Sudden-Turning Typhoons
Given the interpretability, accuracy, and stability of numerical weather prediction (NWP) models, current operational weather forecasting relies heavily on the NWP approach. In the past two years, the rapid development of Artificial Intelligence (AI) has provided an alternative solution for medium-range (1-10 days) weather forecasting. Bi et al. (2023) (hereafter Bi23) introduced the first AI-based weather prediction
In response to the growing need for structured, interoperable agricultural data, this paper presents the Sustainable Wheat Production Datahub, a modular, graph-based framework that brings diverse wheat production datasets together into a single, queryable store. Using the Knowledge Acquisition and Representation Methodology (KNARM), with domain experts in the loop, we developed ontologies for nutrient management and
Notable events recorded on this day and month across all years.