Record 31072026 · captured 2026-08-25
The world looked up Spider-Man: Brand New Day. 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.
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
Glen James Hansard was an Irish singer-songwriter and actor. From Ballymun in northern Dublin, he busked from his teens. In 1990, he co-founded the Irish rock band the Frames, which he fronted. The band released six studio albums, four of which reached the top
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
Matthias Jaissle is a German professional football manager and former player who is currently the head coach of Premier League club Newcastle United.
Anthony Stephen Fauci is an American physician-scientist and immunologist who served as the director of the National Institute of Allergy and Infectious Diseases (NIAID) from 1984 to 2022 and as Chief Medical Advisor to the President from 2021 to 2022. He was
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
Thomas Stanley Holland is a British actor. His accolades include a BAFTA Award as well as two Critics' Choice Awards nominations. Holland's films as a leading actor have grossed over $14.9 billion worldwide, making him the Fourth highest-grossing actor of all
The 2026 Commonwealth Games, officially known as the XXIII Commonwealth Games and commonly known as Glasgow 2026, was a multi-sport event held from 23 July to 2 August 2026 in Glasgow, the largest city in Scotland, for members of the Commonwealth of Nations. T
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
Ceuta is an autonomous city of Spain on the North African coast. Bordered by Morocco, it lies between the Mediterranean Sea and the Atlantic Ocean. Ceuta is one of the special territories of members of the European Economic Area: it is a part of the Schengen a
India at the 2026 Commonwealth Games
India competed at the 2026 Commonwealth Games, held in Glasgow, Scotland, from 23 July to 2 August 2026. It was the country's 19th appearance at the Commonwealth Games, after making its debut at the 1934 Commonwealth Games. The Indian contingent consisted of 1
In the early morning hours of November 13, 2022, four University of Idaho students—Madison Mogen, Kaylee Goncalves, Ethan Chapin, and Xana Kernodle—were fatally stabbed in an off-campus house in Moscow, Idaho. On December 30, authorities arrested 28-year-old B
Jared Joseph Leto is an American actor and musician. Known for his method acting in a variety of roles, he has received various accolades over a career spanning three decades, including an Academy Award and a Golden Globe. He is also the frontman of the rock b
Vincent Pierre Claude Belorgey, known professionally as Kavinsky, was a French DJ, record producer and actor. His production style is reminiscent of the electropop film soundtracks of the 1980s. Kavinsky said that his music was inspired by thousands of films h
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
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
Sadie Elizabeth Sink is an American actress. She began her career in theater as a child, playing the title role in the musical Annie (2012–2014) and young Elizabeth II in the historical play The Audience (2015) on Broadway. In 2016, she made her film debut in
Neatsville is an unincorporated community in Adair County, in the U.S. state of Kentucky. It is located at the junction of Kentucky Route 206 and Kentucky Route 76. Its elevation is 705 feet (215 m). For unknown reasons, the town's name was spelled as Neetsvil
Markéta Irglová is a Czech and Icelandic singer-songwriter, musician, and actress. She starred in the 2007 film Once, which earned her a number of major awards, including the Academy Award for Best Original Song for "Falling Slowly", with co-writer and co-star
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
Dame Harriet Mary Walter is an English actor of stage and screen. She is known for her role as Natalie Chandler in the ITV drama series Law & Order: UK from 2009 to 2014, and in the Hollywood blockbuster Star Wars: The Force Awakens (2015), among other film an
Limonene is a slightly yellow-green liquid aliphatic hydrocarbon classified as a cyclic monoterpene, and is the major component in the fragrance and essential oil of citrus fruit peels, taking its name from Italian limone ("lemon").
Pan Am Flight 103 was a regularly scheduled Pan Am flight from Frankfurt to Detroit via stopovers in London and New York City. Shortly after 19:00 GMT on 21 December 1988, the Boeing 747 Clipper Maid of the Seas was destroyed by a bomb while flying over the Sc
Spider-Man: No Way Home is a 2021 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 sequel to Spider-Man: Homecomin
Jean Grey is a superhero appearing in American comic books published by Marvel Comics, usually those featuring the X-Men, a group of superheroes of which she is a founding member. Created by writer Stan Lee and artist/co-plotter Jack Kirby, the character first
Sir Christopher Edward Nolan is a British and American filmmaker. Known for his Hollywood blockbusters with complex storytelling, Nolan is considered a leading filmmaker of the 21st century. His films have earned over $7.7 billion worldwide, making him the thi
Marvin Pentz Gaye Jr. was an American R&B and soul singer, songwriter, musician, and record producer. Commonly referred to as the "Prince of Motown" and "Prince of Soul", he helped to shape the sound of Motown and soul music in the 1960s and 1970s. A cultural
.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
The Devil Wears Prada 2 is a 2026 American comedy drama film directed by David Frankel and written by Aline Brosh McKenna. A sequel to the 2006 film The Devil Wears Prada, it sees Meryl Streep, Anne Hathaway, Emily Blunt, and Stanley Tucci reprising their role
The Union of European Football Associations (UEFA) is the governing body of football in Europe and one of FIFA's six continental confederations for association football consisting of 55 national associations. It runs national and club competitions for men and
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
BCNet: Bronchus Classification via Structure Guided Representation Learning
CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challenging because bronchial topology varies substantially across individuals. We propose the Bronchus Classification Network (BCNet), a structure-guided framework that uses segment-level topological information from point clouds to improve voxel-level representation learning. BCNet co
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian
Signed and directed networks are ubiquitous in real-world applications. However, there has been relatively little work proposing spectral graph neural networks (GNNs) for such networks. Here we introduce a signed directed Laplacian matrix, which we call the magnetic signed Laplacian, as a natural generalization of both the signed Laplacian on signed graphs and the magnetic Laplacian on directed graphs. We then use th
Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and researchers with the knowledge and skills to become independent users of this potent environment so that they can tackle any problem related to data wrangling and analytics, numerical computing, statistics, and machine learning. This textbook is
Toward Real-Time Image Annotation Using Marginalized Coupled Dictionary Learning
In most image retrieval systems, images include various high-level semantics, called tags or annotations. Virtually all the state-of-the-art image annotation methods that handle imbalanced labeling are search-based techniques which are time-consuming. In this paper, a novel coupled dictionary learning approach is proposed to learn a limited number of visual prototypes and their corresponding semantics simultaneously.
Bridging AI and Energy Forecasting: An Autonomous Workflow with Customized Toolkit
Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like meteorological factors, and its goals must align with actual power grid operations, such as risk assessment and system reliability. In order to bridge the huge gap between advanced machine learning forecasting models and actual power grid demand, this paper proposes an a
LuckyMera: a Modular AI Framework for Building Hybrid NetHack Agents
In the last few decades we have witnessed a significant development in Artificial Intelligence (AI) thanks to the availability of a variety of testbeds, mostly based on simulated environments and video games. Among those, roguelike games offer a very good trade-off in terms of complexity of the environment and computational costs, which makes them perfectly suited to test AI agents generalization capabilities. In thi
A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem
Optimal transport is a fundamental topic that has attracted a great amount of attention from the optimization community in the past decades. In this paper, we consider an interesting discrete dynamic optimal transport problem: can we efficiently update the optimal transport plan when the weights or the locations of the data points change? This problem is naturally motivated by several applications in machine learning
Damped Proximal Augmented Lagrangian Method for weakly-Convex Problems with Convex Constraints
We give a damped proximal augmented Lagrangian method (DPALM) for solving problems with a weakly-convex objective and convex linear/nonlinear constraints. Instead of taking a full stepsize, DPALM adopts a damped dual stepsize to ensure the boundedness of dual iterates. We show that DPALM can produce a (near) $\vareps$-KKT point within $O(\vareps^{-2})$ outer iterations if each DPALM subproblem is solved to a proper a
Background: Pose estimation of rigid objects is a practical challenge in optical metrology and computer vision. This paper presents a novel stochastic-geometrical modeling framework for object pose estimation based on observing multiple feature points. Methods: This framework utilizes mixture models for feature point densities in object space and for interpreting real measurements. Advantages are the avoidance to res
A Review on Building Blocks of Decentralized Artificial Intelligence
Artificial intelligence is transforming our lives, and technological progress and transfer from the academic and theoretical sphere to the real world are accelerating yearly. But during that progress and transition, several open problems and questions need to be addressed for the field to develop ethically, such as digital privacy, ownership, and control. These are some of the reasons why the currently most popular a
A Two-Stage Training Method for Modeling Constrained Systems With Neural Networks
Real-world systems are often formulated as constrained optimization problems. Techniques to incorporate constraints into Neural Networks (NN), such as Neural Ordinary Differential Equations (Neural ODEs), have been used. However, these introduce hyperparameters that require manual tuning through trial and error, raising doubts about the successful incorporation of constraints into the generated model. This paper desc
Safety Verification of Wait-Only Non-Blocking Broadcast Protocols
Broadcast protocols are programs designed to be executed by networks of processes. Each process runs the same protocol, and communication between them occurs in synchronously in two ways: broadcast, where one process sends a message to all others, and rendez-vous, where one process sends a message to at most one other process. In both cases, communication is non-blocking, meaning the message is sent even if no proces
Towards Stability of Parameter-Free Optimization
Hyperparameter tuning, particularly the selection of an appropriate learning rate in adaptive gradient training methods, remains a challenge. To address this challenge, we propose a novel parameter-free optimizer, \textsc{AdamG} (Adam with the Golden step size), designed to automatically adapt to diverse optimization problems without task-specific learning-rate tuning. The core technique underlying \textsc{AdamG} is
Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided Cooperative Learning (P2GCL) framework to jointly enhance atmospheric turbulence strength estimation and infrared image restoration. P2GCL involves a cyclic collaboration between two models, i.e., a TMNet measures turbulence strength and outputs the refractive index structure co
Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces
In the field of monocular depth estimation (MDE), many models with excellent zero-shot performance in general scenes emerge recently. However, these methods often fail in predicting non-Lambertian surfaces, such as transparent or mirror (ToM) surfaces, due to the unique reflective properties of these regions. Previous methods utilize externally provided ToM masks and aim to obtain correct depth maps through direct in
Structuring Quantitative Image Analysis with Object Prominence
When photographers or media professionals compose an image, they make deliberate choices about what to foreground and what to background, shaping how viewers interpret visual content. Yet most quantitative approaches to image analysis overlook this structure and treat detected objects as equally important. We introduce a framework for measuring object prominence-- the relative salience of objects in an image-- as a m
In cybersecurity practice, new forms of cyberattacks continuously emerge, deliberately designed to evade defense systems that rely on previously observed behaviors. Motivated by this challenge, we propose a neural network-based method for anomaly detection that does not rely on (1) prior knowledge of anomaly distributions or (2) the availability of real anomalies during training. Our proposed method trains a neural n
ID-Guard: A Universal Framework for Combating Facial Manipulation via Breaking Identification
The misuse of deep learning-based facial manipulation poses a serious threat to civil rights. To prevent such fraud at its source, proactive defense methods have been proposed that embed invisible adversarial perturbations into images, disrupting the manipulation process and rendering the forged output unconvincing to observers. However, non-targeted disruption of the output may leave identifiable facial features int
Plastic pollution presents an escalating global issue, impacting health and environmental systems, with micro- and nanoplastics found across mediums from potable water to air. Traditional methods for studying these contaminants are labor-intensive and time-consuming, necessitating a shift towards more efficient technologies. In response, this paper introduces micro- and nanoplastics (MiNa), a novel and open-source da
Instruction following is a key capability for LLMs. However, recent studies have shown that LLMs often struggle with instructions containing multiple constraints (e.g. a request to create a social media post "in a funny tone" with "no hashtag"). Despite this, most evaluations focus solely on synthetic data. To address this, we introduce RealInstruct, the first benchmark designed to evaluate LLMs'
Scalable Drift Monitoring in Medical Imaging AI
The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model drift and ensuring long-term reliability. To address these challenges, we develop MMC+, an enhanced framework for scalable drift monitoring, building upon the CheXstray framework that introduced real-time drift detection for medical imaging AI models using multi-modal data conc
AffectNet+: A Database for Enhancing Facial Expression Recognition with Soft-Labels
Automated Facial Expression Recognition (FER) is challenging due to intra-class variations and inter-class similarities. FER can be especially difficult when facial expressions reflect a mixture of various emotions (aka compound expressions). Existing FER datasets, such as AffectNet, provide discrete emotion labels (hard-labels), where a single category of emotion is assigned to an expression. To alleviate inter- and
Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
Granger causality (GC) is widely used to infer directed relationships in time-series data. However, its predictive criterion does not by itself distinguish direct causal effects from dependencies induced by common causes, indirect paths, collider conditioning, or model misspecification. We revisit this limitation by interpreting bivariate and multivariate GC through causal Bayesian networks and Reichenbachs common ca
DehazeGS: Seeing Through Fog with 3D Gaussian Splatting
Current novel view synthesis methods are typically designed for high-quality and clean input images. However, in foggy scenes, scattering and attenuation can significantly degrade the quality of rendering. Although NeRF-based dehazing approaches have been developed, their reliance on deep fully connected neural networks and per-ray sampling strategies leads to high computational costs. Furthermore, NeRF's implici
Metareasoning constraints couple narratives, affect and cognition
Narratives and emotions shape thoughts, and thoughts shape our feelings and stories we tell. Why narrative, affective and cognitive states interact remains unclear. We examine whether this mutual relationship reflects constraints on metareasoning - deciding what to think about - imposed by a shared computational state. Combining self-report and quantification of depression narratives using large language models, Stud
Notable events recorded on this day and month across all years.