Record 21112025 · captured 2026-08-25
The world looked up Google Chrome. 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.
Google Chrome is a cross-platform web browser developed by Google. It was launched in September 2008 for Microsoft Windows and was built with free software components from Apple WebKit and Mozilla Firefox. Versions for Linux, macOS, iOS, iPadOS, and Android we
The Epstein files are a partially released collection of millions of documents, images, videos, and emails related to the activities of American financier and convicted child sex offender Jeffrey Epstein, including his social circle of public figures, politici
Ryan James Wedding is a Canadian former Olympic snowboarder and alleged drug lord. He represented Canada at the 2002 Winter Olympics in the men's parallel giant slalom event. After retiring from snowboarding, he allegedly became an international drug trafficke
Jeffrey Edward Epstein was an American financier and child sex offender. He began his career as a math teacher at the Dalton School in New York City, before entering the banking and finance sector. Over several decades, he made much of his fortune providing ta
Gary Mounfield, known professionally as Mani, was an English bassist, best known for being a member of the rock bands the Stone Roses and Primal Scream.
Richard Bruce Cheney was an American politician and businessman who served as the 46th vice president of the United States under President George W. Bush from 2001 to 2009. Considered the main architect of the Iraq War, Cheney has been called the most powerful
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
Thomas Read Wilson is an English television presenter, author, actor and singer. He is best known as the client coordinator on the E4 reality television series; Celebs Go Dating. In 2021, he was the runner-up on Celebrity Best Home Cook. In 2025, he was the ru
2026 FIFA World Cup qualification
The 2026 FIFA World Cup qualification decided the 45 teams that joined hosts Canada, Mexico, and the United States at the 2026 FIFA World Cup.
This is a list of lists of deaths of significant people, organized by year. New deaths articles are added to their respective month and then linked below.
Wicked: For Good is a 2025 musical fantasy film directed by Jon M. Chu and written by Winnie Holzman and Dana Fox. The sequel to Wicked (2024), it adapts the second act of the 2003 stage musical by Stephen Schwartz and Holzman, which was loosely based on Grego
Lawrence Henry Summers is an American economist. He served as the 71st United States Secretary of the Treasury from 1999 to 2001, the 27th president of Harvard University from 2001 to 2006, and the eighth director of the National Economic Council from 2009 to
Bruce Lee was a Hong Kong and American martial artist, actor, and filmmaker. He was the founder of Jeet Kune Do, a hybrid martial arts philosophy, which was formed from his experiences in unarmed fighting and self-defense—as well as eclectic, Zen Buddhist, and
Vogue Williams is an Irish media personality, presenter and model. After appearing on the reality series Fade Street (2010–2011), she went on to participate in the Australian version of Dancing with the Stars in 2012, as well as appearing on Stepping Out in 20
2026 FIFA World Cup qualification (UEFA)
The European section of the 2026 FIFA World Cup qualification competition acted as qualifiers for the 2026 FIFA World Cup, that was held in Canada, Mexico and the United States, for national teams that were members of the Union of European Football Association
Lainey Denay Wilson is an American country singer-songwriter and actress. She performed at an early age, before going to Nashville to pursue a career as a pop music performer. In 2014, she released her first album on Cupit, followed by a second on Lone Chief i
The Nuremberg trials were international criminal trials held by France, the Soviet Union, the United Kingdom, and the United States against leaders of defeated Nazi Germany for plotting and carrying out invasions of several countries across Europe and committi
Nitish Kumar is an Indian politician from Bihar. He is currently serving as a Member of Parliament in the Rajya Sabha. The national president of the Janata Dal (United), he was the longest serving Chief Minister of Bihar, serving briefly in 2000, from 2005 to
Sheila Cherfilus-McCormick is an American politician and businesswoman who served as the U.S. representative for Florida's 20th congressional district from 2022 until her resignation in 2026. She is a member of the Democratic Party.
2026 FIFA World Cup qualification – UEFA second round
The UEFA second round of the qualification tournament for the 2026 FIFA World Cup, also known as the UEFA play-offs or European play-offs, was contested by sixteen teams from the UEFA segment of qualifying. The play-offs determined the final four European team
Cynthia Erivo is a British actress and singer. Known for her work on both stage and screen, she is the recipient of several accolades and one of few individuals nominated for an Emmy, a Grammy, an Oscar, and a Tony Award (EGOT), winning all but the Oscar. Eriv
2026 FIFA World Cup qualification (inter-confederation play-offs)
The inter-confederation play-offs of the 2026 FIFA World Cup qualification tournament determined two qualification spots for the 2026 FIFA World Cup, played in Canada, Mexico, and the United States. The play-offs took place on 26 and 31 March 2026 at two venue
Miss Universe 2025 was the 74th Miss Universe pageant, held at the Impact Challenger Hall in Pak Kret, Nonthaburi, Thailand, on 21 November 2025.
James Abram Garfield was the 20th president of the United States, serving from March 1881 until his death in September that year after being shot in July. A preacher, lawyer, and Civil War general, Garfield served nine terms in the United States House of Repre
A company is a legal entity representing an association of legal persons with a shared objective, such as generating profit or benefiting society. Depending on the jurisdiction, companies can take on various forms, including voluntary associations, nonprofit o
The Hunger Games: Sunrise on the Reaping
The Hunger Games: Sunrise on the Reaping is an upcoming American dystopian film directed by Francis Lawrence from a screenplay by Billy Ray and Michael Lesslie. Based on the 2025 novel Sunrise on the Reaping by Suzanne Collins, it serves as both a sequel to Th
Stephen Wilson Jr. is an American country and rock singer, guitarist, and songwriter.
The Beast in Me is an American psychological crime thriller television miniseries for Netflix, starring Claire Danes and Matthew Rhys. Created by Gabe Rotter, the series follows an author (Danes) who begins writing a book about her new next-door neighbor (Rhys
Wicked, is a 2024 American musical fantasy film directed by Jon M. Chu and written by Winnie Holzman and Dana Fox. It adapts the first act of the 2003 stage musical by Stephen Schwartz and Holzman, which was loosely based on Gregory Maguire's 1995 novel, a re-
Ariana Grande-Butera is an American singer, songwriter, and actress. Known for her four-octave vocal range, which extends into the whistle register, she is an influential figure in popular music. Publications such as Rolling Stone and Billboard have deemed Gra
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Less is More: Data-Efficient Adaptation for Controllable Text-to-Video Generation
Fine-tuning large-scale text-to-video diffusion models to add new generative controls, such as those over physical camera parameters (e.g., shutter speed or aperture), typically requires vast, high-fidelity datasets that are difficult to acquire. In this work, we propose a data-efficient fine-tuning strategy that learns these controls from sparse, low-quality synthetic data. We show that not only does fine-tuning on
EduMod-LLM: A Modular Approach for Designing Flexible and Transparent Educational Assistants
With the growing use of Large Language Model (LLM)-based Question-Answering (QA) systems in education, it is critical to evaluate their performance across individual pipeline components. In this work, we introduce {\model}, a modular function-calling LLM pipeline, and present a comprehensive evaluation along three key axes: function calling strategies, retrieval methods, and generative language models. Our framework
Learning to Debug: LLM-Organized Knowledge Trees for Solving RTL Assertion Failures
Debugging is the dominant cost in modern hardware verification, where assertion failures are among the most frequent and expensive to resolve. While Large Language Models (LLMs) show promise, they often fail to capture the precise, reusable expertise that engineers apply, leading to inaccurate responses. We propose GROVE, a hierarchical knowledge management framework that learns and organizes reusable debugging exper
Unified Class and Domain Incremental Learning with Mixture of Experts for Indoor Localization
Indoor localization using machine learning has gained traction due to the growing demand for location-based services. However, its long-term reliability is hindered by hardware/software variations across mobile devices, which shift the model's input distribution to create domain shifts. Further, evolving indoor environments can introduce new locations over time, expanding the output space to create class shifts, maki
Foundation models hold promise for specialized medical imaging tasks, though their effectiveness in breast imaging remains underexplored. This study leverages BiomedCLIP as a foundation model to address challenges in model generalization. BiomedCLIP was adapted for automated BI-RADS breast density classification using multi-modality mammographic data (synthesized 2D images, digital mammography, and digital breast tom
APRIL: Annotations for Policy evaluation with Reliable Inference from LLMs
Off-policy evaluation (OPE) estimates the value of a contextual bandit policy prior to deployment. As such, OPE plays a critical role in ensuring safety in high-stakes domains such as healthcare. However, standard OPE approaches are limited by the size and coverage of the behavior dataset. While previous work has explored using expert-labeled counterfactual annotations to enhance dataset coverage, obtaining such anno
Point of Order: Action-Aware LLM Persona Modeling for Data-Grounded Civic Deliberation
LLM-based simulations can enable controlled studies of civic deliberation, but current systems lack speaker-attributed data and methods for evaluating long-form institutional behavior. ASR transcripts typically use anonymous labels such as $Speaker\_1$, preventing models from learning stable participant behavior across meetings. We present a reproducible pipeline that converts public Zoom recordings into speaker-attr
Score-Regularized Joint Sampling with Importance Weights for Flow Matching
Flow matching models effectively represent complex distributions, yet estimating expectations of functions of their outputs remains challenging under limited sampling budgets. Independent sampling often yields high-variance estimates, especially when rare but high-impact outcomes dominate the expectation. We propose a non-IID sampling framework that jointly draws multiple samples to cover diverse, salient regions of
REXO: Indoor Multi-View Radar Object Detection via 3D Bounding Box Diffusion
Multi-view indoor radar perception has drawn attention due to its cost-effectiveness and low privacy risks. Existing methods often rely on {implicit} cross-view radar feature association, such as proposal pairing in RFMask or query-to-feature cross-attention in RETR, which can lead to ambiguous feature matches and degraded detection in complex indoor scenes. To address these limitations, we propose \textbf{REXO} (mul
A Stitch in Time: Learning Procedural Workflow via Self-Supervised Plackett-Luce Ranking
Procedural activities, ranging from routine cooking to complex surgical operations, are highly structured sequences of actions performed in a specific temporal order. Despite the success of current self-supervised learning (SSL) methods on static images and short clips, these models often overlook the underlying sequential structure of such activities. We expose this lack of procedural awareness with a motivating exp
Pillar-0: A New Frontier for Radiology Foundation Models
Radiology plays an integral role in modern medicine, yet rising imaging volumes have far outpaced workforce growth. Foundation models offer a path toward assisting with the full spectrum of radiology tasks, but existing medical models remain limited: they process volumetric CT and MRI as low-fidelity 2D slices, discard critical grayscale contrast information, and lack evaluation frameworks that reflect real clinical
MultiGA: Leveraging Multi-Source Seeding in Genetic Algorithms
In this paper, we introduce, MultiGA, an optimization framework which applies genetic algorithm principles to address complex natural language tasks and reasoning problems by sampling from a diverse population of LLMs to initialize the population of candidate solutions. MultiGA generates a range of outputs from various parent LLMs and uses a neutral fitness function to evaluate them. Through an iterative recombinatio
A cross-species neural foundation model for end-to-end speech decoding
Speech brain-computer interfaces (BCIs) aim to restore communication for people with paralysis by translating neural activity into text. Most systems use cascaded frameworks that decode phonemes before assembling sentences with an n-gram language model (LM), preventing joint optimization of all stages simultaneously. Here, we introduce an end-to-end BraIn-to-Text (BIT) framework that translates neural activity into c
Episodic Memory in Agentic Frameworks: Suggesting Next Tasks
Agentic frameworks powered by Large Language Models (LLMs) can be useful tools in scientific workflows by enabling human-AI co-creation. A key challenge is recommending the next steps during workflow creation without relying solely on LLMs, which risk hallucination and require fine-tuning with scarce proprietary data. We propose an episodic memory architecture that stores and retrieves past workflows to guide agents
$Δ$-ML Ensembles for Selecting Quantum Chemistry Methods to Compute Intermolecular Interactions
Ab initio quantum chemical methods for accurately computing interactions between molecules have a wide range of applications but are often computationally expensive. Hence, selecting an appropriate method based on accuracy and computational cost remains a significant challenge due to varying performance of methods. In this work, we propose a framework based on an ensemble of $Δ$-ML models trained on features extracte
SG-OIF: A Stability-Guided Online Influence Framework for Reliable Vision Data
Approximating training-point influence on test predictions is critical for deploying deep-learning vision models, essential for locating noisy data. Though the influence function was proposed for attributing how infinitesimal up-weighting or removal of individual training examples affects model outputs, its implementation is still challenging in deep-learning vision models: inverse-curvature computations are expensiv
Hidden markov model to predict tourists visited place
Nowadays, social networks are becoming a popular way of analyzing tourist behavior, thanks to the digital traces left by travelers during their stays on these networks. The massive amount of data generated; by the propensity of tourists to share comments and photos during their trip; makes it possible to model their journeys and analyze their behavior. Predicting the next movement of tourists plays a key role in tour
AEGIS: Preserving privacy of 3D Facial Avatars with Adversarial Perturbations
The growing adoption of photorealistic 3D facial avatars, particularly those utilizing efficient 3D Gaussian Splatting representations, introduces new risks of online identity theft, especially in systems that rely on biometric authentication. While effective adversarial masking methods have been developed for 2D images, a significant gap remains in achieving robust, viewpoint-consistent identity protection for dynam
This article presents a state-of-the-art review of recent advances aimed at transforming traditional Failure Mode and Effects Analysis (FMEA) into a more intelligent, data-driven, and semantically enriched process. As engineered systems grow in complexity, conventional FMEA methods, largely manual, document-centric, and expert-dependent, have become increasingly inadequate for addressing the demands of modern systems
Temperature in SLMs: Impact on Incident Categorization in On-Premises Environments
SOCs and CSIRTs face increasing pressure to automate incident categorization, yet the use of cloud-based LLMs introduces costs, latency, and confidentiality risks. We investigate whether locally executed SLMs can meet this challenge. We evaluated 21 models ranging from 1B to 20B parameters, varying the temperature hyperparameter and measuring execution time and precision across two distinct architectures. The results
M^3-Bench: Multi-Modal, Multi-Hop, Multi-Threaded Tool-Using MLLM Agent Benchmark
We present M^3-Bench, the first benchmark for evaluating multimodal tool use under the Model Context Protocol. The benchmark targets realistic, multi-hop and multi-threaded workflows that require visual grounding and textual reasoning, cross-tool dependencies, and persistence of intermediate resources across steps. We introduce a similarity-driven alignment that serializes each tool call, embeds signatures with a sen
Ternary Gamma Semirings as a Novel Algebraic Framework for Learnable Symbolic Reasoning
Binary semirings such as the tropical, log, and probability semirings form a core algebraic tool in classical and modern neural inference systems, supporting tasks like Viterbi decoding, dynamic programming, and probabilistic reasoning. However, these structures rely on a binary multiplication operator and therefore model only pairwise interactions. Many symbolic AI tasks are inherently triadic, including subject-pre
Learning the Value of Value Learning
Standard decision frameworks address uncertainty about facts but assume fixed options and values. We extend the Jeffrey-Bolker framework to model refinements in values and prove a value-of-information theorem for axiological refinement. In multi-agent settings, we establish that mutual refinement will characteristically transform zero-sum games into positive-sum interactions and yield Pareto-improvements in Nash barg
The Rapid Growth of AI Foundation Model Usage in Science
We present the first large-scale analysis of AI foundation model usage in science - not just citations or keywords. We find that adoption has grown rapidly, at nearly-exponential rates, with the highest uptake in Linguistics, Computer Science, and Engineering. Vision models are the most used foundation models in science, although language models' share is growing. Open-weight models dominate. As AI builders increase
Understanding Counting Mechanisms in Large Language and Vision-Language Models
Counting is one of the fundamental abilities of large language models (LLMs) and large vision-language models (LVLMs). This paper examines how these foundation models represent and compute numerical information in counting tasks. We use controlled experiments with repeated textual and visual items and analyze counting in LLMs and LVLMs through a set of behavioral, observational, and causal mediation analyses. To this
Notable events recorded on this day and month across all years.