Record 06082026 · captured 2026-08-25
The world looked up Perez Hilton. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
Complete record JSON
What the most people looked up, ranked by Wikipedia pageviews for that day.
Mario Armando Lavandeira Jr., known professionally as Perez Hilton, is an American blogger, columnist, and media personality. His blog is known for posts covering gossip items about celebrities, and for posting tabloid photos over which he has added his own ca
Abdulrahman Mohamed El-Sayed, commonly known as Abdul El-Sayed, is an American politician and epidemiologist who is the Democratic nominee in the 2026 United States Senate election in Michigan. A progressive member of the Democratic Party, El-Sayed was a candi
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
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
Pradeep Rawat was an Indian actor who worked predominantly in Telugu, Hindi and Tamil language films. Notable for playing villainous roles, Rawat's first appearance was in B.R. Chopra's Mahabharat as Ashwatthama.
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
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 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
Haley Maria Stevens is an American politician serving as the U.S. representative from Michigan's 11th congressional district since 2019. A member of the Democratic Party, Stevens represents most of urbanized Oakland County, including many of Detroit's northern
2026 United States Senate election in Michigan
The 2026 United States Senate election in Michigan will be held on November 3, 2026, to elect a member of the United States Senate to represent the state of Michigan. Democratic former Wayne County health director Abdul El-Sayed and Republican former congressm
.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
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
George Alexander Lombard Jr. is an American professional baseball shortstop for the New York Yankees of Major League Baseball (MLB). He was selected by the Yankees in the first round of the 2023 MLB draft and made his MLB debut in 2026.
Jeans are a type of trousers. Below is a list of denim jeans brands.
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").
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
2026 in film is an overview of events in the film industry scheduled to occur in 2026. Best Picture Academy Award-winners All Quiet on the Western Front and Cimarron entered the public domain this year.
Ted Lasso is an American sports comedy-drama television series developed by Jason Sudeikis, Bill Lawrence, Brendan Hunt, and Joe Kelly. It is based on a character Sudeikis portrayed in a series of promotional media for NBC Sports' coverage of England's soccer
George Paul Lombard Sr. is an American professional baseball coach and former outfielder who is the bench coach for the Detroit Tigers of Major League Baseball (MLB).
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
Mike Rogers (Michigan politician)
Michael J. Rogers is an American law enforcement officer and politician who served from 2001 to 2015 as the U.S. representative for Michigan's 8th congressional district. A member of the Republican Party, he chaired the United States House Permanent Select Com
Trabzonspor Kulübü is a Turkish professional sports club located in the city of Trabzon, located in northeastern Turkey. Established in 1967 through the merger of several local clubs, Trabzonspor is one of the most prominent football clubs in Turkish history.
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
Max Leonard Miller is an American politician who has served as the U.S. representative for Ohio's 7th congressional district since 2023. A member of the Republican Party, he previously served as a political appointee in the first Donald Trump administration.
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
Lloyd John Robertson was a Canadian journalist and news anchor. He served as the chief anchor and senior editor of CTV's national evening newscast, CTV National News with Lloyd Robertson, from 1984 until 2011, when he retired from the broadcast. Robertson subs
Nirmal Purja, also known as Nims or Nimsdai, was a Nepali-British mountaineer. Before pursuing a career in mountaineering, he served in the British Army with the Brigade of Gurkhas and later in the Special Boat Service (SBS), the special forces unit of the Roy
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Exploring the Impacts from Datasets to Monocular Depth Estimation (MDE) Models with MineNavi
Current computer vision tasks based on deep learning require a huge amount of data with annotations for model training or testing, especially in some dense estimation tasks, such as optical flow segmentation and depth estimation. In practice, manual labeling for dense estimation tasks is very difficult or even impossible, and the scenes of the dataset are often restricted to a small range, which dramatically limits t
Spiking Neural Networks (SNNs) have emerged as a hardware efficient architecture for classification tasks. The challenge of spike-based encoding has been the lack of a universal training mechanism performed entirely using spikes. There have been several attempts to adopt the powerful backpropagation (BP) technique used in non-spiking artificial neural networks (ANN): (1) SNNs can be trained by externally computed num
Leveraging Machine Learning to Gain Insights on Quantum Thermodynamic Entropy
We present a thermodynamic analysis of a quantum engine that uses a single quantum particle as its working fluid, inspired by Szilard's classical single-particle engine. Our design is modeled after the classically-chaotic Szilard Map and involves a thermodynamic cycle of measurement, thermal-energy extraction, and memory reset. Our focus is on investigating the thermodynamic costs associated with observing and co
On The Suitability of Differential Dataflow For Datalog Interpretation In Highly Dynamic Settings
In the domain of knowledge representation and reasoning within AI, datalog engines play an ever-increasingly crucial role. The crux of their operation lies in materialization: the evaluation of a data- log program and its incorporation into a database. This operation becomes complex and resource-intensive, especially when the data is highly dynamic, as it is common in distributed environments. Thus, incremental mater
Composing Reinforcement Learning Policies, with Formal Guarantees
We propose a novel framework to controller design in environments with a two-level structure: a known high-level graph ("map") in which each vertex is populated by a Markov decision process, called a "room". The framework "separates concerns" by using different design techniques for low- and high-level tasks. We apply reactive synthesis for high-level tasks: given a specification as a logical
Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection
Phishing emails continue to pose a significant threat, causing financial losses and security breaches. This study addresses limitations in existing research, such as reliance on proprietary datasets and lack of real-world application, by proposing a high-performance machine learning model for email classification. Utilizing a comprehensive and largest available public dataset, the model achieves a f1 score of 0.99 an
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
This paper explores methods for verifying the properties of Binary Neural Networks (BNNs), focusing on robustness against adversarial attacks. Despite their lower computational and memory needs, BNNs, like their full-precision counterparts, are also sensitive to input perturbations. Established methods for solving this problem are predominantly based on Satisfiability Modulo Theories and Mixed-Integer Linear Programm
E$^2$M: Double Bounded $α$-Divergence Optimization for Tensor-based Discrete Density Estimation
Tensor-based discrete density estimation requires flexible modeling and proper divergence criteria to enable effective learning; however, traditional approaches using $α$-divergence face analytical challenges due to the $α$-power terms in the objective function, which hinder the derivation of closed-form update rules. We present a generalization of the expectation-maximization (EM) algorithm, called the E$^2$M algori
Land Use Land Cover (LULC) analysis on satellite images using deep learning-based methods is significantly helpful in understanding the geography, socio-economic conditions, poverty levels, and urban sprawl in developing countries. Recent works involve segmentation with LULC classes such as farmland, built-up areas, forests, meadows, water bodies, etc. Training deep learning methods on satellite images requires large
GFlowNet Training by Policy Gradients
Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with policy-dependent rewards, that bridges keeping flow balance of GFlowNets to optimizing the expected accumulated reward in traditional Reinforcement-Learning (RL). This enables the derivation of new policy-based GFlowNet training methods, in c
Unforgettable Generalization in Language Models
When language models (LMs) are trained to forget (or "unlearn'') a skill, how precisely does their behavior change? We study the behavior of transformer LMs in which tasks have been forgotten via fine-tuning on randomized labels. Such LMs learn to generate near-random predictions for individual examples in the "training'' set used for forgetting. Across tasks, however, LMs exhibit extreme vari
LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content
The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required world knowledge to perform effectively on multiple downstream tasks. However, one downside of scraping data from the web can be the potential sacrifice of the benchmarks on which the abilities of these models are often evaluated. To safeguard against test data contaminat
Protein engineering is important for biomedical applications, but conventional approaches are often inefficient and resource-intensive. While deep learning (DL) models have shown promise, their training or implementation into protein engineering remains challenging for biologists without specialized computational expertise. To address this gap, we propose AutoProteinEngine (AutoPE), an agent framework that leverages
The exponential growth in protein-related databases and scientific literature, combined with increasing demands for efficient biological information retrieval, has created an urgent need for unified and accessible search methods in protein engineering research. We present TourSynbio-Search, a novel bioinformatics search agent framework powered by the TourSynbio-7B protein multimodal large language model (LLM), design
Physics-informed Machine Learning for Battery Pack Thermal Management
With the popularity of electric vehicles, the demand for lithium-ion batteries is increasing. Temperature significantly influences the performance and safety of batteries. Battery thermal management systems can effectively control the temperature of batteries; therefore, the performance and safety can be ensured. However, the development process of battery thermal management systems is time-consuming and costly due t
Comparative Analysis of Black-Box and White-Box Machine Learning Model in Phishing Detection
Background: Explainability in phishing detection model can support a further solution of phishing attack mitigation by increasing trust and understanding how phishing can be detected. Objective: The aims of this study to determine and best recommendation to apply an approach which has several components with abilities to fulfil the critical needs Methods: A methodology starting with analyzing both black-box and white
Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin
Recent works exploring the training dynamics of homogeneous neural network weights under gradient flow with small initialization have established that in the early stages of training, the weights remain small and near the origin, but converge in direction. Building on this, the current paper studies the gradient flow dynamics of homogeneous neural networks with locally Lipschitz gradients, after they escape the origi
MathDebugger: Detecting and Diagnosing Errors in Synthetic Mathematical Data
Synthetic mathematical data has become an important resource for scaling the reasoning capabilities of large language models, yet errors in generated questions and solutions can substantially undermine its value. We introduce MathDebugger, a type-aware benchmark for evaluating whether models can detect and diagnose errors in synthetic mathematical data. MathDebugger contains 2,000 correct questions, 2,000 erroneous q
Spatial Distillation based Distribution Alignment (SDDA) for Cross-Headset EEG Classification
A non-invasive brain-computer interface (BCI) enables direct interaction between the user and external devices, typically via electroencephalogram (EEG) signals. However, decoding EEG signals across different headsets remains a significant challenge due to differences in the number and locations of the electrodes. To address this challenge, we propose a spatial distillation based distribution alignment (SDDA) approac
GRALS: GCN-Guided Redundancy-Aware Local Search for Minimum Vertex Cover
The minimum vertex cover (MVC) problem seeks to identify the smallest set of vertices that cover all edges in an undirected graph. As a fundamental NP-hard combinatorial optimization problem, MVC has been widely studied due to its applications in network analysis and system design. For large-scale instances, local search heuristics are among the most effective approaches, offering a practical trade-off between soluti
Large-Small Model Collaboration for Enhancing Edge-Deployed Small Models
Edge devices host domain-specific small language models (SLMs) with limited resources, while private clouds offer larger LLMs. We propose G-Boost, an adaptive edge-cloud framework that improves a deployed SLM's task performance without parameter updates. It formulates reasoning as a tree search, choosing at each step between SLM-only inference and SLM-LLM logit fusion---which transfers domain knowledge from the S
Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability
One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in the physical world. Specifically, imitation policy based on neural network may generate hallucinations, leading to inaccurate behaviors that impact the safety of real-world applications. To address this issue, this paper proposes the Curiosity-Diffuser, aimed at guiding the con
Large Language Models (LLMs) are increasingly vulnerable to sophisticated multi-turn manipulation attacks, where adversaries strategically build context through seemingly benign conversational turns to circumvent safety measures and elicit harmful or unauthorized responses. These attacks exploit the temporal nature of dialogue to evade single-turn detection methods, representing a critical security vulnerability with
ZoomV: Temporal Zoom-in for Efficient Long Video Understanding
Long video understanding poses a fundamental challenge for large video-language models (LVLMs) due to the overwhelming number of frames and the risk of losing essential context through naive downsampling. Inspired by the way humans watch videos on mobile phones, constantly zooming in on frames of interest, we propose ZoomV, a query-aware temporal zoom-in framework designed for efficient and accurate long video unders
Rating systems on accommodation platforms suffer from a familiar problem: nearly every listing displays a nearly perfect score, so the number that is supposed to separate good listings from bad ones barely varies. Whether the review text accumulating beneath those scores still carries usable information is an open question. I ask a dynamic version of it: does the text guests have already written predict where a listi
Notable events recorded on this day and month across all years.