Record 07052026 · captured 2026-08-25
The world looked up Ted Turner. 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.
Robert Edward Turner III was an American businessman, television producer, media proprietor, and philanthropist. He founded CNN, the first 24-hour cable news channel, and WTBS, which pioneered the superstation concept in cable television. Turner also founded t
Chandrasekaran Joseph Vijay is an Indian politician and former actor who is currently serving as the ninth chief minister of Tamil Nadu since May 2026. He is the founder and president of the political party Tamilaga Vettri Kazhagam (TVK). Prior to entering pol
2026 Tamil Nadu Legislative Assembly election
Elections to appoint the 234 members of the 17th Tamil Nadu Legislative Assembly, the highest body of the Government of Tamil Nadu, were held on 23 April 2026. The results were declared on 4 May 2026 by the Election Commission of India. It recorded the highest
Orthohantavirus is a genus of viruses which includes all hantaviruses that cause disease in humans. Hantaviruses are naturally found primarily in rodents. In general, each hantavirus is carried by one rodent species and each rodent that carries a hantavirus ca
Ratanlal Bhagatram Choudary was an Indian film producer who worked in several film industries, predominantly in Tamil and Telugu along with a few films in Malayalam and Hindi. He was the founder of the production company Super Good Films.
The fifth and final season of the American satirical superhero television series The Boys, the first series in the franchise based on the comic book series of the same name created by Garth Ennis and Darick Robertson, was developed for television by Eric Kripk
The chief minister of Tamil Nadu is the head of government of the Indian state of Tamil Nadu. In accordance with the Constitution of India, the governor is a state's de jure head, while the de facto authority rests with the chief minister. Following elections
Michael Joseph Jackson was an American singer, songwriter, dancer, and philanthropist. Dubbed the "King of Pop", he is widely regarded as one of the most culturally significant figures of the 20th century. His musical achievements broke American racial barrier
Jane Seymour Fonda is an American actress and activist. Fonda's work spans several genres and over seven decades of film and television. She is the recipient of numerous accolades, including two Academy Awards (Oscars), two British Academy Film Awards, eight G
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
2026 West Bengal Legislative Assembly election
Legislative Assembly elections were held in West Bengal to elect all 294 members of the West Bengal Legislative Assembly in two phases on 23 and 29 April 2026, with the votes counted and results for 293 seats released on 4 May 2026. The election saw the defeat
Cinco de Mayo is an annual celebration held on May 5 to celebrate Mexico's victory over the Second French Empire at the Battle of Puebla in 1862, led by General Ignacio Zaragoza. Zaragoza died months after the battle from an illness, however, and a larger Fren
Michael is a 2026 biographical film directed by Antoine Fuqua and written by John Logan. It follows the early life of the American singer Michael Jackson, from his time with the Jackson 5 in the 1960s to the Bad World Tour in the late 1980s. Jackson is portray
Tamil Nadu Legislative Assembly
The Tamil Nadu Legislative Assembly is the unicameral legislature of the Indian state of Tamil Nadu. It has a strength of 234 members, all of whom are democratically elected using the first-past-the-post system. The presiding officer of the assembly is the Spe
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
Tamilaga Vettri Kazhagam is an Indian regional political party active in the state of Tamil Nadu and the union territory of Puducherry. It was founded on 2 February 2024 by actor-turned-politician C. Joseph Vijay, the party's president, and is headquartered in
Gregory Benson is an American comedian, actor, Twitch streamer and director. His production company, Mediocre Films, creates comedic short films, generally for YouTube. He is a frequent director for The Guild.
Daredevil: Born Again season 2
The second season of the American television series Daredevil: Born Again is based on Marvel Comics featuring the character Daredevil. It sees blind vigilante Matt Murdock / Daredevil gathering allies to resist Wilson Fisk, who is the mayor of New York City, a
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
Gavin McKenna is a Canadian professional ice hockey player who is a forward for the Toronto Maple Leafs of the National Hockey League (NHL). McKenna was selected by the Maple Leafs with the first-overall pick in the 2026 NHL entry draft. He played college hock
The Boys is an American satirical superhero streaming television series developed by Eric Kripke for Amazon Prime Video. Based on the comic book series of the same name by Garth Ennis and Darick Robertson, it follows the eponymous team of vigilantes as they co
Mamata Banerjee is an Indian politician and lawyer who served as the eighth chief minister of West Bengal from 2011 to 2026. She was the first and only woman to hold that office. Being the founder and president of the All India Trinamool Congress (AITC), she p
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
Jaafar Jeremiah Jackson is an American actor and singer. A member of the Jackson family, he released his debut single "Got Me Singing" in 2019 but gained popularity for portraying his uncle Michael Jackson in the record-breaking biographical film Michael (2026
Amar Choudary, known professionally as Jiiva, is an Indian actor and film producer who works in Tamil cinema. He is the youngest son of the late film producer R. B. Choudary.
The Boys is an American satirical superhero television series developed by showrunner Eric Kripke that premiered on July 26, 2019, on the streaming service Amazon Prime Video. Kripke also serves as an executive producer, alongside Evan Goldberg, Neal H. Moritz
The Great Shaman Ga Doo-shim is a South Korean streaming television series, starring Kim Sae-ron and Nam Da-reum. It is KakaoTV's first original fantasy mystery series and premiered on July 30, 2021, at 20:00 Korean Standard Time (KST), also airing three hours
Andes virus (ANDV) is the most common cause of hantavirus pulmonary syndrome (HPS) in South America. It is transmitted mainly by the long-tailed pygmy rice rat. In its natural reservoir, ANDV causes a persistent asymptomatic or mild infection and is spread mai
Suvendu Adhikari is an Indian politician who is serving as the 9th Chief Minister of West Bengal since 9 May 2026. He is the first chief minister of West Bengal belonging to the Bharatiya Janata Party (BJP).
The Met Gala, formally known as the Costume Institute Benefit, is the annual haute couture fundraising festival held at and for the benefit of the Metropolitan Museum of Art's Costume Institute on the Museum Mile of Fifth Avenue in Manhattan. The Met Gala is p
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Multi-threaded Memory Efficient Crossover in C++ for Generational Genetic Programming
C++ code snippets from a multi-core parallel memory-efficient crossover for genetic programming are given. They may be adapted for separate generation evolutionary algorithms where large chromosomes or small RAM require no more than M + (2 times nthreads) simultaneously active individuals.
Enhanced Innovized Repair Operator for Evolutionary Multi- and Many-objective Optimization
"Innovization" is a task of learning common relationships among some or all of the Pareto-optimal (PO) solutions in multi- and many-objective optimization problems. Recent studies have shown that a chronological sequence of non-dominated solutions obtained in consecutive iterations during an optimization run also possess salient patterns that can be used to learn problem features to help create new and improv
Hierarchical Vectorization for Portrait Images
Aiming at developing intuitive and easy-to-use portrait editing tools, we propose a novel vectorization method that can automatically convert raster images into a 3-tier hierarchical representation. The base layer consists of a set of sparse diffusion curves (DC) which characterize salient geometric features and low-frequency colors and provide means for semantic color transfer and facial expression editing. The midd
In earlier work we defined a qualitative notion of harm: either harm is caused, or it is not. For practical applications, we often need to quantify harm; for example, we may want to choose the least harmful of a set of possible interventions. In this work, which is an expanded version of an earlier conference paper, we develop a quantitative notion of harm. We first present a quantitative definition of harm in a dete
Analogy between Boltzmann machines and Feynman path integrals
We provide a detailed exposition of the connections between Boltzmann machines commonly utilized in machine learning problems and the ideas already well known in quantum statistical mechanics through Feynman's description of the same. We find that this equivalence allows the interpretation that the hidden layers in Boltzmann machines and other neural network formalisms are in fact discrete versions of path elemen
Explaining the effects of non-convergent sampling in the training of Energy-Based Models
In this paper, we quantify the impact of using non-convergent Markov chains to train Energy-Based models (EBMs). In particular, we show analytically that EBMs trained with non-persistent short runs to estimate the gradient can perfectly reproduce a set of empirical statistics of the data, not at the level of the equilibrium measure, but through a precise dynamical process. Our results provide a first-principles expla
RealLiFe: Real-Time Light Field Reconstruction via Hierarchical Sparse Gradient Descent
With the rise of Extended Reality (XR) technology, there is a growing need for real-time light field reconstruction from sparse view inputs. Existing methods can be classified into offline techniques, which can generate high-quality novel views but at the cost of long inference/training time, and online methods, which either lack generalizability or produce unsatisfactory results. However, we have observed that the i
Machine learning (ML) has gained significant adoption in Android malware detection to address the escalating threats posed by the rapid proliferation of malware attacks. However, recent studies have revealed the inherent vulnerabilities of ML-based detection systems to evasion attacks. While efforts have been made to address this critical issue, many of the existing defensive methods encounter challenges such as lowe
Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?
Sentence transformers are language models designed to perform semantic search. This study investigates the capacity of sentence transformers, fine-tuned on general question-answering datasets for asymmetric semantic search, to associate descriptions of human-generated routes across Great Britain with queries often used to describe hiking experiences. We find that sentence transformers have some zero-shot capabilities
In federated learning (FL), profiling and verifying each client is inherently difficult, which introduces a significant security vulnerability: malicious clients, commonly referred to as Byzantines, can degrade the accuracy of the global model by submitting poisoned updates during training. To mitigate this, the aggregation process at the parameter server must be robust against such adversarial behaviour. Most existi
CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl
The Common Crawl (CC) corpus is the largest open web crawl dataset containing 9.5+ petabytes of data captured since 2008. The dataset is instrumental in training large language models, and as such it has been studied for (un)desirable content, and distilled for smaller, domain-specific datasets. However, to our knowledge, no research has been dedicated to using CC as a source of annotated geospatial data. In this pap
Score-based diffusion models (SDMs) have emerged as a powerful tool for sampling from the posterior distribution in Bayesian inverse problems. However, existing methods often require multiple evaluations of the forward mapping to generate a single sample, resulting in significant computational costs for large-scale inverse problems. To address this, we propose an unconditional representation of the conditional score
Quantifying Geospatial in the Common Crawl Corpus
Large language models (LLMs) exhibit emerging geospatial capabilities, stemming from their pre-training on vast unlabelled text datasets that are often derived from the Common Crawl (CC) corpus. However, the geospatial content within CC remains largely unexplored, impacting our understanding of LLMs' spatial reasoning. This paper investigates the prevalence of geospatial data in recent Common Crawl releases using
Improving Bias Correction Standards by Quantifying its Effects on Treatment Outcomes
With the growing access to administrative health databases, retrospective studies have become crucial evidence for medical treatments. Yet, non-randomized studies frequently face selection biases, requiring mitigation strategies. Propensity score matching (PSM) addresses these biases by selecting comparable populations, allowing for analysis without further methodological constraints. However, PSM has several drawbac
V-RoAst: Visual Road Assessment. Can VLM be a Road Safety Assessor Using the iRAP Standard?
Road safety assessments are critical yet costly, especially in Low- and Middle-Income Countries (LMICs), where most roads remain unrated. Traditional methods require expert annotation and training data, while supervised learning-based approaches struggle to generalise across regions. In this paper, we introduce \textit{V-RoAst}, a zero-shot Visual Question Answering (VQA) framework using Vision-Language Models (VLMs)
Quantum-inspired Reinforcement Learning for Synthesizable Drug Design
Synthesizable molecular design (also known as synthesizable molecular optimization) is a fundamental problem in drug discovery, and involves designing novel molecular structures to improve their properties according to drug-relevant oracle functions (i.e., objective) while ensuring synthetic feasibility. However, existing methods are mostly based on random search. To address this issue, in this paper, we introduce a
Subjective and Objective Quality-of-Experience Evaluation Study for Live Video Streaming
In recent years, live video streaming has gained widespread popularity across various social media platforms. Quality of experience (QoE), which reflects end-users' satisfaction and overall experience, plays a critical role for media service providers to optimize large-scale live compression and transmission strategies to achieve perceptually optimal rate-distortion trade-off. Although many QoE metrics for video-
RoDyGS: Robust Dynamic Gaussian Splatting for Casual Videos
4D reconstruction from casually captured monocular videos is challenging due to inherent ambiguity in reconstructing dynamic 3D geometry. To address this challenge, we introduce Robust Dynamic Gaussian Splatting (RoDyGS), a method that reconstructs dynamic scene representation from casual monocular videos. RoDyGS explicitly separates static and dynamic scene elements, and applies spatiotemporal regularization to enfo
A large language model-type architecture for high-dimensional molecular potential energy surfaces
Computing high-dimensional potential energy surfaces for molecular systems and materials is considered to be a great challenge in computational chemistry with potential impact in a range of areas including the fundamental prediction of reaction rates. In this paper, we design and discuss an algorithm that has similarities to large language models in generative AI and natural language processing. Specifically, we repr
Optimal control and sequential decision making are widely used in many complex tasks. Optimal control over a sequence of natural images is a first step towards understanding the role of vision in control. Here, we formalize this problem as a reinforcement learning task, and derive general conditions under which an image includes enough information to implement an optimal policy. Reinforcement learning is shown to pro
Distilling human mobility models with symbolic regression
Human mobility is a fundamental aspect of social behavior, with broad applications in transportation, urban planning, and epidemic modeling. Represented by the gravity model and the radiation model, established analytical models for mobility phenomena are often discovered by analogy to physical processes. Such discoveries can be challenging and rely on intuition, while the potential of emerging social observation dat
Timber represents an increasingly valuable and versatile resource. However, forestry operations such as harvesting, handling and measuring logs still require substantial human labor in remote environments posing significant safety risks. Progressively automating these tasks has the potential of increasing their efficiency as well as safety, but requires an accurate detection of individual logs as well as live trees a
Fully Guided Neural Schrödinger bridge for Brain MR image synthesis
Multi-modal brain MRI provides essential complementary information for clinical diagnosis. However, acquiring all modalities in practice is often constrained by time and cost. To address this, various methods have been proposed to generate missing modalities from available ones. Existing approaches can be broadly categorized into two types: paired and unpaired methods. While paired methods achieve high synthesis accu
Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers
Parameter shift rules (PSRs) are key techniques for efficient gradient estimation in variational quantum eigensolvers (VQEs). In this paper, we propose its Bayesian variant, where Gaussian processes with appropriate kernels are used to estimate the gradient of the VQE objective. Our Bayesian PSR offers flexible gradient estimation from observations at arbitrary locations with uncertainty information and reduces to th
Positional Encoding in Transformer-Based Time Series Models: A Survey
Recent advancements in transformer-based models have greatly improved time series analysis, providing robust solutions for tasks such as forecasting, anomaly detection, and classification. A crucial element of these models is positional encoding, which allows transformers to capture the intrinsic sequential nature of time series data. This survey systematically examines existing techniques for positional encoding in
Notable events recorded on this day and month across all years.