Record 29042026 · captured 2026-08-25
The world looked up Michael Jackson. 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.
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
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
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
Sabethes (Sabethes) cyaneus is a species of mosquito native to Central America and South America. It is recognized for its striking iridescent blue scales and leg paddles, which are involved in courtship. The larvae are facultative predators, using their sipho
Nathan Lee Chasing His Horse, also known as Nathan Chasing Horse and Nathan Chases His Horse, is a Sicangu Lakota former actor. He is known for his role as the young Lakota character Smiles a Lot in Kevin Costner's 1990 film Dances with Wolves.
The Cottingley Fairies are the subject of a hoax which purports to provide evidence of the existence of fairies. They appear in a series of five photographs taken by Elsie Wright and Frances Griffiths, two young cousins who lived in Cottingley, near Bradford i
The Organization of the Petroleum Exporting Countries is an intergovernmental cartel enabling the co-operation of leading oil-producing and oil-dependent countries in order to collectively influence the global oil market and maximize profit. It was founded on
Michael Akpovie Olise is a professional footballer who plays as a winger or attacking midfielder for Bundesliga club Bayern Munich and the France national team. Widely regarded as one of the best players in the world, he is known for his creative playmaking, t
Nahui Ollin is a 16th-century concept in Aztec/Mexica cosmology with a variety of meanings. Nahui translates to "four," and Ollin translates to "movement" or "motion." Ollin was primarily portrayed in Aztec codices as two interlaced lines, each portrayed with
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
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
Euphoria is an American psychological drama television series created and written by Sam Levinson for HBO. Based on the Israeli miniseries of the same name created by Ron Leshem, the series stars Zendaya as drug-addicted teenager Rue Bennett, who also serves a
Apex is a 2026 survival thriller film directed by Baltasar Kormákur, written by Jeremy Robbins, and starring Charlize Theron and Taron Egerton. It tells the story of a rock climber and kayaker who finds herself being hunted in the wilds of Australia.
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").
Zoë Isabella Kravitz is an American actress, singer, and filmmaker. She has received nominations for a Critics' Choice Award, a Primetime Emmy Award, and a Screen Actors Guild Award. In 2022, she was named by Time magazine as one of the 100 Most Influential Pe
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
Jermaine LaJuane Jacksun is an American musician. A member of the Jackson family, he was second vocalist after his brother Michael of the Jackson 5 from 1964 to 1975, and played bass guitar. In 1983, he rejoined the group, which had been renamed the Jacksons;
Dhurandhar: The Revenge is a 2026 Indian Hindi-language spy action-thriller film written and directed by Aditya Dhar. It is produced by Dhar, Lokesh Dhar, and Jyoti Deshpande under Jio Studios and B62 Studios. It is a sequel to the 2025 film Dhurandhar and the
List of highest-grossing Indian films
This ranking lists the highest-grossing Indian films produced by Indian cinema, based on conservative global box office estimates as reported by organisations classified as green by Wikipedia. The figures are not adjusted for inflation. However, there is no of
Charles III is King of the United Kingdom and 14 other Commonwealth realms.
Donald John Trump is an American politician, media personality, and businessman who is the 47th president of the United States. A member of the Republican Party, he served as the 45th president from 2017 to 2021.
Nicole Rene Glaser is an American stand-up comedian and actress. She has had five television stand-up specials, hosted numerous award shows, and performed at numerous televised roasts, gaining significant popularity for her set on The Roast of Tom Brady. Previ
Terry Gene Bollea, better known by his ring name Hulk Hogan, was an American professional wrestler and media personality. Widely regarded as one of the greatest and most recognized wrestlers of all time, Hogan won multiple championships worldwide, most notably
Melania Knauss Trump is a Slovenian and American former model serving as the first lady of the United States since 2025, a role she previously held from 2017 to 2021 as the third wife of Donald Trump, the 45th and 47th president of the United States. She is th
Marek Heinz is a Czech assistant manager for Sigma Olomouc B since 2025 and a former professional footballer who played as a striker. Heinz was top scorer of the Czech First League in the 2003–04 season, concurrently celebrating the league championship with Ba
Katherine Esther Jackson is the matriarch of the Jackson family of entertainers that includes her children Michael and Janet Jackson. Michael dedicated his sixth studio album Thriller (1982) to her. Janet did the same with her fourth studio album Rhythm Nation
Project Hail Mary is a 2026 American science fiction film produced and directed by Phil Lord and Christopher Miller and written by Drew Goddard, based on the 2021 novel of the same name by Andy Weir. It stars Ryan Gosling, who also produced the film, as Ryland
Verity is a 2018 psychological romantic thriller novel by American author Colleen Hoover. The narrative follows Lowen Ashleigh, a writer who is hired to complete a bestselling book series after its original author, Verity Crawford, is left unable to continue d
Joseph Walter Jackson was an American talent manager and patriarch of the Jackson family of entertainers. He was inducted into the Rhythm and Blues Music Hall of Fame in 2014.
The 2026 Backlash, also promoted as Backlash: Tampa, was a professional wrestling pay-per-view (PPV) and livestreaming event produced by WWE. It was the 21st Backlash event and took place on Saturday, May 9, 2026, at the Benchmark International Arena in Tampa,
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents
Neural Machine Translation (NMT) has shown drastic improvement in its quality when translating clean input, such as text from the news domain. However, existing studies suggest that NMT still struggles with certain kinds of input with considerable noise, such as User-Generated Contents (UGC) on the Internet. To make better use of NMT for cross-cultural communication, one of the most promising directions is to develop
Survey on reinforcement learning for language processing
In recent years some researchers have explored the use of reinforcement learning (RL) algorithms as key components in the solution of various natural language processing tasks. For instance, some of these algorithms leveraging deep neural learning have found their way into conversational systems. This paper reviews the state of the art of RL methods for their possible use for different problems of natural language pr
Laplace-type results characterize the limit of sequence of measures $(π_\varepsilon)_{\varepsilon >0}$ with density w.r.t the Lebesgue measure $(\mathrm{d} π_\varepsilon / \mathrm{d} \mathrm{Leb})(x) \propto \exp[-U(x)/\varepsilon]$ when the temperature $\varepsilon>0$ converges to $0$. If a limiting distribution $π_0$ exists, it concentrates on the minimizers of the potential $U$. Classical results require the
Visuo-Haptic Object Perception for Robots: An Overview
The object perception capabilities of humans are impressive, and this becomes even more evident when trying to develop solutions with a similar proficiency in autonomous robots. While there have been notable advancements in the technologies for artificial vision and touch, the effective integration of these two sensory modalities in robotic applications still needs to be improved, and several open challenges exist. T
Demo: Real-Time Semantic Communications with a Vision Transformer
Semantic communications are expected to enable the more effective delivery of meaning rather than a precise transfer of symbols. In this paper, we propose an end-to-end deep neural network-based architecture for image transmission and demonstrate its feasibility in a real-time wireless channel by implementing a prototype based on a field-programmable gate array (FPGA). We demonstrate that this system outperforms the
Randomization is currently a widely used approach in Sim2Real transfer for data-driven learning algorithms in robotics. Still, most Sim2Real studies report results for a specific randomization technique and often on a highly customized robotic system, making it difficult to evaluate different randomization approaches systematically. To address this problem, we define an easy-to-reproduce experimental setup for a robo
Quantifying the Effect of Feedback Frequency in Interactive Reinforcement Learning for Robotic Tasks
Reinforcement learning (RL) has become widely adopted in robot control. Despite many successes, one major persisting problem can be very low data efficiency. One solution is interactive feedback, which has been shown to speed up RL considerably. As a result, there is an abundance of different strategies, which are, however, primarily tested on discrete grid-world and small scale optimal control scenarios. In the lite
Practical exposure correction via compensation
In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightness. However, existing methodologies tend to be impractical because they lack adaptability to unknown scenes due to restricted modeling patterns and struggle to achieve satisfactory efficiency due to complex computational flows. To tackle these challenges, we establish a ne
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
Bilevel optimization reveals the inner structure of otherwise oblique optimization problems, such as hyperparameter tuning, neural architecture search, and meta-learning. A common goal in bilevel optimization is to minimize a hyper-objective that implicitly depends on the solution set of the lower-level function. Although this hyper-objective approach is widely used, its theoretical properties have not been thoroughl
NUBO: A Transparent Python Package for Bayesian Optimization
NUBO, short for Newcastle University Bayesian Optimisation, is a Bayesian optimization framework for the optimization of expensive-to-evaluate black-box functions, such as physical experiments and computer simulators. Bayesian optimization is a costefficient optimization strategy that uses surrogate modelling via Gaussian processes to represent an objective function and acquisition functions to guide the selection of
A Robust Twin Parametric Margin Support Vector Machine for Multiclass Classification
In this paper, we introduce novel Twin Parametric Margin Support Vector Machine (TPMSVM) models designed to address multiclass classification tasks under feature uncertainty. To handle data perturbations, we construct bounded-by-norm uncertainty set around each training observation and derive the robust counterparts of the deterministic models using robust optimization techniques. To capture complex data structure, w
Conventional medical cancer screening methods are costly, labor-intensive, and extremely difficult to scale. Although AI can improve cancer detection, most systems rely on complex or specialized medical data, making them impractical for large-scale screening. We introduce Can-SAVE, a lightweight AI system that ranks population-wide cancer risks solely based on medical history events. By integrating survival model out
Contrast-Enhanced Gating in GRUs for Robust Low-Data Sequence Learning
Activation functions govern how recurrent networks regulate and transmit information across temporal dependencies. Despite advances in sequence modelling, gated recurrent units (GRUs) still depend on the standard sigmoid and tanh nonlinearities, which can produce weak gate separation and unstable learning, particularly when training data are limited. We introduce squared sigmoid-tanh (SST), a parameter-free activatio
Optimizing BioTac Simulation for Realistic Tactile Perception
Tactile sensing presents a promising opportunity for enhancing the interaction capabilities of today's robots. BioTac is a commonly used tactile sensor that enables robots to perceive and respond to physical tactile stimuli. However, the sensor's non-linearity poses challenges in simulating its behavior. In this paper, we first investigate a BioTac simulation that uses temperature, force, and contact point po
The Russian Legislative Corpus
We present a comprehensive corpus of Russian primary and secondary legislation adopted between 1991 and 2025, comprising 304,382 texts (194,425,905 tokens). The corpus is available in two versions: the basic version contains texts with simple metadata, while the detailed version includes both the original texts and their equivalents converted to the Universal Dependencies CoNLL-U format, annotated with parts of speec
TouchAI: Exploring human-AI perceptual alignment in touch through language model representations
Aligning large language models (LLMs) behaviour with human intent is critical for future AI. An important yet often overlooked aspect of this alignment is the perceptual alignment. Perceptual modalities like touch are more multifaceted and nuanced compared to other sensory modalities such as vision. This work investigates how well LLMs align with human touch experiences using the "textile hand" task. We creat
Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
Uncertainty quantification (UQ) has emerged as a promising approach for detecting hallucinations and low-quality output of Large Language Models (LLMs). However, obtaining proper uncertainty scores is complicated by the conditional dependency between the generation steps of an autoregressive LLM because it is hard to model it explicitly. Here, we propose to learn this dependency from attention-based features. In part
Accuracy Improvement of Cell Image Segmentation Using Feedback Former
Semantic segmentation of microscopy cell images by deep learning is a significant technique. We considered that the Transformers, which have recently outperformed CNNs in image recognition, could also be improved and developed for cell image segmentation. Transformers tend to focus more on contextual information than on detailed information. This tendency leads to a lack of detailed information for segmentation. Ther
BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving
Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single dataset, typically nuScenes. This practice leads to the development of highly specialized models that may fail when faced with different environments or sensor setups, a problem known as domain shift. In this paper, we conduct a comprehensive cross-dataset evaluation o
In this study, I investigate how generative artificial intelligence (AI) systems reproduce and reinforce societal biases, with a specific focus on the representation of women, Black individuals, age groups, and people with visible disabilities in AI-generated occupational images. I analyzed 444 images generated by Microsoft Designer, Meta AI, and Ideogram across 37 occupations and found significant disparities in rep
FARM: Enhancing Molecular Representations with Functional Group Awareness
We introduce Functional Group-Aware Representations for Small Molecules (FARM), a novel foundation model designed to bridge the gap between SMILES, natural language, and molecular graphs. The key idea behind FARM is the incorporation of functional group (FG) annotations at the atomic level, enabling both FG-enhanced SMILES and FG graphs. In this representation, SMILES strings are enriched with functional group inform
PortraVec: Image-Based Portrait Vectorization with Text-Guided Manipulation
While portrait sketch generation is a special task in sketch synthesis, most existing methods are pixel-based, limiting their interpretability and editability. With the rise of vector generation techniques, representing sketches using vector elements may provide more flexible manipulation. However, due to the overlapping nature of vector graphics and the coarse detail modeling, existing vectorization methods struggle
Pathology foundation models (PFMs) have emerged as powerful pretrained encoders for computational pathology, but their robustness under clinically relevant distribution shifts remains insufficiently understood. We benchmark the robustness of recent PFMs in the setting of prostate cancer grading from whole-slide images (WSIs). Using the PANDA dataset, we evaluate PFMs as frozen patch-level feature extractors within we
Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health
Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, accurate automated systems to support clinical decision-making during delivery are currently lacking. To address this gap, we propose Artificial Intelligence for Modeling and Explaining Neonatal Health (AIMEN), a deep learning framework that predicts adverse labor outcomes f
AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization
Image labeling is a critical bottleneck in the development of computer vision technologies, often constraining machine learning performance due to the time-intensive nature of manual annotations. This work introduces a novel approach that leverages outpainting to mitigate annotated data scarcity by generating artificial contexts and annotations, significantly reducing labeling efforts. We apply this technique to a pa
Notable events recorded on this day and month across all years.