Record 12032026 · captured 2026-08-25
The world looked up Bam Adebayo. 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.
Edrice Femi "Bam" Adebayo is an American professional basketball player for the Miami Heat of the National Basketball Association (NBA). He played college basketball for the Kentucky Wildcats before being selected by the Heat with the 14th overall pick in the
Since 28 February 2026, the United States and Israel have been at war with Iran and its regional allies. Hostilities broke out after US–Israeli airstrikes killed several Iranian officials, including Supreme Leader Ali Khamenei. The strikes were launched amid o
List of NBA single-game scoring leaders
This is a complete listing of National Basketball Association players who have scored 60 or more points in a regular season game.
Mojtaba Hosseini Khamenei is an Iranian Shia cleric and politician who has served as the third supreme leader of Iran since 2026. A member of the Khamenei family and the second son of second supreme leader Ali Khamenei, he previously served as Vakil of the Sup
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
The 2026 World Baseball Classic was an international professional baseball tournament between 20 national baseball teams, and the sixth iteration of the World Baseball Classic (WBC). It ran from March 5 to 17, 2026. The pool-play rounds were played in LoanDepo
One Piece is a fantasy adventure television series developed by Matt Owens and Steven Maeda for Netflix. The series is a live-action adaptation of the 1997 Japanese manga series One Piece by Eiichiro Oda, who also serves as a creative consultant. It is produce
Antonín Kinský (footballer, born 2003)
Antonín Kinský is a Czech professional footballer who plays as a goalkeeper for Premier League club Tottenham Hotspur.
The Strait of Hormuz is a waterway between the Persian Gulf and the Gulf of Oman. On the north coast lies Iran, and on the south coast lies the Musandam Peninsula under the Musandam Governorate of Oman, with a portion of the southwest of the peninsula under th
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
War Machine is a 2026 military science fiction action film directed, co-produced, and co-written by Patrick Hughes. It stars Alan Ritchson, Dennis Quaid, Stephan James, Jai Courtney, Esai Morales, Keiynan Lonsdale, and Daniel Webber, and follows a staff sergea
Maxx Robert Crosby is an American professional football defensive end for the Las Vegas Raiders of the National Football League (NFL). He played college football for the Eastern Michigan Eagles and was selected by the Oakland Raiders in the fourth round of the
Ali Hosseini Khamenei was an Iranian politician and Shia cleric who served as the second supreme leader of Iran from 1989 until his assassination in 2026. A member of the Khamenei family who held the title Grand Ayatollah, he previously served as the third pre
A'ja Riyadh Wilson is an American professional basketball player for the Las Vegas Aces of the Women's National Basketball Association (WNBA). Wilson is regarded by many as the best basketball player of her generation, and is widely considered one of the great
A seamount is a large submarine landform that rises from the ocean floor without reaching the water surface, and thus is not an island, islet, or cliff-rock. Seamounts are typically formed from extinct volcanoes that rise abruptly and are usually found rising
Gina Joy Carano is an American actress and mixed martial artist. She competed in Elite Xtreme Combat and Strikeforce from 2006 to 2009, where she compiled a 7–1 record. Her popularity led to her being called the "face of women's MMA", although Carano rejected
Scarpetta is an American crime drama television series developed by Liz Sarnoff and based on the book series of the same name by Patricia Cornwell. It stars Nicole Kidman as the titular character as Dr. Kay Scarpetta, a forensic pathologist who uses forensic t
Carolyn Jeanne Bessette-Kennedy was an American fashion publicist. Raised in Greenwich, Connecticut, she graduated from Boston University and joined Calvin Klein, where she rose from a sales position in Boston to publicity and show-production roles in New York
Benjamin Netanyahu, nicknamed "Bibi", is an Israeli politician and diplomat who has served as Prime Minister of Israel since 2022. Having previously held office from 1996 to 1999 and from 2009 to 2021, Netanyahu is Israel's longest-serving prime minister.
The World Baseball Classic (WBC), also referred to as The Classic, is a quadrennial international baseball tournament sanctioned by the World Baseball Softball Confederation (WBSC), the sport's global governing body, and organized by World Baseball Classic Inc
Iran, officially the Islamic Republic of Iran, and historically known as Persia, is a country in West Asia. It borders Iraq to the west, Turkey, Azerbaijan, and Armenia to the northwest, the Caspian Sea to the north, Turkmenistan to the northeast, Afghanistan
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
Anna's Archive is an open source search engine for shadow libraries that was launched by the pseudonymous Anna shortly after law enforcement efforts to shut down Z-Library in 2022. The site aggregates records from Z-Library, Sci-Hub, and Library Genesis (LibGe
John Fitzgerald Kennedy Jr., also referred to as JFK Jr., was an American businessman, attorney, magazine publisher, and journalist. He was the son of the 35th U.S. president John F. Kennedy, and First Lady Jacqueline Kennedy.
Igor Tudor is a Croatian professional football manager and former player who was most recently the head coach of Premier League club Tottenham Hotspur.
Enhypen is a South Korean boy band formed by Belift Lab. Formerly a joint venture between CJ ENM and Hybe Corporation, the group was formed through the 2020 survival competition show I-Land. The group consists of six members: Jay, Jake, Sunghoon, Sunoo, Jungwo
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.
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
Makalidurga is a hill fort situated near the village of the same name. It is 60 km north of Bangalore and 10 km after Doddaballapura on the way to Gauribidanur. The fort at the summit has an old temple of Shiva with Nandi and in legend Markandeya Rishi perform
Wilt Chamberlain's 100-point game
Wilt Chamberlain set the single-game scoring record in the National Basketball Association (NBA) by scoring 100 points for the Philadelphia Warriors in a 169–147 win over the New York Knicks on March 2, 1962, at Hershey Sports Arena in Hershey, Pennsylvania, U
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Beyond Binomial and Negative Binomial: Adaptation in Bernoulli Parameter Estimation
Estimating the parameter of a Bernoulli process arises in many applications, including photon-efficient active imaging where each illumination period is regarded as a single Bernoulli trial. Motivated by acquisition efficiency when multiple Bernoulli processes are of interest, we formulate the allocation of trials under a constraint on the mean as an optimal resource allocation problem. An oracle-aided trial allocati
Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
The treatment of age-related macular degeneration (AMD) requires continuous eye exams using optical coherence tomography (OCT). The need for treatment is determined by the presence or change of disease-specific OCT-based biomarkers. Therefore, the monitoring frequency has a significant influence on the success of AMD therapy. However, the monitoring frequency of current treatment schemes is not individually adapted t
Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder
Passive non-line-of-sight imaging methods are often faster and stealthier than their active counterparts, requiring less complex and costly equipment. However, many of these methods exploit motion of an occluder or the hidden scene, or require knowledge or calibration of complicated occluders. The edge of a wall is a known and ubiquitous occluding structure that may be used as an aperture to image the region hidden b
Near optimal sample complexity for matrix and tensor normal models via geodesic convexity
The matrix normal model, i.e., the family of Gaussian matrix-variate distributions whose covariance matrices are the Kronecker product of two lower dimensional factors, is frequently used to model matrix-variate data. The tensor normal model generalizes this family to Kronecker products of three or more factors. We study the estimation of the Kronecker factors of the covariance matrix in the matrix and tensor normal
BEFANA: A Tool for Biodiversity-Ecosystem Functioning Assessment by Network Analysis
BEFANA is a free and open-source software tool for ecological network analysis and visualisation. It is adapted to ecologists' needs and allows them to study the topology and dynamics of ecological networks as well as apply selected machine learning algorithms. BEFANA is implemented in Python, and structured as an ordered collection of interactive computational notebooks. It relies on widely used open-source libr
Non-Line-of-Sight Tracking and Mapping with an Active Corner Camera
The ability to form non-line-of-sight (NLOS) images of changing scenes could be transformative in a variety of fields, including search and rescue, autonomous vehicle navigation, and reconnaissance. Most existing active NLOS methods illuminate the hidden scene using a pulsed laser directed at a relay surface and collect time-resolved measurements of returning light. The prevailing approaches include raster scanning o
In Pursuit of Many: A Review of Modern Multiple Object Tracking Systems
Multiple Object Tracking (MOT) is a core capability in modern computer vision, essential to autonomous driving, surveillance, sports analytics, robotics, and biomedical imaging. Persistent identity assignment across frames remains challenging in real scenes because of occlusion, dense crowds, appearance ambiguity, scale variation, camera motion, and identity switching. In this survey we synthesize recent progress by
Efficient Bayesian Updates for Deep Active Learning via Laplace Approximations
Deep active learning (AL) selects batches of instances for annotation to avoid retraining deep neural networks (DNNs) after each new label. Employing a naive top-$b$ selection can result in a batch of redundant (similar) instances. To address this, various AL strategies employ clustering techniques that ensure diversity within a batch. We approach this issue by substituting the costly retraining with an efficient Bay
Explainability of Text Processing and Retrieval Methods: A Survey
Deep Learning and Machine Learning based models have become extremely popular in text processing and information retrieval. However, the non-linear structures present inside the networks make these models largely inscrutable. A significant body of research has focused on increasing the transparency of these models. This article provides a broad overview of research on the explainability and interpretability of natura
Improving Fairness with Ensemble Combination: Margin-Dependent Bounds
The concern about hidden discrimination in machine learning models is growing, as their widespread real-world applications increasingly impact human lives. Various techniques, including commonly used group fairness measures and several fairness-aware ensemble-based methods, have been developed to enhance fairness. However, existing fairness measures typically focus on only one aspect -- either group or individual fai
An Updated Assessment of Reinforcement Learning for Macro Placement
We provide an improved assessment of Google Brain's deep reinforcement learning approach to macro placement and its updated Circuit Training (CT) implementation in GitHub. A stronger simulated annealing (SA) baseline leverages the "go-with-the-winners" metaheuristic and a multi-threading implementation. We develop and release new public benchmarks in sub-10nm technology: LEF/DEF for Google's 7nm TSMC
Disjunctive Branch-and-Bound for Certifiably Optimal Low-Rank Matrix Completion
Low-rank matrix completion consists of computing a matrix of minimal complexity that recovers a given set of observations as accurately as possible. Unfortunately, existing methods for matrix completion are heuristics that, while highly scalable and often identifying high-quality solutions, do not provide an instance-wise certificate of optimality. We reexamine matrix completion with an optimality-oriented eye. We re
Mindstorms in Natural Language-Based Societies of Mind
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each other in a "mindstorm." Recent implementations of NN-based societies of minds consist of large language models (LLMs) and other NN-based experts communicating through a natural language interface. In doing so,
An Overview about Emerging Technologies of Autonomous Driving
Since DARPA started Grand Challenges in 2004 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications. This paper gives an overview about technical aspects of autonomous driving technologies and open problems. We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc.
Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurements
Passive hyperspectral longwave infrared measurements are remarkably informative about the surroundings. Remote object material and temperature determine the spectrum of thermal radiance, and range, air temperature, and gas concentrations determine how this spectrum is modified by propagation to the sensor. We introduce a passive range imaging method based on computationally separating these phenomena. Previous method
Riemannian Laplace Approximation with the Fisher Metric
Laplace's method approximates a target density with a Gaussian distribution at its mode. It is computationally efficient and asymptotically exact for Bayesian inference due to the Bernstein-von Mises theorem, but for complex targets and finite-data posteriors it is often too crude an approximation. A recent generalization of the Laplace Approximation transforms the Gaussian approximation according to a chosen Rie
Large Language Models for Travel Behavior Prediction
Travel behavior prediction is a core problem in transportation demand management and is traditionally addressed using numerical models calibrated on observed data. With recent advances in large language models (LLMs), new opportunities have emerged to model human decision-making through natural language reasoning. This study explores the use of LLMs for travel behavior prediction through two complementary frameworks.
Optimal Transport Aggregation for Distributed Mixture-of-Experts
Mixture-of-experts (MoE) models provide a flexible statistical framework for modeling heterogeneity and nonlinear relationships. In many modern applications, however, datasets are naturally distributed across multiple machines due to storage, computational, or governance constraints. We consider a distributed model aggregation setting in which local MoE models are trained independently on decentralized datasets and s
Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
Multimodal federated learning (MFL) aims to enrich model training in FL settings where clients are collecting measurements across multiple modalities. However, key challenges to MFL remain unaddressed, particularly in heterogeneous network settings where: (i) the set of modalities collected by each client is diverse, and (ii) communication limitations prevent clients from uploading all their locally trained modality
Personalizing explanations of AI-driven hints to users' characteristics: an empirical evaluation
The paper extends an existing Intelligent Tutoring System (ITS) that supports students' learning via AI-driven personalized hints and can generate explanations to justify why/how the hints were generated. In this work, we investigate personalizing these hint explanations to students with low levels of two traits, Need for Cognition and Conscientiousness in order to enhance their engagement with the explanations,
Structured pruning for large language models (LLMs) has garnered significant academic interest due to its ability to efficiently compress and accelerate LLMs by eliminating redundant weight groups at a coarse-grained granularity. Current structured pruning methods for LLMs typically depend on a singular granularity for assessing weight importance, resulting in notable performance degradation in downstream tasks. Intr
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification
Deep active learning (AL) seeks to minimize the annotation costs for training deep neural networks. BAIT, a recently proposed AL strategy based on the Fisher Information, has demonstrated impressive performance across various datasets. However, BAIT's high computational and memory requirements hinder its applicability on large-scale classification tasks, resulting in current research neglecting BAIT in their eval
Modelling Language using Large Language Models
This paper argues that large language models have a valuable scientific role to play in serving as scientific models of public languages. Linguistic study should not only be concerned with the cognitive processes behind linguistic competence, but also with language understood as an external, social entity. Once this is recognized, the value of large language models as scientific models becomes clear. This paper defen
In this study, explainable machine learning techniques are applied to predict the toxicity of mussels in the Gulf of Trieste (Adriatic Sea) caused by harmful algal blooms. By analysing a newly created 28-year dataset containing records of toxic phytoplankton in mussel farming areas and toxin concentrations in mussels (Mytilus galloprovincialis), we train and evaluate the performance of ML models to accurately predict
Exploratory Optimal Stopping: A Singular Control Formulation
This paper explores continuous-time and state-space optimal stopping problems from a reinforcement learning perspective. We begin by formulating the stopping problem using randomized stopping times, where the decision maker's control is represented by the probability of stopping within a given time-specifically, a bounded, non-decreasing, càdlàg control process. To encourage exploration and facilitate learning, w
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