Record 08042026 · captured 2026-08-25
The world looked up Artemis II. 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.
Artemis II was a crewed flyby of the Moon. It is currently the only crewed flight beyond low Earth orbit since Apollo 17 in 1972. It was the first crewed flight of the NASA-led Artemis program, the first crewed flight of the Space Launch System (SLS), and the
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
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
Dusty Allan May is an American professional basketball coach who is the head coach of the Dallas Mavericks of the National Basketball Association (NBA). He was previously the head coach for Florida Atlantic University from 2018 to 2024 and the University of Mi
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
Benjamin Roberts-Smith is an Australian former soldier in the Special Air Service Regiment (SASR). He is one of Australia's most highly decorated soldiers, having received the Medal for Gallantry (2006), the Victoria Cross for Australia (2011)—the highest awar
Gregory Reid Wiseman is a United States Navy captain, test pilot, and NASA astronaut. He was the commander of the 2026 Artemis II lunar flyby mission, the first crewed flight around the Moon since Apollo 17 in 1972. He served as the 17th chief of the Astronaut
Yaxel Okari Lendeborg is an American-Dominican basketball player for the Golden State Warriors of the National Basketball Association (NBA). He was drafted 11th overall in the 2026 NBA draft by the Warriors. Lendeborg played college basketball for the Arizona
The Drama is a 2026 American dark romantic comedy film written and directed by Kristoffer Borgli. It stars Zendaya and Robert Pattinson as a happily engaged couple whose relationship is tested by an unexpected revelation the week before their wedding.
WrestleMania 42, also promoted as WrestleMania Vegas, was a 2026 professional wrestling pay-per-view (PPV) and livestreaming event produced by WWE. It was the 42nd annual WrestleMania and took place as a two-night event on Saturday, April 18 and Sunday, April
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
Elliot Valentin Cadeau is an American-Swedish college basketball player for the Michigan Wolverines of the Big Ten Conference. He was an NCAA national champion and the Final Four Most Outstanding Player in 2026. Cadeau previously played for the North Carolina
Christina Hammock Koch is an American engineer and NASA astronaut. On her mission to the International Space Station in 2019–20 she was part of the first all‑female spacewalk and set the record for the longest spaceflight by a woman. On the Artemis II lunar fl
Daniel S. Hurley is an American men's college basketball coach who is the head coach of the UConn Huskies. In 2023 and 2024, Hurley led UConn to back-to-back NCAA Division I national championships, and led the Huskies to another title game appearance in 2026.
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
Kiari Kendrell Cephus, known professionally as Offset, is an American rapper and songwriter. He is best known for being a member of suburban metro Atlanta-based hip-hop trio Migos. Formed with fellow rappers Quavo and Takeoff in 2008, the group released four c
Sawyer Storm Sweeten was an American child actor. He was best known for his role as Geoffrey Barone on the sitcom Everybody Loves Raymond.
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.
17776 is a serialized speculative fiction multimedia hypertext narrative by Jon Bois, published online through SB Nation. Set in the distant future in which all humans have become immortal and infertile, the series follows three sapient space probes that watch
The Brazilian Grand Prix, currently held under the name São Paulo Grand Prix, is a Formula One championship race which is currently held at the Autódromo José Carlos Pace in Interlagos neighborhood, Cidade Dutra, São Paulo. The inaugural Brazilian Grand Prix,
2018 Tennessee Volunteers baseball team
The 2018 Tennessee Volunteers baseball team represented the University of Tennessee in the 2018 NCAA Division I baseball season. The Volunteers played their home games at Lindsey Nelson Stadium. The team was coached by Tony Vitello in his first season as head
South Middleborough Historic District
The South Middleborough Historic District encompasses the historic village center of South Middleborough, Massachusetts. The village is located about 6.5 miles (10.5 km) south of the town center, at the junction of Wareham and Locust Streets. Wareham Street, w
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
Mircea Lucescu was a Romanian professional football player and manager.
Ye is an American rapper, songwriter, and record producer. He has been listed among the greatest rappers of all time and referred to as one of the most prominent figures in hip-hop. His music, characterized by frequent stylistic shifts, has been credited with
The Super Mario Galaxy Movie is a 2026 American animated adventure comedy film based on Nintendo's Mario video game franchise. Directed by Aaron Horvath and Michael Jelenic and written by Matthew Fogel, it is the sequel to The Super Mario Bros. Movie (2023). C
Twenty-fifth Amendment to the United States Constitution
The Twenty-fifth Amendment to the United States Constitution addresses issues related to presidential succession and disability.
Michigan Wolverines men's basketball
The Michigan Wolverines men's basketball team is the intercollegiate men's basketball program representing the University of Michigan. The school competes in the Big Ten Conference in Division I of the National Collegiate Athletic Association (NCAA), and play
Michael Malone is an American basketball coach who is the head coach of the North Carolina Tar Heels men's basketball team. He previously coached in the National Basketball Association (NBA), where he was the head coach of the Sacramento Kings from 2013 to 201
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Image Captioning via Compact Bidirectional Architecture
Most current image captioning models typically generate captions from left-to-right. This unidirectional property makes them can only leverage past context but not future context. Though refinement-based models can exploit both past and future context by generating a new caption in the second stage based on pre-retrieved or pre-generated captions in the first stage, the decoder of these models generally consists of t
Reachability In Simple Neural Networks
We investigate the complexity of the reachability problem for (deep) neural networks: does it compute valid output given some valid input? It was recently claimed that the problem is NP-complete for general neural networks and specifications over the input/output dimension given by conjunctions of linear inequalities. We recapitulate the proof and repair some flaws in the original upper and lower bound proofs. Motiva
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition
In privacy-preserving data analysis, many procedures and algorithms are structured as compositions of multiple private building blocks. As such, an important question is how to efficiently compute the overall privacy loss under composition. This paper introduces the Edgeworth Accountant, an analytical approach to composing differential privacy guarantees for private algorithms. Leveraging the $f$-differential privacy
Solving Quantified Modal Logic Problems by Translation to Classical Logics
This article describes an evaluation of Automated Theorem Proving (ATP) systems on problems taken from the QMLTP library of first-order modal logic problems. Principally, the problems are translated to both typed first-order and higher-order logic in the TPTP language using an embedding approach, and solved using first-order resp. higher-order logic ATP systems and model finders. Additionally, the results from native
In this paper, we provide a strategy to determine the eigenvalue decay rate (EDR) of a large class of kernel functions defined on a general domain rather than $\mathbb S^{d}$. This class of kernel functions include but are not limited to the neural tangent kernel associated with neural networks with different depths and various activation functions. After proving that the dynamics of training the wide neural networks
Variational Sequential Optimal Experimental Design using Reinforcement Learning
We present variational sequential optimal experimental design (vsOED), a novel method for optimally designing a finite sequence of experiments within a Bayesian framework with information-theoretic criteria. vsOED employs a one-point reward formulation with variational posterior approximations, providing a provable lower bound to the expected information gain. Numerical methods are developed following an actor-critic
Understanding Uncertainty Sampling via Equivalent Loss
Uncertainty sampling is a prevalent active learning algorithm that queries sequentially the annotations of data samples which the current prediction model is uncertain about. However, the usage of uncertainty sampling has been largely heuristic: There is no consensus on the proper definition of ``uncertainty'' for a specific task under a specific loss, nor a theoretical guarantee that prescribes a standard pr
In the paper we argue that performance of the classifiers based on Empirical Risk Minimization (ERM) for positive unlabeled data, which are designed for case-control sampling scheme may significantly deteriorate when applied to a single-sample scenario. We reveal why their behavior depends, in all but very specific cases, on the scenario. Also, we introduce a single-sample case analogue of the popular non-negative ri
An Encoding of Abstract Dialectical Frameworks into Higher-Order Logic
An approach for encoding abstract dialectical frameworks and their semantics into classical higher-order logic is presented. Important properties and semantic relationships are formally encoded and proven using the proof assistant Isabelle/HOL. This approach allows for the computer-assisted analysis of abstract dialectical frameworks using automated and interactive reasoning tools within a uniform logic environment.
CodeMind: Evaluating Large Language Models for Code Reasoning
Large Language Models (LLMs) have been widely used to automate programming tasks. Their capabilities have been evaluated by assessing the quality of generated code through tests or proofs. The extent to which they can reason about code is a critical question revealing important insights about their true capabilities. This paper introduces CodeMind, a framework designed to gauge the code reasoning abilities of LLMs th
Motivated by the problem of matching two correlated random geometric graphs, we study the problem of matching two Gaussian geometric models correlated through a latent node permutation. Specifically, given an unknown permutation $π^*$ on $\{1,\ldots,n\}$ and given $n$ i.i.d. pairs of correlated Gaussian vectors $\{X_{π^*(i)},Y_i\}$ in $\mathbb{R}^d$ with noise parameter $σ$, we consider two types of (correlated) weig
Towards Better Statistical Understanding of Watermarking LLMs
In this paper, we study the problem of watermarking large language models (LLMs). We consider the trade-off between model distortion and detection ability and formulate it as a constrained optimization problem based on the red-green list watermarking algorithm. We show that the optimal solution to the optimization problem enjoys a nice analytical property which provides a better understanding and inspires the algorit
Optimal experimental design (OED) provides a systematic approach to quantify and maximize the value of experimental data. Under a Bayesian approach, conventional OED maximizes the expected information gain (EIG) on model parameters. However, we are often interested in not the parameters themselves, but predictive quantities of interest (QoIs) that depend on the parameters in a nonlinear manner. We present a computati
Controllable Image Generation with Composed Parallel Token Prediction
Conditional discrete generative models struggle to faithfully compose multiple input conditions. To address this, we derive a theoretically-grounded formulation for composing discrete probabilistic generative processes, with masked generation (absorbing diffusion) as a special case. Our formulation enables precise specification of novel combinations and numbers of input conditions that lie outside the training data,
Interdicting a criminal with limited police resources is a challenging task as the criminal changes location over time. The size of the large transportation network further adds to the difficulty of this scenario. To tackle this issue, we consider the concept of a layered graph. At each time stamp, we create a copy of the entire transportation network to track the possible movements of both players, the attacker and
Vision-Language Models (VLMs) rely heavily on pretrained vision encoders to support downstream tasks such as image captioning, visual question answering, and zero-shot classification. Despite their strong performance, these encoders remain highly vulnerable to imperceptible adversarial perturbations, which can severely degrade both robustness and semantic quality in multimodal reasoning. In this work, we introduce Si
Deepfakes represent a growing concern across domains such as disinformation, fraud, and non-consensual media. In particular, the rise of video conference and identity-driven attacks in high-stakes scenarios--such as impostor hiring--demands new forensic resources. Despite significant efforts to develop robust detection classifiers to distinguish the real from the fake, commonly used training datasets remain inadequat
Attentive Dilated Convolution for Automatic Sleep Staging using Force-directed Layout
Sleep stages play an important role in identifying sleep patterns and diagnosing sleep disorders. In this study, we present an automated sleep stage classifier called the Attentive Dilated Convolutional Neural Network (AttDiCNN), which uses deep learning methodologies to address challenges related to data heterogeneity, computational complexity, and reliable and automatic sleep staging. We employed a force-directed l
Recent Advances in Multimodal Affective Computing: An NLP Perspective
Multimodal affective computing has gained increasing attention due to its broad applications in understanding human behavior and intentions, particularly in text-centric multimodal scenarios. Existing research spans diverse tasks, modalities, and modeling paradigms, yet lacks a unified perspective. In this survey, we systematically review recent advances from an NLP perspective, focusing on four representative tasks:
TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignment
Code translation transforms code between programming languages while preserving functionality, which is critical in software development and maintenance. While traditional learning-based code translation methods have limited effectiveness due to the lack of sufficient parallel training data, Large Language Models (LLMs) have recently advanced this field with their strong code generation and comprehension capabilities
ForgeryGPT: A Multimodal LLM for Interpretable Image Forgery Detection and Localization
Multimodal Large Language Models (MLLMs), such as GPT4o, have shown strong capabilities in visual reasoning and explanation generation. However, despite these strengths, they face significant challenges in the increasingly critical task of Image Forgery Detection and Localization (IFDL). Moreover, existing IFDL methods are typically limited to the learning of low-level semantic-agnostic clues and merely provide a sin
Interpreting Temporal Graph Neural Networks with Koopman Theory
Spatiotemporal graph neural networks (STGNNs) have shown promising results in many domains, from forecasting to epidemiology. However, understanding the dynamics learned by these models and explaining their behaviour is significantly more difficult than for models that deal with static data. Inspired by Koopman theory, which allows a simple description of intricate, nonlinear dynamical systems, we introduce new expla
Cobblestone: A Divide-and-Conquer Approach for Automating Formal Verification
Formal verification using proof assistants, such as Coq, is an effective way of improving software quality, but requires significant effort and expertise. Machine learning can automatically synthesize proofs, but such tools are able to prove only a fraction of desired software properties. We introduce Cobblestone, a divide-and-conquer approach for proof synthesis. Cobblestone uses a large language model (LLM) to gene
From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap
The rapid expansion of foundation models (FMs), such as large language models (LLMs), has given rise to FMware, software systems that integrate FM(s) as core components. While building demonstration-level FMware is relatively straightforward, transitioning to production-ready systems presents numerous challenges, including reliability, high implementation costs, scalability, and compliance with privacy regulations. O
Why CNN Features Are not Gaussian: A Statistical Anatomy of Deep Representations
Deep convolutional neural networks (CNNs) are commonly analyzed through geometric and linear-algebraic perspectives, yet the statistical distribution of their internal feature activations remains poorly understood. In many applications, deep features are implicitly treated as Gaussian when modeling densities. In this work, we empirically examine this assumption and show that it does not accurately describe the distri
Notable events recorded on this day and month across all years.