Record 25092026 · captured 2026-09-26
The world looked up Lizzie Borden. 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.
Lizzie Andrew Borden was an American woman who was tried and acquitted of the murders of her father and stepmother in Fall River, Massachusetts. No other individuals were charged with the murders.
The Paradise (2026 Indian film)
The Paradise is a 2026 Indian Telugu-language period action drama film directed by Srikanth Odela and produced by Sudhakar Cherukuri and Ishan Saksena, under Sri Lakshmi Venkateshwara Cinemas and IVY Entertainment, respectively. The film stars Nani, Mohan Babu
Elizabeth Anne Holmes is an American businesswoman convicted of fraud in connection with her health technology company Theranos. Holmes founded Theranos in 2003, and its valuation soared in the early 2010s after it claimed to have revolutionized blood testing
The 2026 Asian Games , officially the XX Asian Games (第二十回アジア競技大会) and also known as Aichi–Nagoya 2026 (愛知・名古屋2026), is an ongoing multi-sport event being held in Aichi Prefecture in Japan from 19 September to 4 October 2026 though several competitions started
The 2026 Asian Games, officially known as the XX Asian Games or Aichi–Nagoya 2026, is the largest sporting event in Asia governed by Olympic Council of Asia (OCA). They are currently held from 19 September to 4 October 2026 in Aichi Prefecture and Nagoya, Japa
India is participating in the 2026 Asian Games in Aichi Prefecture, Japan from 19 September to 4 October 2026. This is the country's 20th consecutive appearance in the competition, having made its debut at the inaugural 1951 Asian Games. The Indian contingent
Aileen Carol Wuornos was an American serial killer. Between 1989 and 1990, while engaging in street prostitution along highways in Florida, Wuornos shot, killed, and robbed seven of her male clients. She initially claimed that her victims had either raped or a
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
Monster: The Lizzie Borden Story
Monster: The Lizzie Borden Story is the fourth season of the American biographical crime drama anthology television series Monster, created by Ian Brennan for Netflix. The season centers on murder suspect Lizzie Borden who was tried and acquitted of the 1892 a
Resident Evil is a 2026 horror film directed by Zach Cregger and written by Cregger and Shay Hatten, based on the Resident Evil video game franchise by Capcom. It is the eighth live-action film of the Resident Evil film series, and serves as a reboot. The film
Thomas Jonathan Bateman is a British actor best known for his roles as Giuliano de' Medici in the Starz historical fantasy drama series Da Vinci's Demons (2013–2015), as Bouc in the mystery films Murder on the Orient Express (2017) and Death on the Nile (2022)
You Can See Everything is a 2026 American documentary film directed by Nathan Fielder and Lance Oppenheim. It follows Elizabeth Holmes, the founder of the defunct health technology company Theranos, and her partner Billy Evans, who invite a film crew to docume
Mushtaq Khan was an Indian film and television actor and comedian who worked in several Hindi films in a career spanning three decades. He was best known for his roles in films such as Hum Hain Rahi Pyar Ke (1993), Jodi No.1 (2001) and Welcome (2007).
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
The Love Hypothesis is a 2026 American romantic comedy film adapted from the novel of the same name by Ali Hazelwood. Directed by Claire Scanlon from a script by Sarah Rothschild, the film stars Tom Bateman and Lili Reinhart and was released on Prime Video on
Ella Beatty is an American actress and the daughter of Annette Bening and Warren Beatty.
Woodrow Tracy Harrelson is an American actor. He first became known for his role as charmingly naive bartender Woody Boyd on the NBC sitcom Cheers (1985–1993), for which he won a Primetime Emmy Award for Outstanding Supporting Actor in a Comedy Series from fiv
Ansel Easton Adams was an American landscape photographer and environmentalist known for his black-and-white images of the American West. He helped found Group f/64, an association of photographers advocating "pure" photography which favored sharp focus and th
Christa Gail Pike is an American convicted murderer who is incarcerated on death row in Tennessee. In 1995, at the age of 18, Pike murdered her 19-year-old Job Corps classmate Colleen Slemmer in Knoxville. Pike and two friends lured Slemmer into the woods, whe
The Bharatiya Sakshya Adhiniyam (BSA), 2023 is an act of the Parliament of India.
The Bharatiya Nyaya Sanhita (BNS), 2023 is the official criminal code of India. It came into effect on 01-July-2024, after being passed by the Parliament in December-2023, replacing the colonial-era Indian Penal Code of 1860 (IPC).
Chad Everett Gilbert was an American guitarist, record producer and songwriter. He was a founding member of the punk rock band New Found Glory, for whom he played lead guitar and sang backing vocals. He was also the lead vocalist for the band's now-defunct sid
Xi Jinping is a Chinese politician who is the paramount leader of China. He has served as the general secretary of the Chinese Communist Party (CCP) and chairman of the Party Central Military Commission (CMC) since 2012, and as the president of China and chair
Gyanesh Kumar is the current chief election commissioner of India, and the first to be appointed under the Chief Election Commissioner and Other Election Commissioners Act, 2023. He has previously served as an election commissioner and as an IAS officer.
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").
The Love Hypothesis is a romance novel by Ali Hazelwood, published September 14, 2021 by Berkley Books. Originally published online in 2018 as Head Over Feet, a Star Wars fan fiction work about the "Reylo" ship between Rey and Kylo Ren, the novel follows a Ph.
Matthew David McConaughey is an American actor. He achieved his breakthrough with a supporting performance in the coming-of-age comedy Dazed and Confused (1993). After a number of supporting roles, his first success as a leading man came in the legal drama A T
Brothers is an American comedy television series created by Matthew McConaughey & Woody Harrelson, Lee Eisenberg, and David West Read. The series premiered on September 23, 2026.
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
Theranos Inc. was an American privately held corporation that was touted as a breakthrough health technology company. Founded in 2003 by then 19-year-old Elizabeth Holmes, Theranos raised more than US$700 million from venture capitalists and private investors,
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
CatSIM: A Categorical Image Similarity Metric
We introduce CatSIM, a new similarity metric for binary and multinary two- and three-dimensional images and volumes. CatSIM uses a structural similarity image quality paradigm and is robust to small perturbations in location so that structures in similar, but not entirely overlapping, image or volumetric regions are rated higher than by simple matching. The metric can also compare arbitrary regions inside images and
A significant challenge to training accurate deep learning models on privacy policies is the cost and difficulty of obtaining a large and comprehensive set of training data. To address these challenges, we present Calpric, which combines automatic text selection and segmentation, active learning and the use of crowdsourced annotators to generate a large, balanced training set for privacy policies at low cost. Automat
A Streaming End-to-End Framework For Spoken Language Understanding
End-to-end spoken language understanding (SLU) has recently attracted increasing interest. Compared to the conventional tandem-based approach that combines speech recognition and language understanding as separate modules, the new approach extracts users' intentions directly from the speech signals, resulting in joint optimization and low latency. Such an approach, however, is typically designed to process one in
Conceptual Model Interpreter for Large Language Models
Large Language Models (LLMs) recently demonstrated capabilities for generating source code in common programming languages. Additionally, commercial products such as ChatGPT 4 started to provide code interpreters, allowing for the automatic execution of generated code fragments, instant feedback, and the possibility to develop and refine in a conversational fashion. With an exploratory research approach, this paper a
DCRMTA: Deep Causal Representation Learning for Multi-Touch Attribution
Multi-touch attribution (MTA) is essential for estimating the contribution of individual advertising touchpoints to user conversions. While recent studies incorporate causal inference to mitigate confounding bias from user preferences, existing multi-stage deconfounding pipelines exhibit a critical structural flaw: they indiscriminately filter out user influences, which inadvertently discards the genuine causal signa
Reconstructing short-lived particles using hypergraph representation learning
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many final-state jets, such as the all-hadronic decay of top-antitop quark pairs, is challenging. We present HyPER: Hypergraph for Particle Event Reconstruction, a novel architecture b
ELiSe: Efficient Learning of Sequences in Structured Recurrent Networks
Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks, memories of past activities need to persist on significantly longer timescales than the relaxation times of single-neuron activity. While recurrent networks can produce such long transients, training these networks is a challenge. Learning via error propagation confers models
A Probabilistic Approach for Model Alignment with Human Comparisons
A growing trend involves integrating human knowledge into learning frameworks, leveraging subtle human feedback to refine AI models. While these approaches have shown promising results in practice, the theoretical understanding of when and why such approaches are effective remains limited. This work takes steps toward developing a theoretical framework for analyzing the conditions under which human comparisons can en
Band-Attention Modulation Network for Robust Face Forgery Detection
Face forgery detection faces critical challenges in generalizing to unseen manipulation techniques and remaining robust under image compression, which often obscures subtle artifacts. Existing methods typically rely on fixed filters or coarse band separation, lacking the adaptability to learn task-specific spectral cues. To address this, we propose the Band-Attention Modulation Network (BAM-Net), a novel framework th
A Unified Theory of Exact Inference and Learning in Exponential Family Latent Variable Models
Bayes' rule describes how to infer posterior beliefs about latent variables given observations, and inference is a critical step in learning algorithms for latent variable models (LVMs). Although there are exact algorithms for inference and learning for certain LVMs such as linear Gaussian models and mixture models, researchers must typically develop approximate inference and learning algorithms when applying nov
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) has exploded in popularity in recent years. While numerous approaches have been developed, they can be broadly categorized into three main types: centralized training and execution (CTE), centralized training for decentralized execution (CTDE), and decentralized training and execution (DTE). CTE methods assume centralization during training and execution (e.g., with fast, fre
The rapid growth of scientific literature makes it increasingly challenging for researchers to identify novel and impactful ideas, especially across disciplines. Modern artificial intelligence (AI) systems offer new opportunities for scientific ideation, but how compelling are AI-generated ideas, and how can their quality be improved? Here, we introduce SciMuse, which generates personalized research ideas using a kno
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
Semi-supervised anomaly detection, which aims to improve the anomaly detection performance by using a small amount of labeled anomaly data in addition to unlabeled data, has attracted attention. Existing semi-supervised approaches assume that most unlabeled data are normal, and train anomaly detectors by minimizing the anomaly scores for the unlabeled data while maximizing those for the labeled anomaly data. However,
Transductive Off-policy Proximal Policy Optimization
Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due to its inherent on-policy nature, its proficiency in harnessing data from disparate policies is constrained. This paper introduces a novel off-policy extension to the original PPO method, christened Transductive Off-policy PPO (ToPPO). Herein, we provide theoretical justi
AIR: Analytic Imbalance Rectifier for Continual Learning
Continual learning (CL) agents incrementally learn from sequentially arriving data and adapt to the dynamic, ever-changing nature of real-world environments. However, many existing CL methods suffer performance degradation in evolving, imbalanced data streams due to limited adaptation to changing class frequencies or ineffective use of mixed data from new and previously observed classes. To deal with these challenges
Evaluation of OpenAI o1: Opportunities and Challenges of AGI
This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, including computer science, mathematics, natural sciences, medicine, linguistics, and social sciences. Through rigorous testing, o1-preview demonstrated remarkable capabilities, often achieving human-level or superior performance in areas rang
MultiViewDx: Evidence-Linked Multi-View Clinical Diagnosis
Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their training data often does not match clinical diagnosis. Most supervision is organized around isolated images or short QA pairs, leaving two structures weakly specified: how evidence leads to a decision, and how views, series, modalities, and patient context from the same case a
This study conducted a comprehensive performance evaluation on YOLO11 (or YOLOv11) and YOLOv8, the latest in the "You Only Look Once" (YOLO) series, focusing on their instance segmentation capabilities for immature green apples in orchard environments. YOLO11n-seg achieved the highest mask precision across all categories with a notable score of 0.831, highlighting its effectiveness in fruit detection. YOLO11m
AI companions increasingly sustain long-term, emotionally engaging relationships but can also make discriminatory remarks or exert control, leaving users to manage harmful conflicts. We analyze 146 posts describing harmful value conflicts with AI companions, then use Minion, a technology probe offering response suggestions ranging from persuasion to boundary setting, to study how 22 users negotiate scenario-based con
Foundations of Large Language Models
This is a book about large language models. As indicated by the title, it primarily focuses on foundational concepts rather than comprehensive coverage of all cutting-edge technologies. The book is structured into six main chapters, each exploring a key area: pre-training, generative models, prompting, alignment, inference, and reasoning. It is intended for college students, professionals, and practitioners in natura
Bias-variance decompositions: the exclusive privilege of Bregman divergences
Bias-variance decompositions are widely used to understand the generalization performance of machine learning models. While the squared error loss permits a straightforward decomposition, other loss functions - such as zero-one loss or $L_1$ loss - either fail to sum bias and variance to the expected loss or rely on definitions that lack the essential properties of meaningful bias and variance. Recent research has sh
Time-Varying Bayesian Optimization Without a Metronome
Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying, expensive, noisy black-box function $f$. However, most of the asymptotic guarantees offered by TVBO algorithms rely on the assumption that observations are acquired at a constant frequency. As the GP inference complexity scales with the cube of its dataset size, this assumption is unrealistic in the long run. In this paper
The Majority Vote Paradigm Shift: When Popular Meets Optimal
Reliably labelling data typically requires annotations from multiple human workers. However, humans are far from being perfect. Hence, it is a common practice to aggregate labels gathered from multiple annotators to make a more confident estimate of the true label. Among many aggregation methods, the simple and well known Majority Vote (MV) selects the class label polling the highest number of votes. However, despite
Ensuring safety in autonomous driving systems remains a critical challenge, particularly in handling rare but potentially catastrophic safety-critical scenarios. While existing research has explored generating safety-critical scenarios for autonomous vehicle (AV) testing, there is limited work on effectively incorporating these scenarios into policy learning to enhance safety. Furthermore, developing training curricu
Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
Predicting clinical outcomes from preclinical data is essential for selecting safe and effective drug combinations and for reducing late-stage failures. AI models use molecular structure and target annotations, and do not leverage the perturbation readouts that report how a compound acts in a cellular context. Here we introduce Madrigal, a multimodal AI model that learns from structural, pathway, cell-viability, and
Origins publishing files written for machines rather than people. Measured against a frozen cohort, so a change in the number means a change in adoption.
| Signal | Web head Tranco top 1,000 n=1,000 | Web tail sampled to rank 100k n=1,000 | AI-native model & dev platforms n=110 |
|---|---|---|---|
| Any agent-facing signal | 12% (120) | 4.4% (44) | 74.55% (82) |
| llms.txt (apex domain) | 9.7% (97) | 3.6% (36) | 60% (66) |
| llms.txt (docs subdomain) | 4% (40) | 1% (10) | 46.36% (51) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 8.18% (9) |
| .well-known/agents.txt | 0.3% (3) | 0.2% (2) | 0% (0) |
| ai.txt | 0.2% (2) | 0.1% (1) | 0% (0) |
| ai-plugin.json (deprecated) | 0.6% (6) | 0.1% (1) | 0.91% (1) |
Notable events recorded on this day and month across all years.