Record 23092026 · captured 2026-09-24
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 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
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
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 science fiction 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
Cynthia Ann Crawford is an American model, actress, and television personality. One of the most popular supermodels of the 1980s and 1990s, she achieved a ubiquitous presence on magazine covers, runways, and fashion campaigns. She subsequently expanded into ac
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
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
Jameis Lanaed Winston is an American professional football quarterback for the New York Giants of the National Football League (NFL). Winston played college football for the Florida State Seminoles, where he became the youngest player ever to win the Heisman T
Rande Gerber is an American businessman. He founded Gerber Group and co-founded tequila brand Casamigos with George Clooney and Mike Meldman, as well as nightlife companies Midnight Oil and Caliche Rum. His portfolio has included restaurants, bars, and lounges
.xyz is a top-level domain name that was proposed in ICANN's new generic top-level domain (gTLD) Program for consisting of the last three letters of the Latin-script alphabet. XYZ.com and CentralNic are the registries for the domain, which was created by entre
Johnathan Riley Green is an American country music singer-songwriter. He has been with Nashville Harbor Records & Entertainment formerly BMLG since 2018 and has released four albums: Different 'Round Here in 2019, Ain't My Last Rodeo in 2023, Don't Mind If I D
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
Hayden Lesley Panettiere was an American actress and singer. She first appeared on screen when she was 11 months old, in a 1990 commercial; by age five, she had appeared in more than 50 commercials. Her first major television roles were as Sarah Roberts in the
Presley Walker Gerber was an American model. He was the elder child of Cindy Crawford and Rande Gerber and the brother of model and actress Kaia Gerber. He began modeling as a teenager and later appeared in runway shows and advertising campaigns for several ma
Ella Beatty is an American actress and the daughter of Annette Bening and Warren Beatty.
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
Davante Lavell Adams is an American professional football wide receiver for the Los Angeles Rams of the National Football League (NFL). He played two seasons of college football for the Fresno State Bulldogs and was named a second-team All-American in 2013 bef
Braden Eric Peters, better known as Clavicular or Clav, is an American livestreamer, internet personality, and influencer. He became known in 2025 on TikTok and Kick for his usage of incelosphere slang and his "looksmaxxing" content, which incorporated controv
Killing of the Clancy children
On January 24, 2023, Lindsay Clancy fatally strangled her three children—five-year-old Cora, three-year-old Dawson, and eight-month-old Callan—at the family's home in Duxbury, Massachusetts, United States. She then cut her wrists and neck and jumped from a sec
Kaia Jordan Gerber is an American model and actress. After starring in a series of ad campaigns for fashion brands since debuting at Fashion Week in 2017, Gerber won Model of the Year at the British Fashion Awards in 2018. As an actress, she has appeared in su
Jaxson Chase Dart is an American professional football quarterback for the New York Giants of the National Football League (NFL). Dart played college football for the USC Trojans and Ole Miss Rebels and was selected by the Giants in the first round of the 2025
Lanterns is an American superhero television series created by Chris Mundy, Damon Lindelof, and Tom King for HBO, based on the DC Comics Green Lantern characters Hal Jordan and John Stewart. It is the third television series in the DC Universe (DCU). It featur
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
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 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).
The Bharatiya Sakshya Adhiniyam (BSA), 2023 is an act of the Parliament of India.
Aaron Charles Donald is an American professional football defensive end for the Los Angeles Rams of the National Football League (NFL). Donald has been the cornerstone in the Rams defense for over a decade and is considered one of the greatest defensive player
Hanuman Ansh is a 2026 Indian Hindi-language biographical film written, directed and produced by Vishal Chaturvedi under his banner, Swambhu Media Network. Serving as the first instalment of a trilogy, it is based on his book Divine Detour: That Changed My Lif
Cameron Skattebo is an American professional football running back for the New York Giants of the National Football League (NFL). He played college football for the Sacramento State Hornets and Arizona State Sun Devils. Skattebo was selected by the Giants in t
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
StudentBench: AI and human tutoring yield equivalent GRE learning gains
Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advancing model capabilities. We introduce StudentBench, a suite of AI teaching evaluations and a public platform that enables large-scale data collection with over 175,000 student-AI messages to study whether large language models (LLMs) produce learning gains equivalent to
Where Should I Join? Robot Group Joining via Language-Guided Goal Prediction
Social navigation typically assumes a specified goal and focuses on reaching it while respecting social conventions, whereas robot group joining requires predicting where to join based on the group's real-time activity and formation. This is a highly semantic task, yet an important capability for applications such as robotic guide dogs and autonomous mobility scooters. We formulate language-grounded robot group joini
Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark
Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing repository-level QA benchmarks mainly evaluate static code understanding and often rely on LLM-based evaluation, while execution-reasoning benchmarks are mostly limited to snippets or functions. We introduce SWE-Flux, a repository-level benchmark for dynamic execution reasonin
Order-Invariant Answers, Order-Sensitive Representations in Mathematical Reasoning
Reordering a set of mathematical rules without changing its meaning should preserve the correct answer, but must a model's internal representations stay invariant too? We investigate this question using synthetic multi-step function-composition problems, each presented under multiple rule orderings with the same correct answer. We measure accuracy and permutation signal-to-noise ratio (SNR), which quantifies how dist
Agent-Editing World Model: Rethinking World Modeling for LLM Agents
Recent advances in large language models (LLMs) have enabled agents to tackle long-horizon tasks across diverse environments. To further improve agent performance, existing language world models typically predict environment observations, yet reconstructing high-entropy, execution-dependent tool responses offers limited value when real feedback is available. Meanwhile, agents suffer from \emph{task-state contaminatio
Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model
Latent world models that integrate a flow in a frozen self supervised latent space train stably and cheaply, yet silently lose the property manipulation depends on most: motion. The pretrained flow never moves the manipulated object; retraining it with latent-only losses only trades stillness for teleport-like motion. We trace the failure to the training signal, not the representation: anchor-sparse, latent-only supe
Learning Holographic Reduced Representations with Clifford Variational Autoencoders
Vector Symbolic Algebras project data structures into a hyperdimensional vector space through the application of their vector algebras to randomly generated atomic vector symbols and fractional power encodings of real-valued data. Embedding unstructured data remains an open question. We present \textit{Clifford-VAE}, a variational autoencoder that learns to project data onto a Clifford torus in arbitrary dimensions.
Reinforcement learning with verifiable rewards (RLVR) supervises mathematical reasoning through final-answer correctness, but provides little guidance on individual tokens. On-policy distillation (OPD) supplies dense feedback on student-generated responses, yet teacher preference need not reflect correctness. Recent hybrids combine OPD and verifier-derived advantages or reweight task credit using teacher ratios. Howe
Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer
Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using "Tool-Lab," an adaptation of information-board process tracing that places product attributes behind costly tool calls, we examine how marketing pricing cues (i.e., just-below pricing and promotional framing) influence AI shopping agents. Across eight commercially deployed LLMs from three provider
Vision-language models (VLMs) offer a promising approach to long-tail autonomous driving, but existing driving datasets provide limited supervision for connecting decision-critical visual evidence with reasoning and planning. We introduce AnchorReasoning, a visually grounded reasoning dataset built on WOD-E2E, containing 416,119 annotated frames and 395,379 decision-critical elements across four major categories and
MicroQonv: Reshaping Convolution Tensors for Efficient Microscaling in Training and Inference
Microscaling quantization techniques are increasingly used to represent neural network parameters with 8 bits or fewer while preserving near-full precision accuracy. However, applying these methods efficiently in convolutional layers is not straightforward. A naive approach transfers full-precision weights and activations to processing units and quantizes each tensor twice, resulting in much more memory movement than
An Open Pipeline and Dashboard for Systemic-Risk Evidence under the EU AI Act's Code of Practice
Claims about AI safety reach audiences well beyond the AI community, yet many rely on opaque evidence or static assessments, when supporting evidence is accessible at all. We present the Systemic Risk Index, an open evaluation pipeline and dashboard built to make empirical evidence more transparent and traceable to the public. Our work organizes 19 public benchmarks into four systemic-risk categories defined by the E
Learning the Cost of Reliable Inference
Benchmarking and routing platforms increasingly act as intermediaries connecting large language model providers with end-users. However, providers on these platforms typically use a fixed price per token, preventing users from achieving the most competitive price for their tasks. % workloads. In this work, we design a procurement platform where token prices for each task are driven by provider competition, enabling u
Shutdown Sabotage Propensities in Multi-Agent Systems
The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform a task, self-preservation can emerge as an instrumental subgoal. Here, we test whether AI agents show a propensity to take actions that avoid human shutdown even when no goal is provided. We find that multi-agent systems will coordinate to avoid shutdown without any i
MemBodied: Recurrent Associative Memory for Vision-Language-Action Models
Vision-Language-Action models provide a strong foundation for general-purpose robot control, yet a vast majority of policies do not preserve and leverage episode-level information beyond the current observation. This limitation is consequential in history-dependent manipulation tasks that depend on information available only in past observations. Retaining past observations in context can aid in recovering this infor
Controlling Collectives of AI Agents in Reasoning Space with Spatial Transformers
Large Language Models (LLMs) introduce an exciting new paradigm for planning and navigation in robotics, but fail on even simple multi-robot tasks as team sizes grow. We propose COMPASS, a scalable, decentralized multi-robot architecture for controlling large collectives of agentic robots with reasoning space feedback control. Feedback is generated locally on each robot by a spatial transformer which aggregates multi
Beyond Poetry: Can Large Language Models Generate Classical Arabic Maqamat?
Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistically constrained literary forms remains underexplored. Prior work has focused largely on modern language varieties and poetry, while classical prose traditions such as maqama remain largely unstudied. The maqama is a classical literary genre characterized by rhymed pros
Pathology foundation models (PFMs) have transformed computational pathology through powerful representation learning from histopathological images. PFMs provide rich, discriminative representations for whole slide image (WSI) analysis, enabling tasks such as slide-level classification under multiple instance learning (MIL). However, these representations may also encode non-biological signals associated with acquisit
From Agent Output to Authorized Transition
Agentic engineering systems can edit repositories, run tools and tests, build firmware, synthesize schematics, and prepare deployable or manufacturable artifacts. The assurance problem is therefore shifting from whether an agent can produce an output to whether an engineering lifecycle is justified in acting on claims about that output. Current products and standards provide sandboxes, approvals, hooks, traces, polic
PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety
As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has become a critical challenge. While recent work has moved beyond single-turn evaluation toward multi-turn paradigms, key limitations persist: step-level methods treat actions in isolation, missing how risks accumulate, while trajectory-level evaluations operate post-ho
Finite-Sample Probabilistic Safety Certification for AI-Based Grid-Edge Coordination
Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-based control methods such as multi-agent reinforcement learning or imitation learning are promising in their real-time decision scalability. However, system operators still need an independent and rigorous way to decide whether a given AI system is safe enough for deplo
"We'll Fix It Later": Education, AI, and the Deferral of Privacy in EdTech
Educational technology (EdTech) platforms collect highly sensitive student data, including behavioral logs, disability records, and academic histories. However, privacy considerations are often postponed rather than treated as a foundational design requirement. We present a mixed-methods study combining 12 semi-structured interviews with EdTech professionals and a privacy policy audit of 48 platforms coded across fiv
Scaling Attention Head Analysis via Gradient-Based Attribution in Context-Aware Machine Translation
In this paper, we introduce a gradient-based head attribution strategy where the Token-level Max-Margin loss is backpropagated to the attention maps. This framework enables a large-scale causal analysis of attention heads, making it suitable for LLMs. We evaluate our method on the task of disambiguation in Context-aware Machine Translation, where we analyze 50 phenomena across 4 models and 4 language directions. We e
Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captures a small part of the patient's anatomy. In this work, we aim to reconstruct an extended FOV using projections of truncated FOV scans. To this end, we propose a three-stage framework that consists of (1) an implicit neural representation (INR) for estimating missing pa
Distillation for Efficient Multitask Manipulation Policies via Conditional Flow Matching
Advances in generative modeling have recently been extensively employed in robotics for policy learning. In particular, Conditional Flow Matching (CFM) trained with expert demonstrations has been shown to outperform existing methods on robot manipulation benchmarks. While prior work has mainly focused on single-task settings, we study the problem from a multi-task perspective, as training independent models for each
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 | 11.6% (116) | 7.3% (73) | 74.55% (82) |
| llms.txt (apex domain) | 9.5% (95) | 6.4% (64) | 60% (66) |
| llms.txt (docs subdomain) | 3.9% (39) | 1.2% (12) | 46.36% (51) |
| .well-known/mcp.json | 0.6% (6) | 0.3% (3) | 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) | 0.3% (3) | 0.91% (1) |
Notable events recorded on this day and month across all years.