Record 24092026 · captured 2026-09-25
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.
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
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
Gary Stephen "Angry" Anderson was an Australian rock singer, songwriter, television personality, actor, and political candidate. He was best known as the lead vocalist and the longest-tenured remaining member of the Australian hard rock band Rose Tattoo from 1
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
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
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
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
Dancing with the Stars (American TV series) season 35
Season thirty-five of Dancing with the Stars premiered on ABC and Disney+ on September 15, 2026, and is scheduled to conclude on November 24, 2026. This season was the fourth to air live on both networks simultaneously. Season nineteen champion Alfonso Ribeiro
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
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
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
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
Ella Beatty is an American actress and the daughter of Annette Bening and Warren Beatty.
Digger is a 2026 satirical black comedy film directed by Alejandro G. Iñárritu, who co-wrote the script with Sabina Berman, Alexander Dinelaris Jr., and Nicolás Giacobone, from a story by Iñárritu, Berman, and Jez Butterworth. It is a co-production of the Unit
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
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
Christa Gail Pike is an American convicted murderess 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, wh
Ezra Frech is an American track and field athlete who competes in high jump, long jump and sprinting events. He is a two-time Paralympian, having competed at the 2020 Summer Paralympics and won two gold medals at the 2024 Summer Paralympics. He also won two si
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
Julia O'Hara Stiles is an American actress and director. Stiles began acting at the age of 11 as part of New York's La MaMa Experimental Theatre Club. Her film debut was a small role at age 15 in I Love You, I Love You Not (1996), followed by a lead role in Wi
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").
.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
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
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).
Mary Mallon, commonly known as Typhoid Mary, was an Irish-born cook who lived in the United States from a young age and is believed to have infected up to fifty-seven people with the bacteria that cause typhoid fever. The infections caused three confirmed deat
The Bharatiya Sakshya Adhiniyam (BSA), 2023 is an act of the Parliament of India.
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,
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
LLM Agents Can Easily Tamper With Their Own Traces
Asynchronous monitoring, incident investigations, and compliance audits primarily rely on agent traces to reconstruct what happened. These analyses assume that LLM agents cannot tamper with their own execution traces. We show that local LLM agents such as Claude Code, Codex, Antigravity, Open Code and Grok Build fail to enforce this boundary. All tested harnesses, except Muse Code, allowed agents to delete their trac
AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control
Latent world models are typically trained to predict factual transitions, whereas model predictive control (MPC) must compare alternative actions from the same state. A model can therefore achieve low factual prediction error yet poorly distinguish candidate actions. We introduce AD-WM, an action-discriminative joint-embedding world model for counterfactual MPC. AD-WM combines residual latent dynamics with predictor-
RAPID: Robot Agentic Programming from Demonstrations
Coding agents have demonstrated enormous success in solving complex programming problems. To leverage their potential for robot systems, this work introduces Robot Agentic Programming from Demonstrations (RAPID), which automatically generates, verifies, and refines robot programs, given a single visual human demonstration. The iterative agentic loop of code refinement requires several key ingredients: (i) a testable
Rolling-WAM: World Action Models with Rolling Imagination
World Action Models (WAMs) couple action generation with future visual prediction for robotic manipulation. However, completing the joint video-action denoising process at each replanning cycle incurs substantial latency, delaying action updates and limiting closed-loop responsiveness. We present Rolling-WAM, a formulation that distributes joint denoising across successive replanning cycles. Our method maintains a sl
Coding Agents for Generalized Task and Motion Planning Problems
Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightly coupled to geometric, kinematic, and dynamic constraints. Generalized TAMP addresses this difficulty by exploiting regularities across problem instances to reduce planning effort on new instances. However, existing methods require substantial TAMP-specific engineering
To Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech
Online misinformation increasingly appears in spoken formats such as news clips, podcasts, interviews, political speeches, and social media videos, creating a need for fact-checking systems that can verify claims directly from speech. We introduce VeriSpeak, a probe benchmark for studying speech-based fact verification in Large Audio Language Models (LALMs). VeriSpeak contains 3,879 spoken claims spanning temporal, g
PoEM: Predicting RL Outcomes from Existing Policies
Foundation models are post-trained with reinforcement learning (RL) to maximize specific rewards, such as human alignment, correctness, or instruction following. This post-training process is computationally intensive, sometimes unstable, and has to be run from scratch every time the reward model changes or when we want to combine multiple rewards. We hence ask: given a new reward function, is it possible to predict
TrackEverything: Long Horizon Dense Tracking via De-Duplicating 3D Scene Representations
Existing point tracking models face a fundamental tradeoff: they can either track a sparse set of query points over long horizons, or track all points across only short clips. We introduce TrackEverything, a 3D point tracker that breaks this trade-off by representing videos as persistent 3D scene tracks in world coordinates. Grounded in the insight that videos are 2D projections of an underlying 3D world, TrackEveryt
An acceptance protocol is developed for sensor-coordinate and polarity binding in mechatronic commissioning. Candidate generation is separated from release authority. Requirements unsupported by a deterministic parser are routed to a frozen local language model with four billion parameters. Plans are released only when both facts can be derived by an external gate under a sealed grammar. One canonical answer is reque
Minimally Invasive Steering of Language Models
Pre-logit steering adapts a frozen language model to a test-time reward by adding vectors to its final hidden states. Unregularized reward optimization can substantially alter the output distribution and degrade generation quality. We propose Minimally Invasive Steering Vector Optimization (MISVO), which penalizes interventions using the local KL geometry of the induced token distribution. The resulting Fisher quadra
Instrumental Monitor Evasion Emerges Under Ordinary Task Pressure
A central concern in AI safety is that agents may treat oversight as an obstacle when it conflicts with completing their goals. We study instrumental evasion, the propensity of LLM agents to circumvent runtime monitoring as a means of completing ordinary tasks. We introduce EvasionBench, a benchmark of 50 diverse task-policy pairs in which completing the task requires an operation prohibited by a runtime monitor. Age
Underwater C3-JEPA: An Object-Centric Cross-View World Model for ROV Salvage
We present Underwater C$^{3}$-JEPA (cross-view, control-conditioned, context-extended), an object-centric multi-view predictive world model for near-field heavy-load underwater ROV salvage. Without contact sensors, it predicts in latent space how the task-object state evolves through contact interaction and under the hydrodynamic lag of the vehicle, from synchronized multi-view RGB observations and vehicle control si
A Living Benchmark for Information Retrieval from Electronic Health Records
Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how clinicians retrieve and synthesize information from patient records. Their safety and utility depend on rigorous evaluation, yet existing benchmarks are manually curated, costly to update, and rapidly become obsolete with evolving technological advancements. We present a
ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds
Scientific discovery begins where known problems end. There, AI systems must engage in exploration: framing hypotheses, designing experiments, and iterating on the results. However, evaluating this ability is difficult: (1) how to verify whether a genuinely new hypothesis holds, and (2) how to determine whether a system has discovered it through exploration or merely recalled related knowledge from pre-training data.
SAGE: Mitigating Long-Horizon Reasoning Biases via Topological Guidance
Long-horizon reasoning remains a central challenge for large language models (LLMs) under sparse-reward regimes. We argue that this brittleness arises from two biases induced by complex reasoning spaces: an exploration bias, where models are drawn toward locally plausible but structurally unstable branches, and a compounding bias, where small local deviations accumulate across depth and suppress rare rewards. We intr
Jev-Mobile: Jev as an Executor for Mobile GUI Agents
Vision-language models (VLMs) have become a common foundation for autonomous mobile GUI agents, but most existing systems rely on the VLM for both planning and action grounding at nearly every interaction step, leading to substantial latency and model-serving cost. We introduce Jev-Mobile, which shifts this paradigm to low-frequency VLM planning and high-frequency lightweight execution: the VLM specifies local goals,
Search-Aware Reinforcement Learning for Multi-Component Query Understanding in Roblox Game Search
Query understanding (QU) plays a critical role in production search systems, translating raw user queries into search execution plans that drive downstream retrieval and ranking. While large language models (LLMs) have enabled QU to be framed as a structured multi-task generation problem (e.g., intent classification, query expansion), optimizing such models to produce search-engine-coupled outputs remains challenging
Does a model's stated reason for rejecting a candidate do any work?
Asked to choose between candidates and explain the choice, a language model often rejects a rival by naming a fact its profile lacks: no director, no date of death. That sentence is a claim about the text in front of the model, and it can be tested without any judge. We insert a real corpus sentence stating the named fact into the rival's profile and ask again under greedy decoding. Two controls separate content from
GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI
Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases. We address the challenge of generating high-quality natural language executable plans for complex tasks by introducing $\textbf{GRASP}$, a strategy-aware, multi-stage planning framework. GRASP decouples the planning pipeline across specialized, context-isolated modules: it pre-compiles global
EnigmaForge: The Question Is Hidden in the Story
Most benchmarks hand the model a question. EnigmaForge hands it a stack of old documents and no question at all. Buried in the letters, receipts, and logbook margins is a small logic puzzle whose solution is unique - proved by a SAT solver at generation time, with an ablation certificate showing every clue is load-bearing. Because instances are generated rather than collected, the corpus renews forever. The headline
Screen Before You Serve: Simulation for Production Customer Experience AI Agents at 140M Scale
Customer experience (CX) agents use tools and large language models to address customer requests and guide conversational interactions with an organization's products. Improving these agents, especially in regulated industries, is difficult: they must detect intent, follow complex operational policies and use tools reliably. Manual end-to-end testing offers limited coverage, while live experiments expose customers to
HEXIS: Compiling Skills into Extended Finite State Machines
Agent skills provide reusable knowledge and instructions, yet agents must repeatedly infer how to apply them and which operation should follow. This couples task reasoning with control decisions, allowing prescribed steps to be omitted or applied incorrectly. We introduce HEXIS, which compiles agent skills into extended finite state machines that separate knowledge from control flow. Skill knowledge is incorporated i
R-DEIM Net: An Efficient Rationale-Augmented Dual-Expert Interaction Model for Paraphrase Detection
Recent advances in paraphrase detection reveal a fundamental trade-off: large language models achieve high accuracy but require high computation, while efficient Siamese-BERT variants offer practical scalability with reduced transparency in rationale generation. We present R-DEIM Net, a 76M-parameter dual-expert architecture exploring whether moderate-scale models can achieve competitive accuracy on paraphrase detect
Accelerating Video Diffusion via Training-Free Trajectory Routing
Video diffusion is computationally expensive, as it requires executing a large model across many denoising steps. Even with step-distillation, inference remains expensive because every distilled step still requires a costly model evaluation. We present TRACK: TRajectory-Aware Capacity routing via top-K selection, a heterogeneous denoising strategy that switches between compatible large and small models at selected st
PrivDrift: Auditing User-Secret Leakage Under Topic Drift in Active LLM Conversations
Large language models increasingly operate as persistent assistants in user-facing, shared-session, and tool-augmented settings. When users disclose sensitive information during an active conversation, that information may remain behaviorally recoverable through later prompts even after the dialogue shifts to unrelated topics. We introduce \textbf{PrivDrift}, a benchmark for auditing whether user-disclosed secrets re
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 | 12.2% (122) | 5.4% (54) | 74.55% (82) |
| llms.txt (apex domain) | 9.8% (98) | 4.7% (47) | 60% (66) |
| llms.txt (docs subdomain) | 4.1% (41) | 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) | 0.7% (7) | 0.1% (1) | 0.91% (1) |
Notable events recorded on this day and month across all years.