Record 02112026 · captured 2026-11-03
The world looked up Haley Stevens. 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.
Haley Maria Stevens is an American politician serving as the U.S. representative from Michigan's 11th congressional district since 2019. Elected as a member of the Democratic Party, Stevens represents most of urbanized Oakland County, including many of Detroit
Sir Patrick Stewart was an English actor. With a career spanning over 60 years on stage and screen, he received numerous accolades, including three Laurence Olivier Awards and a Grammy Award, as well as nominations for a Tony Award, three Golden Globe Awards,
Tung Tung Tung Sahur is an AI-generated fictional character created in 2025 using DALL-E by the Indonesian TikTok user Fernanda Bagas Indrastata, also known as "Noxa" online. Although culturally Indonesian, the character gained initial popularity as a part of
Nidhi Razdan is an Indian journalist and television personality. She was the executive editor of NDTV and the primary anchor of NDTV 24x7 news debate show Left, Right & Centre, and the weekly debate show The Big Fight.
Gabrielle Lisa Williams is an French-American professional basketball player for the Golden State Valkyries of the Women's National Basketball Association (WNBA). She was selected fourth overall by the Chicago Sky in the 2018 WNBA draft. She was a EuroLeague c
Danielle Fabiola "Inde" Navarrette is an American actress. She began acting in short films as a teenager before landing roles in the drama series 13 Reasons Why (2020) and the superhero series Superman & Lois (2021–2024). Navarrette achieved global stardom for
Heidi Kaulitz is a German and American model, television host, actress, producer, and businesswoman. She appeared on the cover of the Sports Illustrated Swimsuit Issue in 1998 and was the first German model to become a Victoria's Secret Angel.
Ciara Mageean was an Irish middle-distance runner. She specialised in the 1500 metres. Mageean won the gold medal in the 2024 European Athletics Championships, and became the first individual Irish European champion since Sonia O'Sullivan.
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 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
Abdulrahman Mohamed "Abdul" El-Sayed is an American epidemiologist, public health administrator, academic and politician who is the Democratic nominee in the 2026 United States Senate election in Michigan.
Jailer 2 is a 2026 Indian Tamil-language action comedy film written and directed by Nelson Dilipkumar. It was produced by Kalanithi Maran through Sun Pictures. A sequel to Jailer (2023), the film stars Rajinikanth, Ramya Krishnan, Yogi Babu, Mirnaa and Rithvik
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
Andrea Kimi Antonelli is an Italian racing driver who competes in Formula One for Mercedes. Antonelli won the Formula One World Drivers' Championship in 2026 with Mercedes, becoming the youngest-ever World Drivers' Champion; he has won nine Grands Prix since h
Sanjay Gupta was an Indian filmmaker, producer, and screenwriter who worked in Hindi films. Gupta was mostly known for his remakes of American action-thriller and crime films, including films such as Aatish, Kaante, Kaabil, Shootout at Lokhandwala, Shootout at
Halloween, also known as All Hallows' Eve or All Saints' Eve, is a celebration observed in many countries on 31 October, the eve of Western Christianity's feast of All Hallows' Day. It is at the beginning of the observance of Allhallowtide, the time in the Chr
Omar Farooq Abdullah is an Indian politician serving as the chief minister of the union territory of Jammu and Kashmir since 2024. He is also currently serving as the Leader of the House in the Jammu and Kashmir Legislative Assembly. He had previously served a
You Can See Everything is a 2026 American metadocumentary 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 invited a film crew to docume
Elections are currently being held in the United States on November 3, 2026. In these midterm elections, which occurred during the second term of Republican president Donald Trump, all 435 seats in the U.S. House of Representatives and 35 of the 100 seats in t
Natalie Mitsue Nakase is an American professional basketball coach and former player who is the head coach of the Golden State Valkyries of the Women's National Basketball Association (WNBA). After retiring as a player, she was a head coach for both men's and
Obsession is a 2025 American supernatural horror film written, directed, and edited by Curry Barker. It follows shop clerk Bear as he makes a wish for his friend Nikki to fall in love with him, which makes her become obsessed. Cooper Tomlinson, Megan Lawless,
Matthew Langford Perry was a Canadian and American actor. Known primarily for his work in comedy, he gained international fame for starring as Chandler Bing on the NBC television sitcom Friends (1994–2004), receiving his first Primetime Emmy Award nomination i
Clayface is a 2026 American body horror film based on the eponymous character from DC Comics. Directed by James Watkins from a screenplay by Mike Flanagan and Hossein Amini, it is the third film in the DC Universe (DCU). Tom Rhys Harries stars as Matt Hagen /
Maya Indea Jama is a British broadcaster and media personality. She began her career as a presenter for MTV, 4Music and BBC Radio 1. She has presented television shows, including The Circle (2017), Glow Up: Britain's Next Make-Up Star (2021–2022), and Love Isl
Christopher Scott Murphy is an American lawyer, author, and politician serving since 2013 as the junior United States senator from Connecticut. A member of the Democratic Party, he served from 2007 to 2013 in the United States House of Representatives, represe
The Golden State Valkyries are an American professional basketball team based in the San Francisco Bay Area. The Valkyries compete in the Women's National Basketball Association (WNBA) as a member of the Western Conference. The team began play in the 2025 seas
Neelesh Misra is an Indian journalist, author, radio storyteller, scriptwriter and lyricist. He hosted Yaadon Ka IdiotBox on BIG FM 92.7. He is co-founder and editor of Gaon Connection, a rural newspaper. He is working on "The Neelesh Misra Show" on Red FM 93.
The Day of the Dead is a holiday traditionally celebrated on November 1 and 2, though other days, such as October 31 or November 6, may be included depending on the locality. The multi-day holiday involves family and friends gathering to pay respects and remem
Wildwood is a 2026 American stop-motion animated epic fantasy film directed by Travis Knight and written by Chris Butler, based on the 2011 novel by Colin Meloy and Carson Ellis. Produced by Laika, the film stars Carey Mulligan, Peyton Elizabeth Lee, Jacob Tre
Santos Saúl "Canelo" Álvarez Barragán is a Mexican professional boxer. He has held multiple world championships in four weight classes, from light middleweight to light heavyweight, including unified titles in three of those weight classes. He has held the Wor
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Pixel-UMI: Learning Environment-Aware Whole-Body Manipulation from Sensorized Human Demonstrations
Sensorized human demonstrations offer scalable data for mobile manipulation, but embodiment differences complicate policy learning. We present Pixel-UMI, a pipeline for learning environment-aware whole-body policies from human data. We first introduce Environment-Aware Retargeting (EAR), which combines reconstructed scene geometry with demonstrated head and gripper trajectories to determine robot posture and generate
Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation
General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, creating mismatches that limit the capabilities of the complete system. We present Pixel, a co-designed full-stack system for learning general-purpose mobile manipulation. Pixel com
From Natural Language to Exact Cover: A Neuro-Symbolic Approach to Zebra Puzzles
Chain-of-Thought (CoT) generation has substantially improved the performance of Large Language Models (LLMs) on complex reasoning tasks, including code generation, data analysis, and exam-style question answering. Despite these advances, purely neural LLMs continue to struggle with elementary logical reasoning problems and lack the determinism, soundness, and reliability characteristic of symbolic reasoning systems.
WebHarbor: Docking Real Websites for Evolving GUI Agent Environments
GUI web agents require realistic and interactive environments that remain stable during both evaluation and training. Live website evaluation suffers from changing content, access restrictions, and limited coverage of authenticated workflows, while existing synthetic environments for training often lack functional depth and visual fidelity. We propose WebHarbor, a suite of 153 executable and dockerized website enviro
D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Reward Models
Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in failed executions due to implicit success assumptions or relative temporal ranking designs. Naive prompting of frontier models collapses into a binary success detector that fails to capture nuanced, non-linear progress an
Strategist: Evolving Reasoning with Agents
A model is only half of an AI agent system. The other half is the inference strategy: the reasoning procedure that turns model calls into a response. Today that second half is written by hand, and the experience of building one strategy never carries to the next. We introduce Strategist, a meta-agent that evolves inference strategies across tasks. Each strategy is written as a blueprint,executable code that other str
Tracing the Scientific Discovery Capacity of LLMs to Their Training Data
Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery. How can we trace the scientific discovery capacity of LLMs to their training data? We study this question as one of missing probability mass and develop a theoretical account in which monofacts-the facts observed once during training-set the discovery capacity. In materials sci
DiabAgent: Toward Agentic Physiological Control
As pretraining scales, medical language models have advanced rapidly in clinical question answering. Their ability to achieve effective physiological control through sustained intervention still lacks systematic quantitative evaluation. Type 1 diabetes provides a concrete setting: impaired insulin secretion creates dependence on exogenous insulin, with dosing continually adjusted using information about meals, exerci
Four Bridges: Measuring Deception Propensity in a Multi-Agent Game
AI agents are increasingly deployed in settings where they interact and coordinate with other agents, yet honesty is mostly measured in single-turn, single-agent benchmarks that pressure the model to deceive. We study deception that emerges in multi-agent interaction without any instruction to deceive. We introduce Kradle, a platform for evaluating AI models, and Four Bridges, an information asymmetry game in which f
Spacetime Emergence in the Memory of a Learning Agent
We show that the causal structure of spacetime can emerge within the memory of a learning agent performing a quantum information task. We train a model-based reinforcement-learning agent to maximize the quantum mutual information between localized quantum probes interacting with a quantum field in Minkowski spacetime, without directly providing it with information regarding the spacetime metric or causal structure. I
Evaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models
Time series foundation models (TSFMs) are increasingly used for probabilistic forecasting across diverse domains, yet the reliability of their uncertainty estimates remains poorly understood. In this work, we study uncertainty calibration in probabilistic TSFMs from a broader methodological and empirical perspective. We introduce a taxonomy of how TSFMs represent predictive uncertainty and develop a fine-grained eval
FedReady: Bounded Agents for Federation Formation
Federated learning (FL) runtimes standardize aggregation and deployment, but each new study still requires federation formation: selecting task-eligible sites and preparing their local data and task code for federated training or analysis. This preparation recurs when the target changes, while raw records and site-private mappings are excluded from cross-site FL messages. We present FedReady, a system that performs f
Sonar-MoE: In-Backward Expert Updates for Memory-Efficient Mixture-of-Experts Training
Most parameters of a Mixture-of-Experts (MoE) model belong to its experts, and standard training keeps every expert gradient in GPU memory until the optimizer step. This memory grows with the number and size of the experts, so it rises as MoE models scale. We introduce Sonar-MoE, which updates each expert tensor during the backward pass and frees its gradient right away. It brings optimizer-in-backward from dense mod
PlantVLM-Edge: Quantized Vision-Language Models for On-Device Crop Health Diagnosis
Timely and accurate crop health diagnosis is essential for sustainable agricultural production, yet accurate diagnosis often requires expert knowledge that is not readily available. Recent vision-language models (VLMs) have demonstrated remarkable capabilities in visual understanding, reasoning, and natural-language interaction, creating new opportunities for intelligent crop health assessment. However, deploying VLM
MCP Tool Poisoning in Agentic AI Frameworks: A Cross-Framework Measurement Study
The Model Context Protocol (MCP) lets agentic AI frameworks connect language models to external tool providers, but it carries attacker-controlled content (tool descriptions, schema fields, and response data) into model context without validation. Prior benchmarks measure model compliance with poisoned instructions without confirming real execution. We present the first cross-framework measurement of MCP tool poisoni
LLM coding agents can increasingly automate model post-training, but whether they can act as forward-deployed engineer (FDE) agents, discovering customer requirements and turning them into deployment decisions, remains unclear. We study this on a real enterprise text-to-SQL engagement: a simulated customer, grounded in the real use case's requirements, starts with an ambiguous request. An agent must discover acceptan
An Agentic Framework for Automated Power System Studies and Grid Connection Assessment
Connecting new generation and demand to the grid depends on two scarce skills: checking applications against a large, changing body of regulation, and running the network studies that decide where and how a project connects. We present Grid Agents, an AI system that brings both together, and the methodology we use to evaluate it. The Grid Ontology is its knowledge system. It represents the regulation, standards and e
Skin cancer diagnosis, particularly differentiating melanoma from benign nevi, is challenging due to the visual similarity between lesions. Although convolutional neural networks (CNNs) and vision transformers (ViTs) have shown promising performance, their effectiveness often deteriorates on data from heterogeneous clinical sources. Conventional domain adaptation methods address domain shift but require access to sou
Library of Layers (LoL): Adaptively Ordering Transformer Layers at Runtime
Computer programmers chain together the same reusable computational primitives, for example, conditional statements or loops, but in different orders to implement different algorithms. In contrast, existing language model architectures always execute their layers in the same order. We introduce Library of Layers (LoL), an architecture that dynamically orders its layers during inference to solve the problem at hand. L
Grading the Unannotated: Insights from the WorkRB Skill Extraction Challenge at RecSys-HR 2026
Skill extraction benchmarks score models against a few human-annotated positives and treat every other skill in the vocabulary as equally wrong. At the scale of ESCO (13,939 skills) this binary view can reward models that rank the annotated positive high for the wrong reason, and hides semantically nonsensical predictions. The WorkRB Challenge at RecSys-HR 2026 replaces it with graded relevance: every candidate skill
PanoTac: A Dense Three-Axis Tactile Sensor for Robust Touch-Centric Manipulation
Contact-rich manipulation benefits from tactile feedback that captures both detailed contact geometry and interaction forces. When scooping grains, contact patterns help infer spoon orientation, while resistance transmitted through the grasp guides motion. To provide these complementary sensing capabilities, we present PanoTac, a low-cost, compliant tactile fingertip designed for dense three-axis tactile sensing. Eac
VIAS: Value-Isolating Activation Steering for Multi-Value Alignment and Compliance for Organisations
Organisations increasingly deploy large language model agents that must follow organisational values. We check whether activation steering, which adds vectors to a model's internal activations during generation without changing its weights, can improve compliance beyond prompting alone. Since most scenarios involve several values at once, we focus on multi-value steering. A simple way to build these vectors is to con
A Cross-Domain Matrix Engine for Signal Processing and Deep Neural Net Inference
Matrix multiplication dominates both PHY signal processing and Deep Neural Network (DNN) inference, yet these domains place opposing demands on the matrix engine. Signal processing requires low-latency execution of relatively small matrix operations, whereas DNN inference, particularly at large batch sizes, prioritizes high throughput and energy efficiency for large matrix multiplications. While offering efficient me
Can AI contribute to formal demography? We report an experiment in which an AI model, Claude, was asked to explain and then simplify the proof of an earlier result: that vaccinating the oldest against COVID-19 saves both the most lives and the most years of life, because the years saved per person treated rise with age. The model proposed a new proof that is shorter, more intuitive, and somewhat more general than the
Online Label-Free Gradient Matching for Continual Language Model Training
Language models in customer-facing products must be continually updated, since the data they serve shifts over time. As retraining on the full accumulated data is impractical, each update should instead run on a small set of examples carrying the training signal of all data seen so far. The strongest current methods build this set by gradient matching, which synthesizes examples whose training gradients match those o
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 | 13.7% (137) | 4.5% (45) | 74.55% (82) |
| llms.txt (apex domain) | 11.9% (119) | 3.8% (38) | 60.91% (67) |
| llms.txt (docs subdomain) | 4% (40) | 1% (10) | 47.27% (52) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 9.09% (10) |
| .well-known/agents.txt | 0.3% (3) | 0.2% (2) | 0% (0) |
| ai.txt | 0.3% (3) | 0.1% (1) | 0% (0) |
| ai-plugin.json (deprecated) | 0.6% (6) | 0.2% (2) | 0.91% (1) |
Notable events recorded on this day and month across all years.