Record 26102026 · captured 2026-10-27
The world looked up 2026 Brazilian general election. 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.
2026 Brazilian general election
General elections were held in Brazil on 4 October 2026 to elect the president, vice president, members of the National Congress, the governors, vice governors and legislative assemblies of all federative units, and the district council of Fernando de Noronha.
2026 Serbian parliamentary election
Early parliamentary elections were held in Serbia on 25 October 2026 to elect members of the National Assembly. The elections were originally due by December 2027; Aleksandar Vučić, then the president of Serbia, dissolved the National Assembly and called the e
Clayface is a 2026 American body horror psychological thriller 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
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
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
You Can See Everything is a 2026 American meta-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 invited a film crew to
2026 British Columbia general election
The 2026 British Columbia general election was held on October 24, 2026, to elect members of the Legislative Assembly of 44th Parliament of the Canadian province of British Columbia. Lieutenant Governor Wendy Lisogar-Cocchia dropped the writs of election on Se
Damodharan Kothandaraman, professionally known as Chef Damu, was an Indian celebrity chef. He was known for hosting numerous cooking shows and serving as a judge on popular Tamil language television programs, most notably Cooku with Comali on Star Vijay. He ho
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
Wildwood is a 2026 American stop-motion animated epic dark 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, Jaco
Lorne Doerkson MLA is a Canadian politician who is the premier-designate of British Columbia. He has served as interim leader of the Conservative Party of British Columbia and leader of the Opposition since 2026. A member of the Legislative Assembly of British
Ainsley Earhardt is an American conservative television host and author. She is a co-host of Fox & Friends.
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
William Evans is an American businessman who founded and runs Haemanthus, a diagnostics start-up based in Austin, Texas. He became the partner of Elizabeth Holmes, the founder of Theranos, in 2017. Evans is featured in the book Bad Blood: Secrets and Lies in a
Sean Patrick Hannity is an American conservative television presenter, political commentator, broadcaster and writer. He hosts The Sean Hannity Show, a nationally syndicated talk radio show, has hosted a self-titled political commentary program on Fox News sin
Candice Susan Swanepoel is a South African model. She is best known for her work with Victoria's Secret. She became a Victoria's Secret Angel in 2010. In 2016, she was listed 8th on the Forbes top-earning models list.
The Student List is a Serbian electoral list formed by the Students in Blockade, the student movement that led the anti-corruption protests following the Novi Sad railway station canopy collapse in November 2024. First announced in May 2025, after the students
Abdulrahman Mohamed 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.
Dorothy is a 2026 Indian Tamil-language crime drama film written and directed by Karthik Subbaraj and produced by Guneet Monga Kapoor, Achin Jain and Jyoti Deshpande. The film stars Sananth, Rishikanth, and Keerthy Suresh in the lead roles. It follows two inse
Wicker is a 2026 romantic fantasy comedy-drama film written and directed by Alex Huston Fischer and Eleanor Wilson, based on the short story "The Wicker Husband" by Ursula Wills. The film stars Olivia Colman, Alexander Skarsgård, Elizabeth Debicki, Marli Siu,
Nathan Joseph Fielder is a Canadian filmmaker, actor, and comedian. He is known for his awkward, deadpan persona and his use of satire and surreal humor.
Alexander Volkanovski is an Australian professional mixed martial artist. He currently competes in the Featherweight division of the Ultimate Fighting Championship (UFC), where he is the current and two-time UFC Featherweight Champion. Volkanovski is the first
Jamie Miller is a Welsh singer-songwriter from Cardiff, currently based in Los Angeles. He first gained recognition as a finalist on The Voice UK in 2017, where he finished in third place. Known for his blend of pop and R&B influences, Miller signed with Atlan
The Orions are a fictional extraterrestrial humanoid species in the American science fiction franchise Star Trek, making their first appearance in the initial pilot for Star Trek: The Original Series, "The Cage". Susan Oliver portrayed the first Orion seen on
Archibald Charles Manning is an American college football quarterback for the Texas Longhorns. He is a member of the Manning family of football players.
UFC 333: Volkanovski vs. Evloev was a mixed martial arts event produced by the Ultimate Fighting Championship that took place on October 24, 2026, at the Etihad Arena in Abu Dhabi, United Arab Emirates.
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'.
Street Fighter is a 2026 martial arts film directed by Kitao Sakurai and written by Sakurai and T. J. Fixman, with a story by Dalan Musson and Gary Dauberman. It is the third live-action feature-length film based on the Street Fighter video game series by Capc
The Kehlsteinhaus, commonly known in English as the Eagle's Nest, is a Nazi-era chalet situated atop the Kehlstein, a subpeak of the Hoher Göll above Obersalzberg, near Berchtesgaden in southeastern Germany. Completed in 1938, it was commissioned by Martin Bor
Elections are scheduled to be held, in large part, on November 3, 2026, in the United States. In these midterm elections, scheduled to occur during Republican president Donald Trump's second term, all 435 seats in the U.S. House of Representatives and 35 of th
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Retriever-Free Retrieval: Navigating Documents with Decision Models
While language models have become dramatically more capable, retrieval still largely relies on lexical matching or similarity in fixed embedding spaces. This creates a capability asymmetry: what the retriever fails to find, even the strongest generator cannot recover. We propose DecisionRAG, which brings the capabilities of pretrained language models to retrieval using decision models that jointly evaluate candidate
Center-of-Mass Interpretation of Evolution Strategies
Evolution strategies (ES) update a model by sampling a population of perturbed copies, scoring each one, and moving in the reward-weighted direction of the perturbations. This update is usually presented as an estimate of a smoothed gradient. We present a geometrical interpretation of this update instead. Treat each perturbed model as a particle and its reward as the particle's mass. Before scoring, every particle ha
Learning Force-Reactive Humanoid Loco-Manipulation
Many everyday tasks require controlling contact force as well as motion. On a humanoid, this force must often be coordinated across both hands and the whole body, and cannot be specified by kinematic trajectories alone. Therefore, we present FLORE, a framework for learning force-reactive humanoid loco-manipulation. We collect robot-free demonstrations using two force-sensing UMI-style handheld grippers for hand motio
Patient-specific rubric-based evaluation of large language models across longitudinal cancer care
Large language models (LLMs) show promise in specialty medicine, yet existing evaluations largely focus on isolated clinical encounters rather than tracking how clinical responsibilities evolve across a longitudinal care pathway. Here we introduce NPC-RubricBench, a phase-aware benchmark for evaluating multistage clinical reasoning across the cancer care continuum, using nasopharyngeal carcinoma as a defined disease
I-HITL: Inalienable Human-in-the-Loop
Human oversight is a pillar of AI safety. It is often exercised by a human in the loop (HITL) who approves critical actions taken by an AI agent. AI agents' increasing ability to bypass guardrails, though, raises the question of how to enforce HITL robustly. We introduce the concept of inalienable human-in-the-loop (I-HITL). An I-HITL protocol ensures that an agent can initiate an action only with explicit human appr
Profiling a Frontier Agent with EBench: From Direct Control to Harness with Policy
Frontier multimodal large language models (MLLMs) can control robots without robot-specific training, but how their capabilities compare and interact with post-trained vision-language-action (VLA) and world action model (WAM) policies across manipulation demands remains to be thoroughly evaluated. In this report, we evaluate GPT-6-Astra on EBench as the core of an agent that controls a robot through an agent harness
Reva: Real-Time Vulnerability Detection through Contextual Probing of Large Language Models
A vulnerability costs more to fix the later it is discovered. As coding agents generate code faster than developers can review it, software needs a first line of defense screening each new function in real time. LLM agents have recently become capable of finding real-world vulnerabilities by working as a security expert would: they run analysis tools, explore the surrounding code, test hypotheses and weigh the eviden
A robot policy needs to understand what a task is asking for in a scene, and how to move the robot to accomplish that task. To achieve these two skills, we introduce Zero-real Agent Policy (ZAP), a recipe that teaches a small off-the-shelf vision-language model to control a robot via a simple tool harness. We use a pretrained 27B parameter model to bootstrap world understanding and reasoning, followed by supervised f
Learning When to Commit: Schedule Distillation for Fast Diffusion Language Models
Diffusion large language models (dLLMs) can generate multiple tokens in parallel, but often require many decoding rounds to complete a response. Efficient generation depends not only on which tokens are easy to predict, but also on how committing to them helps predict the remaining positions. A highly predictable token may provide little useful context, while revealing a less predictable token can help several other
Game theory of academic effort and hiring in the age of AI
Many academic disciplines (in particular, mathematics and the theoretical sciences) face difficult questions about how to adapt their practices to the rise of highly capable artificial intelligence (AI). Before AI, a well-written research paper with a strong theoretical result acted as a reliable signal that its authors understood their field in depth. Now that AI is widely accessible, such signals have become cheape
A Unified Arena for LLM Agents across Diverse Eurogame
Interactive environments offer a practical way to evaluate large language model (LLM) agents, and competitive games extend this evaluation to decisions shaped by competing goals and other agents' choices. Yet existing evaluations confined to individual games or execution frameworks leave unclear which competitive advantages persist across settings. We introduce DECE (Diverse Eurogame Competitive Environments), a unif
Root cause analysis (RCA) of microservice failures has attracted many LLM agents whose investigation is hand-crafted, through standard operating procedures, fixed stages and role agents. Each is evaluated on its own data against few baselines, so it is unknown whether this design beats letting a capable model investigate on its own. We compare three simple harnesses that prescribe none of the model's calls (one call
Item-item similarity is one of the oldest and most foundational signals in recommender systems: two items are assumed to be similar when the same users consume them. Despite the sparsity and scale of interaction data, the implicit assumption across the field is that item co-occurrence reflects genuine shared preference, capturing what users like together. In this paper, we demonstrate that a substantial fraction of o
Mental-health risks such as depression, dementia, and suicidal ideation can emerge during hospitalization among chronically ill patients and may worsen without timely recognition and intervention. However, most existing mental health studies focus on patients with established psychiatric conditions rather than patients hospitalized primarily for physical illness. In this work, we investigate whether latent mental-hea
EEGaze: Multimodal Attention Prediction in Visual Search via EEG-Based Saliency Refinement
Visual search is ubiquitous in daily life, from locating keys in a messy apartment to finding a tool in a cluttered workshop or an application icon on a desktop screen. While visual attention is to a large extent driven by image content, research in psychology indicates that user cognitive states have a significant influence on attention allocation. A promising way to access information about cognitive states is via
CLOSURE: Cross-Channel Closure for Multivariate Time Series Anomaly Detection
Multivariate time series produced by industrial installations and server clusters are under continuous monitoring, and anomaly detection is the first line of defense before a local fault escalates into a system-wide failure. In the absence of labels, the dominant paradigm trains a reconstruction model on normal data and scores the residual to reach a verdict. Recent work has steadily enriched the expressiveness of th
Multi-Objective Reinforcement Learning Using Routed Ensembles and Trajectory Attribution
Multi-objective reinforcement learning is a fundamental problem for modern AI, with applications spanning post-training, reasoning models, and robotic control. A central challenge is to learn policies that balance competing objectives, such as helpfulness versus honesty in safety and alignment, or speed versus energy in robotics. The optimal policy can vary sharply with objective-weighting combinations, and the exten
The Watchtower Imperative: Lifespan-Calibrated Evaluation for Frontier AI
The gap between AI capability deployment and safety assurance is structural and cannot be closed through internal evaluations alone. Analyzing documented harms (2017-2026) across the human lifespan reveals that disparate incidents --- from voice assistants endangering children to AI companions implicated in adolescent suicide and automated care denials for the elderly --- reflect a single failure: evaluating systems
Can JEV Support Clinical Trial Criteria Assessment?
Clinical trial prescreening requires distinguishing unmet conditions from insufficient evidence in patient records. Given patient records, criterion questions, and predefined answer options, we retrospectively compared JEV, a non-generative decision model returning native option probabilities, with schema-constrained Qwen Flash across 2,048 test patient-condition pairs from TrialGPT and question-answer datasets deriv
Audit Where Hacks Pay: Budgeted Strong-Verifier Audits Against Reward Hacking in GRPO
Reinforcement learning with verifiable rewards trains on cheap checks, such as unit tests, that a policy can learn to game, while a stronger check is too expensive to run on every rollout. We study how to spend a limited strong-verifier budget in GRPO, separating which weakly passing rollouts to audit from what reward a caught hack receives. At a fixed policy state with centered advantages, the expected update depend
Transformer-based language models exhibit an astonishing capacity to generalize to longer and more difficult problem instances than those seen in training. However, theoretical understanding of this phenomenon still lags behind. Unlike most machine learning models, the generalisation abilities of transformers inherently require considering two axes. On one hand, one must examine in-distribution statistical generalisa
Explainable Multimodal AI Approach to Reduce Unnecessary Breast Biopsies
Recently, there has been rise in multimodal vision-language models for computer-aided diagnosis (CAD), yet their application in breast diagnosis, particularly for predicting biopsy outcomes remains limited. This study presents a multimodal vision-language approach, incorporating Grad-CAM as an Explainable AI (XAI) technique, to predict benign tumors in patients recommended for biopsy, especially those classified as B
MiRL: Error-Targeted Reinforcement Learning for Correcting Terminal Agent Misbehaviors
Error-targeted learning gives a legible way to improve a model: identify specific weaknesses of the model, train the model to fix these weaknesses, and check whether the weaknesses are fixed. We study how to apply error-targeted learning to terminal agents, which solve long-horizon tasks specified in natural language by interacting with a command shell. Existing error-targeted methods are designed for single-turn tas
Towards a Unified Framework of Optimal Input-Side Dimensional Configuration for Deep CTR Prediction
Deep click-through rate (CTR) prediction has achieved substantial success through increasingly expressive feature interaction architectures. However, predictive performance also depends on how input-side information is configured before interaction modeling. Existing studies have shown that selecting informative samples, features, or embedding units can improve prediction accuracy. Nevertheless, they primarily optimi
EvoRouter: Cost-Efficient Multi-Agent Routing via Insight-Guided On-Policy Distillation
Serving web queries at scale with multi-agent systems requires jointly configuring large language models, collaboration modes, agent counts, interaction rounds, and skills. However, the resulting configuration space grows combinatorially, while sparse execution rewards provide limited fine-grained supervision for interdependent planning decisions. We propose EvoRouter, a self-evolving multi-agent routing framework dr
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 | 13.5% (135) | 5.2% (52) | 74.55% (82) |
| llms.txt (apex domain) | 11.5% (115) | 4.5% (45) | 60.91% (67) |
| llms.txt (docs subdomain) | 4.1% (41) | 1% (10) | 46.36% (51) |
| .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) | 0.1% (1) | 0.91% (1) |
Notable events recorded on this day and month across all years.