Record 16092026 · captured 2026-09-17
The world looked up 2014 European Parliament election. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
Complete record JSON
What the most people looked up, ranked by Wikipedia pageviews for that day.
2014 European Parliament election
The 2014 European Parliament election was held in the European Union (EU) between 22 and 25 May 2014. It was the 8th parliamentary election since the first direct elections in 1979, and the first in which the European political parties fielded candidates for P
Widow's Bay is an American supernatural comedy horror television series created by Katie Dippold for Apple TV, and starring Matthew Rhys, Kate O'Flynn, Kevin Carroll, Dale Dickey, Kingston Rumi Southwick, and Stephen Root. The series is set in the fictional Ne
Matthew Rhys is a Welsh actor. Known for portraying morally complex protagonists, he has received various accolades including four Primetime Emmy Awards, becoming the first and only actor to win in all three Lead Actor categories in Emmys history. He has also
John Davis Tuggle was an American professional football running back who played in the National Football League (NFL) for one season with the New York Giants. He played college football for the California Golden Bears and was selected by the Giants as the fina
Thomas Joseph Pelphrey is an American actor. He is known for playing the roles of Jonathan Randall on the CBS television series Guiding Light, Mick Dante on As the World Turns, Kurt Bunker on Banshee, Ward Meachum on Iron Fist, Ben Davis on Ozark, Perry Abbott
The 78th Primetime Emmy Awards honored the best in American prime time television programming from June 1, 2025, until May 31, 2026, as chosen by the Academy of Television Arts & Sciences. The awards ceremony was held live on September 14, 2026, at the Peacock
Kenneth Walker III is an American professional football running back for the Kansas City Chiefs of the National Football League (NFL). Nicknamed "K9", he played college football for the Wake Forest Demon Deacons and Michigan State Spartans, winning the Walter
Kaley Christine Cuoco is an American actress. She starred as Bridget Hennessy on the ABC sitcom 8 Simple Rules (2002–2005), Penny on the CBS sitcom The Big Bang Theory (2007–2019), and as the title character in the HBO Max comedic thriller The Flight Attendant
Mariska Magdolna Hargitay is an American actress. She is best known for playing Olivia Benson on NBC's Law & Order: Special Victims Unit since 1999, the longest-running character of all time in an American primetime drama. Her accolades include three Primetime
Joseph Junior Andreou O'Cearuill, commonly known as JJ Gabriel, is an English footballer who plays as a forward for Premier League club Manchester United.
Benjamin Hammond Haggerty, better known by his stage name Macklemore, is an American rapper. A native of Seattle, Washington, he started his career in 2000 as an independent artist releasing: Open Your Eyes (2000), The Language of My World (2005), and The Unpl
Keri Lynn Russell is an American actress. Working mainly in dramatic television since the 1990s, she has received eight nominations for the Critics' Choice Television Award for Best Actress in a Drama Series. She won a Golden Globe Award in 1999 for her lead r
Robert Hearth Kenneth Kraft is an American businessman. He is the chairman and chief executive officer (CEO) of the Kraft Group, a diversified holding company with assets in paper and packaging, sports and entertainment, real estate development, and a private
Sydney Bernice Sweeney is an American actress. She gained early recognition for her roles in Everything Sucks!, The Handmaid's Tale, and Sharp Objects in 2018. She received wider acclaim for her performances in the drama series Euphoria (2019–2026) and the fir
Michael Andrew Fox, known professionally as Michael J. Fox, is a Canadian and American actor and activist. His accolades include five Primetime Emmy Awards, four Golden Globe Awards, two Actor Awards, and a Grammy Award. Fox was also was appointed an Officer o
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
Robert Gordon Mackie was an American fashion designer and costumier, best known for his dressing of numerous entertainment personalities for television, movies, concerts, and live stage shows. He was the costume designer for The Carol Burnett Show during its e
The September 11 attacks, colloquially known as 9/11, were a coordinated series of suicide attacks perpetrated by the Islamic terrorist organization al-Qaeda against the United States in 2001. A total of 19 hijackers commandeered four commercial passenger airl
Joseph Delpesh O'Cearuill is a retired footballer who played as a defender. His previous clubs have included Barnet and St. Patrick's Athletic, and he has been capped by the Republic of Ireland.
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
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 Li
Sally Margaret Field is an American actress. Known for her roles on screen and stage, she has received various accolades including two Academy Awards, two Golden Globe Awards, and four Primetime Emmy Awards, as well as nominations for two British Academy Film
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
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 attempted suicide by cutting her wrists and n
Marvel's Wolverine is a 2026 action-adventure game developed by Insomniac Games and published by Sony Interactive Entertainment. It was released worldwide for the PlayStation 5 on September 15, 2026. Based on the Marvel Comics character Wolverine, it is inspir
Edward Christopher Sheeran is an English singer-songwriter. Born in Halifax, West Yorkshire, and raised in Framlingham, Suffolk, he began writing songs around the age of eleven. In early 2011, Sheeran independently released the extended play No.5 Collaboration
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
Jean Elizabeth Smart is an American actress. Her work includes both comedy and drama, and her accolades include eight Emmy Awards, three Actor Awards and three Golden Globe Awards, with nominations for a Grammy Award and a Tony Award.
The Beast in Me is an American psychological crime thriller television miniseries for Netflix, starring Claire Danes and Matthew Rhys. Created by Gabe Rotter, the series follows an author (Danes) who begins writing a book about her new next-door neighbor (Rhys
General elections were held in Sweden on 13 September 2026 to elect the 349 members of the Riksdag. They in turn will elect the prime minister. Local elections were also held on the same day. The preliminary count on election night indicated that the left-lean
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Objective vs. Search: Decomposing What Makes a Good Tokeniser
Two dominant tokenisation algorithms are used by modern language models: byte-pair encoding (BPE) and UnigramLM. These differ along two orthogonal axes: their optimisation objective (compression vs. log-likelihood) and their search procedure (bottom-up merging vs. top-down pruning). Existing comparisons confound these axes, making it unclear whether their observed differences stem from what is being optimised vs. how
A Zeroth-Order Paradigm for LLM Preference Alignment
Direct preference alignment methods are widely used to align large language models (LLMs) with human preferences because of their computational and memory efficiency. However, likelihood displacement motivates alternative ways to extract information from preference pairs with small likelihood margins. In this paper, we propose and analyze Comparison-based Preference Optimization (ComPO), a zeroth-order alignment meth
Recent advances in video generation allow robots to learn manipulation trajectories from generated videos. However, these approaches produce purely kinematic trajectories that lack force information, causing failures in contact-rich tasks where appropriate contact forces are essential for success. In this work, we explore augmenting generated video with audio to shape a bounded, time-varying desired-force profile usi
Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery from failed steps. We extend SwiftSage, a dual-process agent that combines a fast action proposer with a slower planner, using two modular cognitive extensions: an Adaptive Memory Module (AMM) for salience-gated episodic storage and trigger-driven retrieval, and a Self-R
Affora: A Design System for Agent-Friendly Interfaces
Computer-use agents increasingly operate software designed for people, but interfaces often leave actions or task state unclear to machine readers. We present Affora, a design system that supports both readers while preserving visual freedom and familiar human workflows. Three controlled studies examine component implementations, visual variation, and interaction-design principles. Their findings inform guidance from
Flag Game: A Toy Model for Mechanistic Swarm Interpretability
Emergent coordinated behaviors of AI agents are starting to present critical safety risks. A key phenomenon driving these behaviors is the rapid formation and spread of beliefs about the world, and mechanistic understanding is crucial for collective alignment. To this end, we introduce the Flag Game, a toy model for studying the mechanisms of collective belief formation. Concretely, a hidden country flag defines the
rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured station keeps the jobs tractable for current policies. Vision-Language-Action (VLA) models now dominate as the policy paradigm for these robots. The inference latency of VLA models directly affects robot responsiveness and motion smoothness. However, existing VLA inference
Artificial intelligence (AI) is increasingly integrated into healthcare systems worldwide, yet its successful clinical adoption depends critically on workforce readiness, particularly in low- and middle-income countries (LMICs) where infrastructural and training gaps persist. This cross-sectional study evaluated awareness, attitudes, preparedness, and barriers to AI adoption among 761 healthcare professionals across
Reporting Practice Matters: The Impact of Reference Choice on Chest X-ray Report Evaluation
Radiologists follow heterogeneous reporting practices. Two radiologists examining the same image and identifying the same clinical findings might nevertheless compose superficially distinct reports, varying in terminology, shorthand, formatting, and level of detail. These variations in reporting norms represent an under-appreciated obstacle in efforts to evaluate AI-based radiology report generation (RRG) models, whe
Securing quantum error correction against misleading advice from AI agents
Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity in passive syndrome records that obstructs recovery selection, then show how additional calibration measurements support certified recovery updates under uncertainty and drift. In an odd-distance square toric code with error-free preparation, syndrome measurements, and r
MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education
Large vision-language models have achieved remarkable progress in multi-modal understanding, yet their capabilities in educational settings remain insufficiently evaluated. In AI-assisted language learning, models must interpret artistic imagery, understand its semantic, affective, and cultural content, and reason about visual context to support meaningful interaction. However, existing benchmarks primarily focus on
Probabilistic Linear Explanations
Formal explainability provides mathematically grounded justifications for individual predictions. However, abductive explanations often exceed human cognitive limits by involving too many features, while probabilistic relaxations have remained largely limited to categorical classification. We present a unified framework for probabilistic explainability based on sparse, anchored linear models, applicable to both binar
Double descent is the principle of least action
The test error of a model plotted against its number of parameters $d$ falls, peaks when the model can just fit the training data, and falls again, exhibiting the double descent phenomenon. We explain the phenomenon with statistical mechanics. The training trajectory of a stochastic gradient-based method is a particle wandering over the energy landscape of the training loss at an induced temperature $T$, and a run th
RLLBC-Lib: An Educational Code Library for Reinforcement Learning and Learning-Based Control
Reinforcement learning (RL) is an exciting concept as well as a remarkable success story worth sharing. However, RL builds on rather complex interactions between different objects that play out over several cycles. Such dynamics are often best explained with an easily accessible implementation. We present RLLBC-Lib, a carefully crafted code library with the goal of lowering the entry barrier for students and other le
Social Laws for Multi-agent Coordination in Stochastic Environments
In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous research on social laws for multi-agent systems has primarily focused on deterministic, goal-based settings. This paper extends the concept of social laws to stochastic, reward-based environments, proposing a formalism for defining and verifying their robustness under var
Higher-order pruning of experts in mixture-of-experts language models
Mixture-of-Experts (MoE) language models suffer from large parameter counts, which create a significant memory bottleneck. Expert pruning is the most direct approach for reducing this parameter count, yet existing methods make pruning decisions for each expert independently, and assume experts' contributions are purely additive. In reality, expert usage in MoEs is inherently cooperative. We derive HOPE (Higher-Order
Beyond Outcomes: Dual-View Relational Learning for Efficient Agent Benchmarking
Agent benchmarks are substantially more costly to evaluate than conventional LLM benchmarks. Benchmark compression is therefore a natural solution, yet existing methods primarily model redundancy in task--model final-score distributions, which is important in agentic evaluation. To address this limitation, we analyze large-scale trajectories and identify six complementary process signals that are systematically assoc
ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions
Privacy evaluations of tool-using LLM agents often inspect a designated action, final response, or attacker report. These local proxies can miss unauthorized exposure elsewhere in a multi-step session and lack common ground truth across outlets, reports, and tool paths. We introduce privacy exposure displacement, the mismatch between a local evaluation proxy and target-grounded session exposure, and ASLEval, an autho
When a large vision-language model misclassifies a harmful meme, the failure may reflect missing internal evidence or an inability to route represented evidence to its output. We distinguish these cases in Gemma-3 and Qwen3.5 using sparse autoencoders, role-conditioned probes, causal interventions, and recovery experiments across six harmful content benchmarks, with additional Spanish and Hindi-English code-mixed eva
Taming the Agentic RAN: Stability-Guaranteed Arbitration of Autonomous AI Agents in O-RAN
The O-RAN control plane is becoming agentic: autonomous AI agents, deployed as rApps by different vendors, independently close control loops over shared radio resources. We demonstrate on a live O-RAN system that this independence is unsafe. Two agents with individually correct objectives, one protecting a latency SLA and one maximizing utilization for energy efficiency, jointly drive recurring opposing excursions of
GrainSpeech: Less Context, More Detail for Compact Speech Synthesis
Compact acoustic models face a challenging quality-capacity trade-off. We investigate two factors in this regime: encoder context and Mel-spectrogram supervision. A receptive-field-scaling study shows that expanding self-attention beyond 15 phonemes provides no consistent gains in pitch, energy, or duration prediction. Guided by this finding, we introduce a fixed-receptive-field convolutional encoder that reduces the
An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time. Serving systems decide whether that cache stays, leaves, or comes back by guessing how long the tool will run, from the tool's name, its history, a duration declared before the call, or the engine's own occupancy. We show that no estimate fixed before a call starts can know its duration, and such
Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data
The scaling laws hold that a language model grows more capable with more parameters and more training data, and Mixture-of-Experts (MoE) architectures have ridden these laws to remarkable results, activating only a fraction of an enormous stored parameter bank for each token. That success is built on static pretraining data. A deployed model faces a different world, where much of the data that would make it more usef
Using OCR Heads to Verbalize Image Semantics
How do VLMs map from pixels to semantics? To understand this general question, we focus on a narrow one: studying how VLMs perform optical character recognition (OCR). Across four models, we identify attention heads causally necessary for OCR, and discover that these are in fact general-purpose heads that output interpretable semantic features across all image tokens. For example, pointing these heads at an image tok
Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows
Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-output classifiers, per turn rails, and span-level evaluators. The policies organizations actually hold, such as referral thresholds, authority limits, and review requirements, are properties of the whole execution rather than of any one step. This mismatch admits a fai
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) | 5.4% (54) | 75.45% (83) |
| llms.txt (apex domain) | 9.4% (94) | 4.6% (46) | 60.91% (67) |
| llms.txt (docs subdomain) | 3.8% (38) | 1% (10) | 44.55% (49) |
| .well-known/mcp.json | 0.4% (4) | 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) | 0.5% (5) | 0.1% (1) | 0.91% (1) |
Notable events recorded on this day and month across all years.