Record 31082026 · captured 2026-09-01
The world looked up Toxic (2026 film). 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.
Toxic: A Fairy Tale for Grown-Ups is a 2026 Indian psychological thriller gangster film directed by Geetu Mohandas and jointly produced by Venkat K. Narayana and Yash through KVN Productions and Monster Mind Creations respectively. It stars Yash in the lead ro
Dolly Rebecca Parton Dean was an American singer-songwriter, actress and businesswoman. Dubbed the "Queen of Country", Parton was one of the most successful country music performers in history. She was also known for her cultural influence and philanthropy via
The 2026 All In, also promoted as All In: London, was a professional wrestling pay-per-view (PPV) event produced by the American company All Elite Wrestling (AEW). It was AEW's fourth annual All In, and the fifth overall. The event took place on August 30, 202
Killing of the Clancy children
On January 24, 2023, Lindsay Clancy 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 neck an
The Whisper Man is a 2026 American crime thriller film directed by James Ashcroft and written by Ben Jacoby and Chase Palmer. It is based on the novel of the same name by Alex North and stars Robert De Niro, Michelle Monaghan, and Adam Scott. The film's plot f
Timothy James Curry was an English actor, singer and comedian who amassed more than 240 credits on screen and stage in a career which spanned nearly 60 years. Curry made his acting debut in the West End production of Hair (1968–1969) and gained wide recognitio
Spider-Man: Brand New Day is a 2026 American superhero film based on the Marvel Comics character Spider-Man. Produced by Columbia Pictures, Marvel Studios, and Pascal Pictures, and distributed by Sony Pictures Releasing, it is the 38th film in the Marvel Cinem
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
Lake Ontario is one of the five Great Lakes of North America. It is bounded on the north, west, and southwest by the Canadian province of Ontario, and on the south and east by the U.S. state of New York. The Canada–United States border spans the centre of the
Coyote vs. Acme is a 2026 American live-action animated legal comedy film directed by Dave Green and written by Samy Burch, who developed the story with James Gunn and Jeremy Slater. Based on the 1990 The New Yorker magazine article "Coyote v. Acme" by Ian Fra
The Odyssey is a 2026 epic action fantasy film written and directed by Christopher Nolan, who produced it with his wife Emma Thomas. An adaptation of Homer's ancient Greek epic poem the Odyssey, it stars an ensemble cast including Matt Damon, Tom Holland, Anne
2026 Icelandic European Union membership negotiations referendum
A referendum on the resumption of European Union membership negotiations was held in Iceland on 29 August 2026. Its result was to reject the proposal for resuming accession negotiations. Iceland applied to join the EU in 2009, but negotiations have been suspen
Filip Hrgović is a Croatian professional boxer. He has held the International Boxing Federation (IBF) heavyweight title since August 2026. As an amateur, he won the gold medal at the 2015 European Championships and a bronze at the 2016 Olympics.
Enriko Moses Itauma is a British professional boxer. He has challenged once for the IBF heavyweight title in August 2026. At regional level, he has held the Commonwealth heavyweight title since 2025.
On the morning of 26 August 2026, a series of flash floods destroyed the Gyirong checkpoint on the China–Nepal border and struck dozens of settlements along a 72 km (45 mi) stretch of the Trishuli River in Nepal.
Buddy is a 2026 American black comedy supernatural horror film directed by Casper Kelly and written by Kelly and Jamie King. The film stars Cristin Milioti, Delaney Quinn, Patton Oswalt, Michael Shannon, Topher Grace, and Keegan-Michael Key as the voice of the
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
Harald V was King of Norway from 1991 until his death in 2026.
List of highest-grossing films
Films generate income from several revenue streams, including theatrical exhibition, home video, television broadcast rights, and merchandising. However, theatrical box-office earnings are the primary metric for trade publications in assessing the success of a
Hanuman Ansh is a 2026 Hindi-language devotional drama film, written and directed by Vishal Chaturvedi. Based on the life of Neem Karoli Baba, popularly known as Maharaj-ji. Hanuman Ansh is produced by Swambhu Media Network Pvt. Ltd., Ragini S., Namrata G. S.,
Umar Magomednabiyevich Nurmagomedov is a Russian professional mixed martial artist. He currently competes in the Bantamweight division of the Ultimate Fighting Championship (UFC). Nurmagomedov has previously competed in the Eagle Fighting Championship (EFC) an
Damián Emiliano Martínez Romero, also known as Dibu Martínez, is an Argentine professional footballer who plays as a goalkeeper for Premier League club Chelsea and the Argentina national team. Known as a specialist in saving penalty kicks, he is often regarded
Gabriel Fernando de Jesus is a Brazilian professional footballer who plays as a forward for Premier League side Arsenal.
Haakon VIII is King of Norway, reigning since the death of his father, Harald V, on 28 August 2026.
The 2026 Heatwave was a professional wrestling television special and livestreaming event produced by WWE, held exclusively for wrestlers from the promotion's developmental brand, NXT. It was the fifth annual Heatwave produced by WWE for NXT and the 13th Heatw
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
The Dog Stars is a 2026 post apocalyptic science fiction action thriller film directed by Ridley Scott from a screenplay by Mark L. Smith, based on the 2012 novel by Peter Heller. The film stars Jacob Elordi, Josh Brolin, Margaret Qualley, and Guy Pearce, and
Michael Joseph Jackson was an American singer, songwriter, dancer, and philanthropist. Dubbed the "King of Pop", he is widely regarded as one of the most culturally significant figures of the 20th century. His musical achievements broke American racial barrier
Nancy Grace Roman Space Telescope
The Nancy Grace Roman Space Telescope (shortened as the Roman Space Telescope, Roman, NGRST, or RST) is a NASA infrared space telescope that was launched on a trajectory toward a Sun–Earth L2 orbit on 30 August 2026 by a Falcon Heavy launch vehicle. It is name
Bethlehem Kudumba Unit is a 2026 Indian Malayalam-language romantic comedy film starring Nivin Pauly and Mamitha Baiju in the lead roles, directed by Girish A. D. and produced by Bhavana Studios, Fahadh Faasil, Dileesh Pothan and Syam Pushkaran.
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
SUN: Persistent Programs For Language-Grounded Control-to-Learning-to-Real Policies
Bridging model-based control and learned policies in long-horizon manipulation has harbored a silent disagreement: control executes specified objectives, learning amortizes that behavior into a reactive policy, yet existing protocols discard task semantics, leaving rewards hand-crafted and behavior drifting from what control verified.We introduce Semantically UNified (SUN) Programs, typed executables where geometric
Auditing Anonymous AI Models: A Four-Stage Protocol for Black-Box Identity Verification
The 2025--2026 AI market has seen a wave of stealth releases: frontier models launched anonymously on developer platforms under codenames. For their users, identity determines data-handling terms, supply-chain risk, and capability expectations. No validated methodology exists for black-box identity verification of anonymous models: practitioner checklists lack accuracy evidence, and self-identification is untrustwort
OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques
Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding (KGE) models and, more recently, Large Language Model (LLM)-based approaches. Although modern OA frameworks provide unified ecosystems for deploying these heterogeneous aligners, mechanisms for systematically reconciling their complementary and sometimes conflicting p
When Does Bigger Help? A Controlled Study of LLM Scale for Ontology Learning
The effect of Large Language Model (LLM) scale on ontology learning (OL) performance remains insufficiently characterized. We present a controlled evaluation of 13 models spanning dense and Mixture-of-Experts variants from the Qwen3.5 and Qwen3.6 lineages, together with proprietary GPT release variants, using the OntoLearner retrieval-augmented generation pipeline. All models are evaluated with the same embedding mod
BLOOM-WILT: Logit Tilting for Behaviour Elicitation in Automated LLM Auditing
Users of a deployed language model routinely encounter behaviours that testing almost never surfaces, since deployment puts the model through orders of magnitude more interactions than any evaluation can simulate. Automated auditors make testing cheap to scale and flexible enough to cover almost any specified behaviour, yet their lack of optimisation pressure makes them sample-inefficient. To address this shortcoming
LLM Post-Training as Brownfield Maintenance: An Industrial Perspective on Dataware Engineering
Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixture budgets without regressing the rest. The maintained artifact is increasingly dataware: behavior governed by a curated post-training mixture, updated via bounded mixture patches rather than clean-slate retraining. From an industrial code-generation improvement effort,
Cross-Regional Grapevine Cold Hardiness Prediction via Learned Multimodal Latent Representations
Accurate daily predictions of cold hardiness in woody plants are critical in regions where freezing temperatures can damage dormant buds and reduce seasonal yield. Existing biophysical, hybrid, and deep learning models have shown high predictive accuracy when trained on local data but remain largely site-specific. The limited availability of cold hardiness data, coupled with the lack of principled methods for transfe
Token-Efficient Data Reasoning Agents via Adaptive Structuring of Unstructured Data
Valuable data remains embedded in unstructured sources: web pages, reports, contracts, filings, earnings calls, and PDFs. The big bet in enterprise AI is deploying LLM agents that reason over this data to answer complex questions for every knowledge worker. Agents can do this today, but at prohibitive cost. Each question repeatedly opens large documents to recover scattered evidence, consuming up to a million tokens.
Reconciling Process Supervision with Outcome-Based Credit in Agentic Policy Optimization
Outcome-based reinforcement learning provides verified feedback for language-model agents, but assigns trajectory-level advantage uniformly to all decisions, yielding coarse credit over long-horizon interactions. On-policy self-distillation offers finer supervision by re-evaluating sampled behavior with privileged information (PI) available only during training. However, fine-grained supervision is not necessarily fi
Learning to Evaluate Before Improving: Automatic Rubric Induction for Automatic Research Agents
Autonomous scientific research agents are increasingly applied to end-to-end scientific workflows, including literature review, data analysis, experimentation, and report generation. However, open-ended research tasks often do not clearly specify the analyses, methods, and success criteria required to complete the task. As a result, agents may miss important analyses, use inappropriate methods, or draw conclusions th
Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence
Recent advances in large reasoning models (LRMs) have shown that reinforcement learning with verifiable rewards (RLVR) can substantially improve reasoning in mathematics and code, where outcomes can be checked automatically. Extending this progress to open-ended and agentic tasks remains difficult because reliable rewards are harder to obtain and direct human supervision cannot keep pace with the scale and complexity
Real-Time Video Anomaly Detection Using YOLO Pose Estimation and CLIP-Based Semantic Scoring
We propose a lightweight two-stage framework for real-time video anomaly detection. The first stage employs YOLO v11n-pose to detect persons and extract seventeen skeletal keypoints in a single forward pass. The second stage encodes each cropped person region through CLIP ViT-B/32 and computes cosine similarity against predefined textual descriptions of anomalous behaviors. This architecture eliminates the need for o
Wrong Prediction, Right Answer: Recovering Evidence from Collapsed LLM Sequence Scores
When a large language model fails a reasoning task, it is often assumed to lack the underlying capability. However, this conflates a genuine absence of reasoning with a late-stage output bottleneck. We observe a consistent readout gap across diverse reasoning benchmarks: hidden-state probes successfully decode correct answers even when native sequence scoring completely collapses due to structural biases. To test whe
Measure Before You Manage: Evaluating Agent Working Memory in Coding Agents
Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated state play different semantic roles and exhibit different size, retention, and representation profiles. Recent work has begun to explore memory-management mechanisms that account for such heterogeneity. This work focuses on semantic heterogeneity and studies how it should shape the management and evaluati
MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
AI agents in partially observable environments need to coordinate active sensing with working memory to maintain an evolving perceptual state. However, existing benchmarks struggle to isolate this perceptual-state construction and interpretation capability because they introduce physical and control complexities. We address this with MNIST-PRO, a benchmark that isolates agentic perception by converting MNIST digit re
Ambient AI scribes draft clinical notes under the reassurance that a clinician signs every note. We audited three commercial AI scribes on the same 142 consultations: 565 notes from recorded UK primary-care and US ambulatory encounters plus authored scenarios. Twelve discovery passes proposed 13,678 candidate errors; the 5,898 clearing an importance filter went to an adversarial panel of two models from different fam
Ambient AI scribes draft clinical notes, and published audits find their dominant error is omission: information the encounter established that the note fails to record. The standard check is an LLM judge: a second model reads the note against the transcript and flags problems. We ask whether judges detect omissions. Public corpora cannot supply the answer key: their clinician reference notes and transcripts are mate
Stick to What You Know: A Study of Knowledge-Aligned Supervised Fine-Tuning
Supervised fine-tuning (SFT) trains a base language model to imitate target responses, and these targets may require knowledge the base model has not robustly internalized. We study this as a source of hallucinations and frame a group of mitigation methods as \emph{knowledge-aligned SFT}: constraining SFT training targets to the base model's parametric knowledge. Under a unified setup, we compare existing generation-
Evaluating and Improving LLM Self-Modeling
We study self-modeling: an LLM's ability to answer questions about its own behavior. We focus on verifiable behavioral questions, such as whether a prompt edit would change the model's final answer. To measure this capability, we introduce a benchmark that tests diverse types of self-modeling questions. Current models show non-trivial but limited self-modeling skill, and make systematic mistakes on simple counterfact
MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI
Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep learning approaches process individual 2D slices, discarding this context. We present MR-JEPA, a self-supervised video foundation model for CMR that extends LeJEPA to 3D spatiotemporal inputs through tubelet tokenization, spatiotemporal masking augmentation, and initializat
CoJEPA: Combining Contrastive Learning and JEPA for Global-Local Music Representations
Joint-Embedding Predictive Architecture (JEPA) has shown strong performance in learning rich representations through self-supervised prediction in latent space. However, it typically relies on teacher--student architecture with an EMA to stabilise training, and can tend to yield uninformative representations. Contrastive learning is stable to train and produces strong global representations, but remains limited on lo
CogEvol: Towards Efficient and Reliable Learning Environment Generation
We present CogEvol, a family of models trained specifically for Learning Environment Generation: turning a course brief into a finished learning artifact (structured-JSON slides or self-contained interactive HTML pages) in a single pass. Across 220k production requests, CogEvol completes a slide in a median of 17 seconds and an interactive page in 59, replacing minutes-long multi-turn agent scaffolding. Reliability i
A Universal Context-Reuse Layer for Cross-Model KV Sharing
Modern large language model (LLM) serving systems increasingly operate over repeated or shared context, yet each model typically performs its own prefill computation even when another model has already processed the same input. Existing KV-cache reuse mechanisms substantially reduce redundant computation within a single model, but generally assume that the producer and consumer of a cache are identical. We study \emp
LOCI: A Locator-Critic with Refinement Loop
Vision-Language Models (VLMs) still struggle on tasks requiring complex visual understanding. We argue that the core issue is not high-level reasoning, but instead failing to locate critical details in the image. Due to this shortcoming, VLMs generate often plausible but incorrect reasoning based on flawed perceptual grounding. To address this, we propose Locator-Critic (LOCI), a training-free framework that decouple
Taking the Whys Seriously: Limitations of Counterfactual Explanations in Justification and Recourse
Counterfactual explanations (CEs) are widely used in explainable artificial intelligence (AI) to show how a model's outputs would change if the input features were manipulated. This technique is used for a range of tasks such as debugging models, explaining predictions, justifying decisions, and providing algorithmic recourse. In this paper, we explore the normative legitimacy of employing counterfactuals in real-lif
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 | 11.2% (112) | 4.4% (44) | 75.45% (83) |
| llms.txt (apex domain) | 8.7% (87) | 3.5% (35) | 59.09% (65) |
| llms.txt (docs subdomain) | 3.5% (35) | 0.9% (9) | 43.64% (48) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 7.27% (8) |
| .well-known/agents.txt | 0.2% (2) | 0.1% (1) | 0% (0) |
| ai.txt | 0.1% (1) | 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.