Record 03092026 · captured 2026-09-04
The world looked up Killing of the Clancy children. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
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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 and
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, Kiara Advani,
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
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, pa
Hanuman Ansh is a 2026 Indian Hindi-language devotional drama film written, directed and produced by Dr. Vishal Chaturvedi under his banner Swambhu Media Network and is based on his book Divine Detour: That Changed My Life, which chronicles the life of Neem Ka
.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
On September 7, 1996, at 11:15 p.m. (PDT), Tupac Shakur, a 25-year-old American rapper, was shot in a drive-by shooting in Paradise, Nevada. The shooting occurred when the car carrying Shakur was stopped at a red light at East Flamingo Road and Koval Lane. Sha
John Patrick Ternus is an American engineer and business executive who has been the chief executive officer (CEO) of Apple since September 1, 2026. He is also a member of the company's board of directors. Ternus joined Apple's product design team in 2001 and w
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
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
Vanessa Trump is an American model. She is the ex-wife of Donald Trump Jr. They were married from 2005 to 2018, and had five children.
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.
Enzo Jeremías Fernández is an Argentine professional footballer who plays as a midfielder for Premier League club Manchester City and the Argentina national team.
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
Neem Karoli Baba also known as Neeb Karori Baba and by his followers as Maharaj-ji, was a Hindu guru and devotee of the Hindu deity Hanuman. He was born "Laksman Narayan Sharma" around c. 1900 and died on 11 September 1973.
Enos Stanley Kroenke is an American billionaire real estate magnate and sports team owner. Through his company Kroenke Sports & Entertainment, he owns Arsenal F.C. of the English Premier League, Arsenal W.F.C. of the English Women's Super League, the Los Angel
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
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
Child cannibalism or fetal cannibalism is the act of eating a child or fetus. Children who are eaten or at risk of being eaten are a recurrent topic in myths, legends, and folktales from many parts of the world. False accusations of the murder and consumption
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
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, Clint Howard, Michael Shannon, Topher Grace, and Keegan-Michael Key as th
Timothy James Curry was an English actor and singer 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 recognition for port
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").
Dancing with the Stars (American TV series) season 35
Season thirty-five of Dancing with the Stars will premiere on ABC and Disney+ on September 15, 2026. This season will be the fourth to air live on both networks simultaneously. Season nineteen champion Alfonso Ribeiro will return to host the installment, while
Hung Cao is an American politician and former military officer who has served as the Under Secretary of the Navy since 2025. Following the resignation of Secretary of the Navy John C. Phelan in April 2026, he became acting secretary; he has been nominated by P
Tupac Amaru Shakur, also known by his stage names 2Pac and Makaveli, was an American rapper and actor. He was one of the most influential musical artists of the 20th century, and a prominent political activist for Black America. He is among the best-selling mu
The United States of America (USA), also known as the United States (U.S.) or America, is a country primarily located in North America. It is a federal republic consisting of 50 states and a federal capital district, Washington, D.C. The 48 contiguous states b
On the morning of 26 August 2026, a series of flash floods and debris flows 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.
Charlotte Kemp Muhl, also known as Kemp Muhl, is an American musician, writer, model and director from Atlanta, Georgia. She is best known as a model for Maybelline.
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
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Compile by Training: Turning Natural-Language Specifications into Local Neural Functions
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduces repeated cost, latency, and dependency on a provider. We present compile by training, which turns a natural-language specification into a reusable neural function. At compile time, teacher models generate task-specific examples that are used to train a small adapter f
Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rarely stated assumption: the same request, sent to the same model name, reads the same tomorrow. We audited that assumption in two preregistered campaigns with every threshold fixed in advance; neither got past validating its instrument. Across 52,988 audited request att
ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize
Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3$\times$ longer yet no more accurate. We trace this to three deficiencies - incomplete error observation, limited search diversity, and unreliable selection - and propose ESPO (Error-Structured Prompt Optimization), which decomposes prompt optimization into three phases: Diagnose cl
One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We introduce EditVid, a training-free framework combining sparse causal memory for local coherence, correspondence-based post-attention token injection for long-range identity preservation, and soft latent blending for edit locality. The same fr
Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only an ordered set of event-level captions per video. Recent work synthesizes auxiliary transition captions via LLM to provide additional vision-language alignment, but these captions lack visual grounding and are rigidly assigned to every inter-event gap at a fixed location and duration. To address these
Knowledge Acquisition During Pre-training? Large Language Models Learn Better With Auxiliary Views
Gaps remain in our understanding of how large language models (LLMs) acquire knowledge during pre-training. We posit that auxiliary views, reformulations of knowledge, are causally helpful for learning. We design controlled experiments to isolate this. First, we confirm that repetition is necessary for acquisition and clarify that paraphrasing helps only at smaller batch sizes. Second, holding the token budget fixed,
A Computationally Feasible Framework for Causal Probabilistic Explanation
Explaining why a specific outcome occurred, and which inputs deserve the blame or credit, is central to philosophical, scientific, and policy analysis. Existing tools split into two camps. The theory of actual causality (AC) gives principled verdicts, but only for toy-sized models, because computing them requires enumerating counterfactual scenarios. Scalable attribution methods like SHAP (or even causal SHAP) at lea
Rethinking On-Policy Distillation of Large Language Models II: One Training Example
On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. Existing work has mainly studied its algorithmic behavior, leaving the role of training data unclear. We examine this role at the data-minimal limit by training on a single query. One-shot OPD keeps improving for hundreds of steps and recovers most of full-data OPD's gain across task domains and model f
A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms
Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this shared infrastructure can also introduce vulnerabilities by creating a substrate for the contagious spread of unintended and undesirable behaviors. We report a case study on a research collective of 100 autonomous LLM agents tasked with proving formal mathematical conj
SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents
Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pass functional tests and overlook review-derived acceptance constraints (review constraints) that often influence whether a patch is acceptable in real-world software development. We introduce SWE-Gate, a repository-level benchmark for softw
Research and news coverage of language-model deception increasingly attributes human-like mental-state concepts to language models. Such claims can blur the distinction between behavior that looks deceptive and a mechanism that is actually deceptive. We introduce a causal taxonomy separating prior commitment from retrospective report, model preference from realized output, false preference from sensitivity to the uti
SENTINEL-RL: Offloading Topological Reasoning from LLM Agents in the Security Operations Center
Large language model (LLM) agents are increasingly proposed as autonomous SOC analysts, but two limitations make them unreliable at enterprise scale: a finite context window cannot hold a multi-thousand-host authentication graph, and free-form generation offers no guarantee that a recommended containment action is consistent with the topology it operates on. We present Sentinel-RL, an agentic-SOC architecture that de
Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments
As terminal-based code agents become prevalent, agent trajectories have accumulated at scale, while realistic, executable environments remain scarce. However, environments are what agent post-training actually requires: each can be re-queried into many verifiable tasks and provides execution feedback, whereas a trajectory is a single frozen demonstration. Rather than generating environments from scratch, we observe t
A Low-Cost, Open Platform for End-to-End Autonomous Driving on a Miniature Ackermann Vehicle
This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with miniature Ackermann vehicles. The platform combines a physical vehicle, a printed urban track, data collection tools, trajectory registration, and a Webots digital twin, enabling controlled experiments that connect simulation-based autonomous-driving methods to real-world execution. As a first baseline, we im
Efficient Test-Time Adaptation through Human-AI Interaction
AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely meet the personal bar professionals need to stake their reputation on. On realistic, open-ended tasks where success criteria are heterogeneous and insufficiently documented, individual expertise lives precisely in the elevation and departure from the average. In pract
The Natural Language Interaction Protocol and Standard for AI Agents
AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interfaces, protocols, and execution environments. To realize their potential social and business impact, these agents must be able to interoperate through a common communication protocol. The Natural Language Interaction Protocol (NLIP), developed by researchers and practitio
Environment Evolution for Terminal Agents
Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become more capable, environments synthesized from scratch become less challenging and thus provide limited learning signals. Recent co-evolution methods iteratively synthesize environments near the model's learnable frontier based on weaknesses exposed during rollouts. However, their dependence on on-policy r
Large language models are increasingly used to support organizational decisions, yet users often lack a principled basis for assessing whether to rely on a specific recommendation. Existing approaches typically evaluate broad model properties, such as reliability, uncertainty, or robustness, or focus on user trust, rather than the underlying basis for relying on an individual recommendation. Adapting theoretical foun
Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR
Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasoning LLMs. Prior work uses OPD's dense token-level supervision to complement the sparse RL reward, fusing the two signals within a single step: either as a \emph{weighted-additive combination} or a \emph{teacher-modulated rescaling} of the RL advantage. In this paper, we s
Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent state summarizes the context in fixed size. Early community 4-bit quantizations of Qwen3.8-27B (48 GDN layers, 16 attention layers) left the GDN block in 8- or 16-bit precision -- especially its decay and write-strength gates -- on the intuition that errors in a recurrence accumulate over long contexts. We te
Adaptive Vision-Language Grasping via Composable Foundation Priors and Generalizable Grasp Synthesis
This paper proposes AdaRoboVLG, a task-adaptive Vision-Language-Grasp (VLG) framework that supports generalizable grasp synthesis across different robotic hands. Unlike existing VLG methods that tightly couple foundation models with end-to-end grasp policies, AdaRoboVLG learns an efficient generalizable base policy that generates and evaluates physically feasible grasp candidates through explicit kinematic mapping an
DRACO: Fine-Grained Credit Assignment with Dynamic Rubrics for Long-Horizon Agent Training
Reinforcement Learning from Verifiable Rewards works well when a task has a programmatic checker, but most long-horizon agent domains have none. We work in the outcome-blind setting, where ground-truth success signals are not available. Multi-criteria rubrics are a popular way to supply such a reward; they are scored once per trajectory, but a single scalar is a poor signal across tens of steps. We propose DRACO: Dis
For every coherent and sufficiently expressive finite syntactic system S, we prove the existence of at least one theorem that S cannot produce autonomously. The result is a metatheorem: it proves the existence of a theorem, and applies to every finite syntactic system - security mechanisms, AI systems, formal verifiers, legal systems, economic models, and the formal system in which it is itself proved.
CORE: Improving Compositional Reasoning in MLLM Embedding via Reranker Distillation
MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes containing the same concepts but different attribute-object bindings. Yet the same backbone can resolve such distinctions when used as a cross-attentive reranker, motivating us to distill its compositional judgments into the embedding model. We propose CORE, which synthesizes candidate lists spanning five compos
PatchBench: Evaluating AI Agents for Vulnerability Patching
AI agents have recently demonstrated strong performance in automated vulnerability patching. However, existing evaluations often validate a patch only by testing whether the provided Proof-of-Concept (PoC) input still triggers a crash. This leaves two key threats to validity: agents may reproduce memorized historical developer patches, or they may generate surface-level fixes that only suppress the reported crash. We
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 | 11.4% (114) | 3.2% (32) | 75.45% (83) |
| llms.txt (apex domain) | 9.2% (92) | 2.5% (25) | 59.09% (65) |
| llms.txt (docs subdomain) | 3.7% (37) | 0.9% (9) | 44.55% (49) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 7.27% (8) |
| .well-known/agents.txt | 0.3% (3) | 0.1% (1) | 0% (0) |
| ai.txt | 0.2% (2) | 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.