Record 06102026 · captured 2026-10-07
The world looked up Christa Pike. 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.
Christa Gail Pike is an American convicted murderer on death row in Tennessee. In 1995, when she was 18, Pike and her boyfriend lured their 19-year-old classmate Colleen Slemmer into a wooded area in Knoxville where they tortured and killed her. Over roughly t
The Wikimedia Foundation, Inc. (WMF) is an American 501(c)(3) nonprofit organization headquartered in San Francisco, California, and registered there as a charitable foundation. It is most known for hosting Wikipedia, one of the world's most visited websites.
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.
Digger is a 2026 American satirical black comedy film directed, co-written, and co-produced by Alejandro González Iñárritu. Tom Cruise, who also produced the film, stars as Digger Rockwell, an aging oil magnate whose drilling sets off an ecological disaster. T
Drishyam: The Conclusion is a 2026 Indian Hindi-language crime thriller film co-written, produced, and directed by Abhishek Pathak. Produced by Panorama Studios and Star Studio18, it is a sequel to Drishyam 2 (2022). Unlike its predecessors, the film features
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
East of Eden is a 1952 family saga novel by American author and Nobel Prize winner John Steinbeck. Many regard the work as Steinbeck's most ambitious novel, and Steinbeck himself considered it his magnum opus. Steinbeck said of East of Eden, "It has everything
East of Eden (2026 miniseries)
East of Eden is a 2026 American historical drama television limited series created by Zoe Kazan, starring Florence Pugh. It is adapted from John Steinbeck's 1952 novel of the same name and premiered on Netflix on October 1, 2026.
Dakota Mayi Johnson is an American actress. Her accolades include nominations for a British Academy Film Award and a Critics' Choice Award. She was featured in the Forbes 30 Under 30 list in 2016.
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
Lizzie Andrew Borden was an American woman who was tried and acquitted of the murders of her father and stepmother in Fall River, Massachusetts. No other individuals were charged with the murders.
Flávio Nantes Bolsonaro is a Brazilian lawyer and far-right politician serving as a senator for Rio de Janeiro since 2019. A son of the 38th president of Brazil, Jair Bolsonaro, he is affiliated with the Liberal Party (PL). He previously served as a state depu
Robert Kelker-Kelly was an American soap opera actor and professional aircraft pilot, known for playing Bo Brady on the NBC soap opera Days of Our Lives from 1992 to 1995. He was also known for his portrayals of Sam Fowler from 1987 to 1990 and Dr. Shane Rober
John Dennis Hastert was an American politician, educator, and felon who served as the 51st speaker of the United States House of Representatives from 1999 to 2007. A member of the Republican Party, he represented Illinois's 14th congressional district from 198
Karl Alexander Deisseroth is an American scientist and physician. He is the D.H. Chen Foundation Professor of Bioengineering and a professor of psychiatry and behavioral sciences at Stanford University. He was jointly awarded the Nobel Prize in Physiology or M
Verity is a 2026 American erotic psychological thriller film directed by Michael Showalter, written by Nick Antosca, and based on Colleen Hoover's novel of the same name. The film stars Anne Hathaway, Dakota Johnson, and Josh Hartnett.
Bryce Christopher Young is an American professional football quarterback for the Carolina Panthers of the National Football League (NFL). He played college football for the Alabama Crimson Tide, where he set the school single-game passing yards record with 559
Theodore John Kaczynski, also known as the Unabomber, was an American mathematician and domestic terrorist. A mathematics prodigy, he abandoned his academic career to pursue a reclusive primitive lifestyle and lone wolf terrorism campaign.
Jeffrey Howard Archer, Baron Archer of Weston-super-Mare, was an English novelist and politician. He was the Member of Parliament (MP) for Louth (Lincolnshire) from 1969 to 1974, but did not seek re-election after almost going bankrupt. Archer revived his fort
Pneumonic plague is a severe lung infection caused by the bacterium Yersinia pestis. Symptoms include fever, headache, shortness of breath, chest pain, coughing, and coughing up blood. They typically start about three to seven days after exposure. It is one of
Jair Messias Bolsonaro is a Brazilian politician and former military officer who served as the 38th president of Brazil from 2019 to 2023. He previously served as a member of the Chamber of Deputies from 1991 to 2019.
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
2024 Cornell University rape allegations
On September 16, 2026, an anonymous former student of Cornell University identified under the pseudonym Jane Doe filed a civil lawsuit against the university, its Chi Phi fraternity chapter, and a group of seven student members of the fraternity among others.
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
Sarah "Sass" Jordan was a British-born, Canadian-raised rock singer. Her first single, "Tell Somebody," from her debut album of the same title, won the Juno Award for Most Promising Female Vocalist in 1989. Based on her 1992 album Racine she was Billboard's to
2026 Port Shuaiba drone attack
On 1 March 2026, an Iranian one-way attack drone struck a tactical operations center belonging to the United States Armed Forces in Port Shuaiba, an industrial port in Kuwait. The operations center was described as a makeshift and relatively unprotected site w
Neatsville is an unincorporated community in Adair County, located 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
.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
Florence Pugh is an English actress. Her accolades include a British Independent Film Award, in addition to nominations for an Academy Award and three BAFTA Awards.
Tetairoa McMillan, nicknamed "T-Mac", is an American professional football wide receiver for the Carolina Panthers of the National Football League (NFL). McMillan played college football for the Arizona Wildcats, earning Polynesian College Football Player of t
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction Reconstruction
Existing methods for 4D hand-object reconstruction often rely on costly per-sequence optimization, while generative approaches typically synthesize interactions from random noise, which can lead to unstable interaction prediction. We introduce 4D-HOF, a feed-forward framework that reconstructs 4D hand-object interactions from coarse but informative estimates produced by vision foundation models. Concretely, we learn
IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas
Scientific research often begins by synthesizing ideas from a set of related papers to identify gaps and formulate new directions. However, training language models to perform this form of literature-grounded ideation remains challenging, as existing approaches based on prompting or feedback lack structured supervision for how papers should be synthesized. We introduce IdeaAnchor, a paradigm for training LLMs to perf
DepthWorld: 3D World Model for Robot Manipulation
World models offer a data-driven alternative to traditional simulators for robotics, with applications spanning policy evaluation, improvement, and planning. All of these uses depend on faithful 3D geometry, yet current video-based world models are trained on RGB alone and produce rollouts that look correct frame-by-frame but do not compose into a consistent 3D world. Closing this gap requires progress on two fronts:
Sherpa: Teaching LLMs to Teach Adaptively
Large language models (LLMs) have become increasingly capable problem solvers, but being able to solve a problem is not the same as being able to teach it. Existing approaches to training LLMs as teachers rely on demonstrations, preference data, or predefined pedagogical criteria that specify what good teaching looks like. However, these signals are often not grounded in individual student learning outcomes, where ef
Agent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?
Large language models (LLMs) can solve many narrow tasks, but querying them separately for millions of related instances can be prohibitively expensive. Can LLM agents autonomously create cheaper solutions for such workloads? We call this ability "bottling": the ability to turn general capabilities into task-specific solutions that balance answer quality and amortised cost. We introduce BOTTLED, a benchmark in which
AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World Model
Web agents complete user requests by reading and acting on pages that third parties write, so an instruction planted on a page can redirect the agent away from the user's goal. The agent cannot simply ignore the page, because the page also holds the values and controls the task requires. Current defenses fine-tune the agent on injections fixed before training, and attackers that adapt to the trained model bypass them
VeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning
Self-improving policies continually expose new failure patterns, changing what their judges must be able to verify. However, current fixed judges constrain both optimization feedback and the discovery of useful training examples, limiting further self-improvement. This challenge is even more acute in embodied reasoning, where reliable evaluation must account for spatial grounding, causal reasoning, and safety-aware d
WorldSonus: Bringing Sound to Worlds
Recent advances in world models have enabled increasingly realistic visual synthesis. However, these generated environments remain largely silent. Bringing sound to world models poses three core challenges: real-time generation to keep pace with interactive video streams, interactive control to respond to mid-stream sound instructions, and spatially aligned stereo to reflect scene geometry and camera motion. To addre
Reinforcement Learning with Conformal Action Sets: An Application to Sequential Recommendation
Sequential recommenders typically use a fixed slate size even though the number of useful alternatives changes within a session. We propose Reinforcement Learning with Calibrated Pruning (RLCP), which adapts the retained action set using critic scores and an online threshold. The threshold is updated from binary feedback indicating whether the set contains an action in a proxy target. We prove a deterministic bound o
EgoLAP: Learning from Egocentric Human Data through Language-Action Reasoning
Egocentric human data offer a path to scaling robot learning beyond costly robot demonstrations, yet the embodiment gap makes raw human trajectories a poor supervisory target for control. Our key insight is that, although low-level actions are embodiment-specific, their underlying motion intent can capture task-relevant structure that transfers across humans and robots. We introduce EgoLAP, a VLA pre-training framewo
Many long-horizon agents compact their context on a global rule, usually a token budget, blind to what the agent was doing. We ask whether the agent's recent behaviour predicts when a compaction will hurt. TRACE's public corpus of 590 harness-triggered AppWorld compaction boundaries replays each boundary from a re-executed prefix state under the pre-compaction context and under the summary, and records the burden of
WorldSolver: Can LLM Agents Simulate the Physical Dynamics via Solver Generation?
LLM-based agents are increasingly advancing scientific and engineering problem solving, with physics simulation emerging as a challenging yet practical testbed for reproducing complex physical phenomena with application in embodied AI, games and films. As the workhorse of such simulation, a solver computes how the state of a dynamic system evolves over time. Building such solvers requires physical understanding to id
nanoMuse: An Open-Source Personal Agent for Every Device You Own
Assistants from 2011 answered and waited, and agents from 2023 did a task and stopped. In September 2026 Meta's Muse showed an agent for one person, with accounts, devices, memory and a conversation that lasts, closed, in a vendor's cloud, in one country. Such an agent is expected to act on a person's accounts and devices, remember them across weeks, speak first when it is worth it, and answer for what it did. It is
Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and existing evaluations do not examine this process across sequential tasks in both the natural and social sciences. We formalize ScienceClaw as fixed-parameter program self-evolution that unifies task solving, scientific verification, and program updates. ScienceClaw-Eval
Coupled but Late: Turn-Taking Between Full-Duplex Speech Models in Unscripted Dialogue
Full-duplex speech models are trained to converse with a person, but they are increasingly made to converse with each other, in self-play data generation, agent societies, and model-based evaluation. In that loop no human absorbs a timing error: each model's turn-taking is the other's input. We ask what timing the loop settles into. Two PersonaPlex-7B instances exchange audio tokens on a shared clock in unscripted co
Secure Speculative Decoding for Large Language Models
Speculative decoding accelerates inference for a large language model (LLM), referred to as the \emph{target model}, by first using a smaller model, referred to as the \emph{draft model}, to generate candidate tokens and then verifying them with the target model for acceptance or rejection. Prior studies primarily focused on the efficiency-utility trade-off of speculative decoding, e.g., lossy speculative decoding, l
Principled Under Pressure: Post-Training Decides Whether LLMs Act on Their Own Moral Judgment
Language models increasingly act as agents. An agent that says an action is wrong and then takes it anyway is a different failure from one that does not know better, and evaluations of stated values cannot see it. We build a pre-registered panel of 248 scenarios across five kinds of pressure. Each scenario is posed twice to the same model, once as the agent choosing what to do and once in the third person asking whic
MemFLoRA: Memory-Floor LoRA for CNN Adaptation at the Edge
On-device learning is necessary when the model encounters user-,sensor-, or environment-specific shifts after deployment. Although parameter-efficient fine-tuning (PEFT) methods, particularly Low-Rank Adaptation (LoRA) variants, enable efficient adaptation at the edge, the limiting resource for Convolutional Neural Network (CNN) adaptation is often not the number of trainable parameters but the activation state that
Semantic Behavioral Watermarking: Paraphrase-Robust and Forgery-Resistant Provenance for LLM Agents
Behavioral watermarking embeds an owner identifier in an LLM agent's high-level action choices, giving provenance without touching output tokens. Prior agent watermarks break in two ways. First, all three prior schemes bind the watermark to the exact action symbol, so renaming a tool desynchronizes decoding even when the observation is untouched; in AgentMark's own robustness test, paraphrasing the observation alone
ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding
As coding agents increasingly undertake real-world work autonomously, judging whether their risk treatments are warranted has become important. Existing work evaluates related agent behaviors from separate perspectives, but lacks a systematic framework for unifying these behaviors. To bridge this gap, we introduce ParanoiaEval, the first benchmark for unified evaluation of risk-treatment capabilities in coding agents
Selective Transfer of RL Updates for Visual Reasoning
Model merging provides a training-free way to transfer reasoning capabilities from language models to vision-language models (VLMs), but endpoint-based transfer can conflate pre-existing model differences with changes acquired during reasoning post-training. We instead formulate capability transfer around the training-stage update, isolating the parameter changes induced by reinforcement learning (RL). Yet transferri
A Case Study in Assuring AI-Written Software
Software-engineering agents can enable people without formal software training to build systems they could not otherwise implement and simultaneously can produce more code than even experts can meaningfully inspect. In both cases, exhaustive code review is not reliable as the sole basis for human control. We report a case study of a production healthcare platform built through coding agents and governed by an operato
SquidAgent: Parallelize Wisely, Coordinate Efficiently
LLM-based agents solve complex multi-step tasks, but sequential execution incurs substantial latency. In principle, parallelizing work across multiple agents should yield near-linear speedups. Yet existing parallel multi-agent systems often run slower than a single-agent baseline. We attribute this gap to two hidden costs that parallel execution incurs but a serial agent avoids. First, there is a re-exploration cost:
HygieneRoboBench: Benchmarking Hygiene-Aware Planning for Household Robots
Contact with contaminated objects can spread hazards through a household robot's grippers, tools, and shared surfaces, while new contacts can make an existing plan unsafe. Existing benchmarks do not jointly assess how planners identify hygiene risks from contact history and plan safe continuations after new contact events. Planners must do so within time and resource limits while respecting user priorities. We introd
Parallel Predictive World Models for Accurate and Efficient Long-Horizon Planning
Long-horizon world-model planning typically relies on autoregressive rollouts, where predicted states are repeatedly fed back into the model. This preserves temporal structure but creates a horizon-length sequential path and exposes later predictions to recursive decoded-state feedback. We introduce Parallel Predictive World Models (PPWM), which predict a finite-horizon trajectory in parallel while retaining causal i
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 | 12.5% (125) | 6.4% (64) | 74.55% (82) |
| llms.txt (apex domain) | 10.2% (102) | 5.5% (55) | 60% (66) |
| llms.txt (docs subdomain) | 4.2% (42) | 1% (10) | 46.36% (51) |
| .well-known/mcp.json | 0.6% (6) | 0.3% (3) | 9.09% (10) |
| .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) | 0.6% (6) | 0.3% (3) | 0.91% (1) |
Notable events recorded on this day and month across all years.