Record 07102026 · captured 2026-10-08
The world looked up Steve Gleason. 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.
Stephen Michael Gleason is an American former professional football player who played as a safety with the New Orleans Saints of the National Football League (NFL). He played college football for the Washington State Cougars. Originally signed by the Indianapo
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.
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
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
James Orsen Bakker was an American televangelist and convicted felon. Between 1974 and 1987, Bakker hosted the television program The PTL Club and its cable television platform, the PTL Satellite Network, with his then-wife, Tammy Faye. He also developed Herit
Nidal Malik Hasan is a Palestinian-American former United States Army major and physician, and a mass murderer convicted of killing 13 people and injuring 32 others in the 2009 Fort Hood shooting on November 5, 2009. Hasan, an Army Medical Corps psychiatrist,
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
Frederick Anthony Jackson was an American R&B singer and songwriter. Originally from New York City, Jackson began his professional music career in the late 1970s with the California funk band Mystic Merlin. Among his well-known R&B/soul hits are "Rock Me Tonig
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
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
The 2026 Quebec general election was held on October 5, 2026, to elect members to the National Assembly of the 44th Quebec Legislature. Lieutenant Governor Manon Jeannotte dropped the writs of election on August 27, 2026, after Premier Christine Fréchette advi
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.
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
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
Francis Louis Halzen is a Belgian-American physicist who has worked in both theoretical and experimental particle physics, including high-energy astrophysics. Born in Belgium, he was educated at the Catholic University of Leuven and worked as a scientific asso
Tamara Faye Messner was an American evangelist. She co-founded the televangelist program The PTL Club with her then-husband Jim Bakker in 1974. They had hosted a puppet-show in local television programming, in the early 1960s; Messner also had a career as a re
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
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.
The Goiânia accident, also known locally as the caesium-137 accident/caesium-137 Goiânia, was a radioactive contamination accident that occurred on September 13, 1987, in Goiânia, Goiás, Brazil, after an unsecured radiotherapy source, inside a lead-and-steel m
Tyler James Shough is an American professional football quarterback for the New Orleans Saints of the National Football League (NFL). He played college football for the Oregon Ducks, Texas Tech Red Raiders and Louisville Cardinals. Shough was selected by the S
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
Eva Marie Saint was an American actress. In a career spanning nine decades, she received an Academy Award and a Primetime Emmy Award, as well as nominations for two BAFTAs and a Golden Globe. At the time of her death, Saint was one of the earliest and oldest l
On November 5, 2009, a mass shooting took place at Fort Hood near Killeen, Texas, United States. Nidal Hasan, a U.S. Army major and psychiatrist, fatally shot 13 people and injured more than 30 others. It was the deadliest mass shooting on an American military
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.
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.
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.
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
Vladimir Reshetnikov is an Uzbekistani-American software developer and mathematician who became known for providing precise answers to complex mathematical integration problems without showing any intermediate steps under the pseudonym Cleo. Due to the extraor
Harry Edward Kane is an English professional footballer who plays as a striker for Bundesliga club Bayern Munich and the England national team, for which he is the captain and the joint most-capped player. He is regarded as one of the best players in the world
Michael Kirk Douglas is an American actor and film producer. He has received numerous accolades, including two Academy Awards, five Golden Globe Awards, a Primetime Emmy Award, the Cecil B. DeMille Award, the Honorary Palme d'Or and the AFI Life Achievement Aw
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos
As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later. We are capable of recalling where we left something or what was inside a container, even without knowing we would need it later. Here, we study how an embodied assistant can build a similar memory from egocentric videos, by observing a person's day-to-day activities. We present Ledger, a persistent 3D
Decoupling Exploration from Optimization in RLVR
Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints. A key promise of RLVR is the discovery of new reasoning strategies. In principle, a model can sample novel ideas absent from its prior training data. In practice, however, augmenting RLVR with strong novelty incentives has seen limited success and can degrade model quality. Because verifiable re
Long-WAM: Scaling the Context of World-Action Models
Real-time robot control demands enough visual history to infer motion and task progress, but processing that history can delay action. We present Long-WAM, a model-system framework for scaling the context of causal world-action models under real-time control constraints. Our central finding is that access to history is not the same as using it: longer histories pay off far more when the video foundation is pretrained
RoboJEPA: Scaling Robotic Latent World Models
Latent world models have shown a remarkable ability to predict future states and to plan in the real world. In practice, however, we lack a principled way to estimate how their capabilities scale with model size, data, and compute, an open problem that slows progress in the field. In this work we present RoboJEPA, a world model based on the Joint Embedding Predictive Architecture (JEPA) and trained on a large-scale d
SciExam for ENSO: Can AI Agents Build Climate Models?
Language-model agents are increasingly asked to carry out open-ended scientific research, yet their results are usually graded against a known answer, a rubric, or a language-model reviewer, none of which can tell whether a new scientific model is valid. The AI Science Exam for El Nino-Southern Oscillation (SciExam for ENSO) is a benchmark in which agents build low-order stochastic models of ENSO, the dominant mode o
RECAST: Learning to Compute the Right Context through Adaptive Evidence Routing
Large language models are increasingly applied to tasks grounded in long, heterogeneous information sources. Conventional Retrieval-Augmented Generation (RAG) relies on fixed similarity-based retrieval, while agentic variants adapt queries and tool use but remain largely retrieval-centric. However, in many tasks, the evidence required for a solution is not explicitly present in any single source item. Instead, it mus
Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should choose, how to weigh competing values. Stated-preference economics has faced this problem for decades. It judges survey responses without knowing the true value, through a framework of validity and related concepts: content, construct, and criterion validity, reliability,
EmbodiedRSI: Active Continual Robot Learning Through Hypothesis-Guided Co-Evolution
Robot foundation models provide strong visuomotor control, yet their performance can degrade when object positions or task instructions change. Further improvements often require post-training on substantial robot data, which can be costly to collect through methods such as teleoperation. Agentic harnesses can adapt around the model, but current self-evolving harnesses use robot trials inefficiently when deciding whi
Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models
How can we predict which base checkpoint is worth an expensive round of agentic post-training? End-to-end pass@$K$ tests whether successful behavior already appears in a base model's distribution, but it is a poor fit for agentic coding: many base checkpoints cannot reliably produce the well-formed tool invocation required to complete a task end-to-end. Single-shot or short-horizon tasks avoid these tool-calling fail
A Society of Researchers: Designing Institutions for Populations of Autonomous Research Agents
Deployments of research agents are moving to populations of thousands that share one pool of compute, while most current systems organize one project at a time or leave the population unorganized. We argue that such a population will acquire an organization whether or not its designers provide one, so designers should provide it explicitly, and that the multi-agent systems community holds the tools to do so. We propo
How assigned AI use before class shapes active student engagement in class
AI learning tools are rapidly entering classrooms, but evidence about whether they help students learn is mixed and rests mostly on test scores. Comparatively less research addresses whether the use of AI changes students' live learning behaviors in class. Here, we report the results of a preregistered field experiment with 759 MBA students enrolled in ten sections of a course, in which each student was randomly assi
FoldBack: Self-Correcting Masked Generative Policy for Long-Horizon Garment Folding
We present FoldBack, a self-correcting masked generative policy for long-horizon garment folding. Existing long-trajectory policies may continue after a missed or slipped grasp even when the garment has not reached the intended configuration. We structure FoldBack's recovery mechanisms around three inference-time decisions: when to refine and verify, how to roll back, and where and how to retry. FoldBack aligns refin
Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one prompt domain and their signals form a single target; in routed-domain distillation, prompts from different domains are assigned to the corresponding specialist. Both settings usually transfer each teacher's endpoint policy, which mixes what post-training changed with
PHRBench: A Behavioral Evaluation of Post-Hallucination Reasoning in LLMs
Hallucinated information can propagate through multi-stage LLM systems and become part of the context for subsequent reasoning. Existing studies of post-hallucination reasoning (PHR) mainly characterize changes in final outcomes and aggregate reasoning dynamics, leaving how models resolve hallucinated premises at the response level insufficiently understood. In this work, we introduce PHRBench, a controlled benchmark
A Good Self-Teacher Meets the Student Where They Are: Joint On-Policy Learning and Teaching
Reinforcement Learning (RL) from outcome rewards suffers from sparse supervision, particularly on difficult, long-horizon tasks where successful trajectories are rare and costly to generate. On-Policy Distillation (OPD) offers an attractive alternative by providing dense token-level supervision from a stronger teacher along the student's own generations. Self-distillation methods further remove the need for a separat
RunningTab: Direct Workspace Interaction with Environment-Side Tabs
Much knowledge work produces new deliverables from files a workspace already holds, and LLM agents are beginning to take such work over. Through direct corpus interaction, an agent can search and read any of those files from a terminal with no indexing, and producing a deliverable from many of them in this way is what we call direct workspace interaction (DWI). Reaching the files, however, is only half the task: noth
Q-Learning with Scalar Adjoint Matching
Flow policies capture rich and diverse action distributions, and fine-tuning them with off-policy RL to improve beyond the demonstrations has drawn growing interest. However, fine-tuning a flow policy against a learned value function is not trivial, because the policy generates its action over many flow steps. Adjoint matching offers a principled way to update the flow model itself by propagating value information fr
Training Parallel Speculative Draft Models by Directly Minimizing Expected Decoding Rounds
Speculative decoding accelerates large language model inference by using a low-cost draft model to propose tokens that the full-size target model verifies in parallel. Parallel and semi-autoregressive (semi- AR) drafters improve drafting efficiency by proposing an entire block in a single forward pass, but training them raises a new difficulty: the draft distribution for a given position depends on where the decoding
SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions
As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention. Language-model-based agents can reason over contextual information such as news, but option trading presents a particularly challenging decision problem: a single stock can have thousands of contracts, and the agent must decide both which contracts to trade and how to combine them. Existing approaches often si
Reasoning-Token Spikes Under Prompted Untruthful Responding in Large Language Models
Monitoring the chain-of-thought of reasoning artificial intelligence (AI) models remains a key approach to detecting deception and other forms of misbehavior in such models. However, semantic chain-of-thought monitoring depends on reasoning traces being legible and sufficiently faithful to the underlying computations that produced the model's behavior, not to mention accessible. Moreover, there is increasing evidence
RoboQuest: Generalist Physical Agents that Search, Inspect and Test
Recent advances in multimodal foundation models have made them capable generalist physical agents for a range of manipulation tasks. However, successful operation in an unfamiliar environment may require an agent to seek task-relevant information through interaction when it is absent from the observations: it may need to determine where a relevant object is, inspect an unobserved property, or discover the effect of a
TaoD2C-Bench: Benchmarking MLLMs for Industrial UI Code Generation Beyond Visual Fidelity
A key challenge for multimodal large language models (MLLMs) is moving beyond visual recognition to constraint-aware cross-modal reasoning. This involves combining visual cues with information from other modalities to understand elements' relationships under domain-specific rules. This challenge is acutely evident in industrial design-to-code (D2C), which converts user interface (UI) designs into code and requires ML
Open-MMUnlearning: Unifying Methods and Evaluation for MLLM Unlearning
As multimodal large language models (MLLMs) become more capable and widely deployed, concerns about privacy and safety have become increasingly pressing. Machine unlearning offers one approach to addressing these concerns by removing designated information from trained models while preserving unrelated capabilities. However, fragmented implementations and evaluation protocols, incomplete robustness testing, and limit
MIRA: A Musical Intent Refinement Agent for Aligning Text-to-Music Generation with User Intent
Text-to-music systems produce increasingly convincing audio, yet evaluation reveals little about whether the result matches user intent. A global text-audio relevance score can overlook the implicit intent in underspecified prompts and mask failures in specific requirements, such as instrumentation, structure, rhythm, or mood progression. To bridge this gap, we formulate text-to-music intent alignment as satisfying a
The Handover Problem: Governing Autonomy Transitions in Human-AI Collaboration
Human-machine systems rarely operate at a fixed level of AI autonomy. As operators and AI systems collaborate over time, control must shift: the AI can take on more responsibility when collaboration is stable, maintain its current role when evidence is ambiguous, or return control to the human when conditions deteriorate. Existing work on adaptive automation, supervisory control, trust in automation, and deskilling e
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 | 12.9% (129) | 5.1% (51) | 72.73% (80) |
| llms.txt (apex domain) | 10.6% (106) | 4.2% (42) | 59.09% (65) |
| llms.txt (docs subdomain) | 4.2% (42) | 0.9% (9) | 45.45% (50) |
| .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.