Record 02102026 · captured 2026-10-03
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 Knoxville in 1995, when she was 18, Pike and her boyfriend lured their 19-year-old Job Corps classmate Colleen Slemmer into the woods where they tortured and killed her. In 1996,
USS Theodore Roosevelt (CVN-71)
USS Theodore Roosevelt (CVN-71) is the fourth Nimitz-class, nuclear-powered, aircraft carrier in the United States Navy. She is named in honor of Theodore Roosevelt, the 26th president of the United States and a proponent of naval power. She is the fourth ship
The 2026 Asian Games, officially known as the XX Asian Games or Aichi–Nagoya 2026, is the largest sporting event in Asia governed by Olympic Council of Asia (OCA). They are currently being held from 19 September to 4 October 2026 in Aichi Prefecture and Nagoya
India is participating in the 2026 Asian Games in Aichi Prefecture, Japan from 19 September to 4 October 2026. This is the country's 20th consecutive appearance in the competition, having made its debut at the inaugural 1951 Asian Games. The Indian contingent
2024 Cornell University rape allegations
On September 16, 2026, an unnamed former student of Cornell University, identified under the pseudonym Jane Doe, sued the university and its Chi Phi fraternity chapter, including a group of seven students known as the Cornell 7, alleging that she was drugged a
Sebastian Theodore Kemble Croft is an English actor and singer. He began his career as a child actor on stage before making his television debut as Young Ned Stark in Game of Thrones (2016). He earned a BAFTA Children's Award nomination for his role in Horribl
The 2026 Asian Games , officially the XX Asian Games (第二十回アジア競技大会) and also known as Aichi–Nagoya 2026 (愛知・名古屋2026), is an ongoing multi-sport event being held in Aichi Prefecture in Japan from 19 September to 4 October 2026 though several competitions started
Isabella May Ramsey is an English actor. They are known for their breakthrough roles as young noblewoman Lyanna Mormont in the fantasy television series Game of Thrones (2016–2019) and as Ellie in the post-apocalyptic drama series The Last of Us (2023–present)
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.
Theodore John Kaczynski, also known as the Unabomber, was an American mathematician and domestic terrorist. A mathematics prodigy, he abandoned his academic career in 1969 to pursue a reclusive primitive lifestyle and lone wolf terrorism campaign. Kaczynski mu
Richard E. Grant is a Swazi-English actor and presenter. He made his film debut as Withnail in the comedy Withnail and I (1987). Grant received critical acclaim for his role as Jack Hock in Marielle Heller's drama film Can You Ever Forgive Me? (2018), winning
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
Digger is a 2026 satirical black comedy film directed by Alejandro G. Iñárritu, who co-wrote the screenplay with Sabina Berman, Alexander Dinelaris Jr., and Nicolás Giacobone, from a story by Iñárritu, Berman, and Jez Butterworth.
Flydubai Flight 1073 was a regularly scheduled international passenger flight operated by Flydubai from Dubai International Airport in the United Arab Emirates (UAE) to Ben Gurion Airport near Tel Aviv, Israel. On 30 September 2026, while en route, the Boeing
Aileen Carol Wuornos was an American serial killer. Between 1989 and 1990, while engaging in street prostitution along highways in Florida, Wuornos shot, killed, and robbed seven of her male clients. She initially claimed that her victims had either raped or a
Dame Esther Louise Rantzen was an English journalist and television presenter who presented the BBC television series That's Life! for 21 years, from 1973 until 1994. She worked with various charitable causes and founded the charities Childline, a helpline for
Jerry Faye Hall is an American model and actress. She began modeling in the 1970s and became one of the most sought-after models in the world. She transitioned into acting, appearing in the 1989 film Batman. Hall was the long-term partner of Rolling Stones fro
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
Benjamin Satterley, better known by his ring name Pac, was an English professional wrestler. He was best known for his time in All Elite Wrestling (AEW), where he was a member of the Death Riders and Death Triangle, and WWE, where he previously performed under
Job Corps is a program administered by the United States Department of Labor that offers free education and vocational training to people ages 16 to 24.
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.
Pentobarbital is a short-acting barbiturate typically used as a sedative, a preanesthetic, and to control convulsions in emergencies. It can also be used for short-term treatment of insomnia but has been largely replaced by the benzodiazepine family of drugs.
Jeffrey Preston Bezos is an American businessman, and the founder, executive chairman, and former president and CEO of Amazon, the world's largest e-commerce and cloud computing company. According to the Bloomberg Billionaires Index and Forbes, he was the worl
The 2026 FIFA ASEAN Cup is the inaugural edition of the FIFA ASEAN Cup, an international football competition sanctioned by FIFA for men's national teams of Southeast Asia and guest teams. The tournament takes place during the FIFA international window from 24
Verity is a 2026 American psychological erotic 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.
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
Lethal injection is the practice of injecting one or more drugs into a person for the express purpose of causing death. The main application for this procedure is capital punishment. The drugs cause the person to become unconscious, stop breathing, and develop
Cristiano Ronaldo dos Santos Aveiro is a Portuguese professional footballer who plays as a forward for and captains the Saudi Pro League club Al-Nassr. Nicknamed CR7, he has won numerous individual accolades throughout his career, including five Ballons d'Or,
Charles Davis "Chad" Lowe II is an American actor and director. He is the younger brother of actor Rob Lowe. He won an Emmy Award for his supporting role in Life Goes On as a young man living with HIV. He has had recurring roles on ER, Melrose Place, and Now a
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 cut her wrists and neck and jumped from a sec
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization
Invariance to diverse types of image corruption, such as noise, blurring, or colour shifts, is essential to establish robust models in computer vision. Data augmentation has been the major approach in improving the robustness against common corruptions. However, the samples produced by popular augmentation strategies deviate significantly from the underlying data manifold. As a result, performance is skewed toward ce
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data samples are often decentralized and Non-Independently Identically Distributed (Non-IID), causing divergence and performance degradation in the federated learning process. As a new solution, clustered federated learning groups federated clie
MaPa: Text-driven Photorealistic Material Painting for 3D Shapes
This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural material graphs as the appearance representation, which supports high-quality rendering and provides substantial flexibility in editing. Instead of relying on extensive paired data, i.e., 3D meshes with material graphs and corresponding text d
Exponential time differencing for matrix-valued dynamical systems
Matrix evolution equations occur in many applications, such as dynamical Lyapunov/Sylvester systems or Riccati equations in optimization and stochastic control, machine learning or data assimilation. In many such problems, the dominant stability restriction is imposed by a stiff linear term, making standard explicit integrators impractical. Exponential time differencing (ETD) is known to produce highly stable numeric
Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning
We study a structured class of Markov Decision Processes, known as Exo-MDPs, in which the state space is partitioned into exogenous and endogenous components. Exogenous states evolve stochastically, independent of the agent's actions, while endogenous states evolve deterministically based on both state components and actions. Exo-MDPs capture many operations research settings, including inventory control, resourc
RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic Observations
Anomaly detection is essential for robotic perception and industrial inspection, yet most benchmarks are collected under controlled conditions with fixed viewpoints and stable illumination. These settings do not reflect robotic deployment, where camera pose, lighting, and surface reflectance vary continuously. We present RAD (Realistic Anomaly Detection), a robot-captured multi-view benchmark for pose-agnostic anomal
Linguistic traces of stochastic empathy in language models
Differentiating generated and human-written content is increasingly difficult. We examine how an incentive to convey humanness and task characteristics shape this human vs AI race across five studies. In Study 1-2 (n=530 and n=610) humans and a large language model (LLM) wrote relationship advice or relationship descriptions, either with or without instructions to sound human. New participants (n=428 and n=408) judge
Information propagation dynamics in Deep Graph Networks
Graphs are a highly expressive abstraction for modeling entities and their relations, such as molecular structures, social networks, and traffic networks. Deep Graph Networks (DGNs) have emerged as a family of deep learning models that can effectively process and learn such structured information. However, learning effective information propagation patterns within DGNs remains a critical challenge that heavily influe
Adaptive and oblivious statistical adversaries are equivalent
We resolve a fundamental question about the ability to perform a statistical task, such as learning, when an adversary corrupts the sample. Such adversaries are specified by the types of corruption they can make and their level of knowledge about the sample. The latter distinguishes between sample-adaptive adversaries which know the contents of the sample when choosing the corruption, and sample-oblivious adversaries
Multi-Sensor Fusion for UAV Classification Based on Feature Maps of Image and Radar Data
The cost, flexibility, and efficiency of modern UAVs make them attractive across many applications, but their proliferation has driven a rising number of malicious or accidental incidents, making UAV detection and classification mechanisms essential. Individual sensing modalities each present complementary limitations, and existing detection systems typically rely on a single sensor or fuse modalities only at the dec
CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions
Chord progressions encapsulate important information about music, pertaining to its structure and conveyed emotions. They serve as the backbone of musical composition, and in many cases, they are the sole information required for a musician to play along and follow the music. Despite their importance, chord progressions as a data domain remain underexplored; existing datasets lack the scale, structural annotation, an
Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
Federated learning (FL) is a learning paradigm that enables collaborative training of models using decentralized data. Recently, the utilization of pre-trained weight initialization in FL has been demonstrated to effectively improve model performance. However, the evolving complexity of current pre-trained models, characterized by a substantial increase in parameters, markedly intensifies the challenges associated wi
Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
LLM-based robots use Large Language Models (LLMs) as planners to translate natural language instructions into policies such as grasp(), move_to(), and open_gripper(). Jailbreak attacks on these robots extend the threat from generating malicious content to executing harmful behaviors. However, we find that existing jailbreak attempts against LLM-based robots that produce malicious-looking policies (intent jailbreaks)
Stochastic Optimal Control for Continuous-Time fMRI Representation Learning
Learning robust representations from functional magnetic resonance imaging (fMRI) is fundamentally challenged by the temporal irregularity and noise inherent in data from heterogeneous sources. Existing self-supervised learning (SSL) methods often discard critical temporal information by discretizing or averaging fMRI signals. To address this, we introduce a novel framework that reframes SSL as a Stochastic Optimal C
REVEAL: Robust Evolution of Vision-Language Models for Explainable AI-Video Detection
The rapid advancement of AI-generated video poses challenges to digital authenticity and security. Current detection methods, often trained on specific datasets, struggle with the ever-evolving landscape of generative techniques and unseen manipulations. We introduce a framework leveraging Vision Language Models (VLMs) for robust AI-generated video detection. Our approach equips the VLM with the ability to reason abo
PUMA: Learning a Mutation-Aware Vocabulary of Protein Units
Modeling protein sequences as a language has made language models a powerful tool in computational biology, yet the language itself remains poorly understood. A key step toward understanding it is identifying its constituent units. In natural languages, morphemes can occur in multiple forms; similarly, in proteins, mutations can give rise to variations of a unit that persist through evolution, forming families of rel
Structured-Noise Masked Modeling for Video, Audio and Beyond
Masked modeling has emerged as a robust self-supervised learning framework. However, most methods rely on random masking, which disregards the structural properties of different data modalities. To align with the spatiotemporal and spectral characteristics of video and audio data, we introduce a structured noise-based masking approach. By filtering white noise into different color noise distributions, we generate str
Policy gradient (PG) methods have played an essential role in the empirical successes of reinforcement learning. In order to handle large state-action spaces, PG methods are typically used with function approximation. In this setting, the approximation error in modeling problem-dependent quantities is a key notion for characterizing the global convergence of PG methods. We study Softmax PG with linear function approx
WaLLM -- Understanding Use and Engagement with a General-Purpose LLM on WhatsApp
Large language model (LLM) chatbots are increasingly reaching users through messaging platforms (e.g. WhatsApp). However, these systems remain largely proprietary and opaque, while academic research has focused on narrow, domain-specific assistants. This leaves open questions about how people use general-purpose LLMs and how such systems should be designed. To address this gap, we developed WaLLM, a general-purpose L
Hardening Soft Information: Evidence on Analyst Integration Costs
We examine how the cost of transforming qualitative information into precise numerical estimates--a form of integration cost--creates a structural friction in expectations formation. To isolate this integration cost from the costs of information awareness and acquisition, we exploit sell-side analyst reports, in which the same forecaster simultaneously produces textual narratives and numerical forecasts. Because the
Meta-reinforcement learning with minimum attention
Minimum attention applies the least action principle in changes of control concerning state and time, first proposed by Brockett. The involved regularization is highly relevant in emulating biological control, such as motor learning. We apply minimum attention in reinforcement learning (RL) as part of the rewards and investigate its connection to meta-learning and stabilization. Specifically, model-based meta-learnin
MMMG: a Comprehensive and Reliable Benchmark for Multitask Multimodal Generation
Automatically evaluating multimodal generation presents a significant challenge, as automated metrics often struggle to align with human evaluation, especially for complex tasks that involve multiple modalities. We present MMMG, the first benchmark to bring the verifiable-task paradigm to multimodal generation, spanning 4 modality combinations (image, audio, interleaved text and image, interleaved text and audio). As
We introduce CoLoRA (Convolutional Low-Rank Adaptation), a parameter-efficient fine-tuning method for convolutional neural networks (CNNs). CoLoRA extends LoRA to convolutional layers by decomposing kernel updates into lightweight depthwise and pointwise components. This design reduces the number of trainable convolutional-update parameters by over 80\% compared with full convolutional fine-tuning, while allowing the
Early weed identification is crucial for effective management and control, and researchers, agronomists, and technology developers are increasingly interested in automating this process using computer vision and artificial intelligence; however, limited expert-verified data and variable morphological features have hindered the development of AI-based weed identification models. To address these issues, we present Wee
False discovery rate (FDR) control methods are essential for voxel-wise multiple testing in neuroimaging data analysis, where hundreds of thousands or even millions of tests are conducted to detect brain regions associated with disease-related changes. Classical FDR control methods (e.g., BH, q-value, and LocalFDR) assume independence among tests and often lead to high false non-discovery rates (FNR). Although variou
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 | 11.8% (118) | 5.3% (53) | 74.55% (82) |
| llms.txt (apex domain) | 9.7% (97) | 4.5% (45) | 60% (66) |
| llms.txt (docs subdomain) | 3.9% (39) | 1% (10) | 46.36% (51) |
| .well-known/mcp.json | 0.6% (6) | 0.2% (2) | 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) | 0.6% (6) | 0.2% (2) | 0.91% (1) |
Notable events recorded on this day and month across all years.