Record 09112025 · captured 2026-08-25
The world looked up Zohran Mamdani. 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.
Zohran Kwame Mamdani is an American politician who has served since 2026 as the 112th mayor of New York City. A member of the Democratic Party and the Democratic Socialists of America, he represented the 36th district in the New York State Assembly from 2021 t
Frankenstein is a 2025 American Gothic science fiction horror film written, co-produced, and directed by Guillermo del Toro, based on the 1818 novel by Mary Shelley. The film stars Oscar Isaac as Victor Frankenstein and Jacob Elordi as the Creature, with Mia G
Pluribus is an American post-apocalyptic science fiction television series created by Vince Gilligan for Apple TV. Set and filmed primarily in Albuquerque, New Mexico, the series follows novelist Carol Sturka, who finds herself isolated after an alien virus tr
Google Chrome is a cross-platform web browser developed by Google. It was launched in September 2008 for Microsoft Windows and was built with free software components from Apple WebKit and Mozilla Firefox. Versions for Linux, macOS, iOS, iPadOS, and Android we
James Abram Garfield was the 20th president of the United States, serving from March 1881 until his death in September that year after being shot in July. A preacher, lawyer, and Civil War general, Garfield served nine terms in the United States House of Repre
Predator: Badlands is a 2025 American science fiction action film directed by Dan Trachtenberg and written by Patrick Aison from a story by Trachtenberg and Aison. It is the seventh installment in the Predator franchise and set after the events of The Predator
Rama Sawaf Duwaji is an American animator, illustrator, and ceramist. As the wife of Mayor Zohran Mamdani, she has been the first lady of New York City since January 2026.
James Dewey Watson was an American molecular biologist, geneticist, and zoologist. In 1953, he and Francis Crick co-authored an academic paper in Nature proposing the double helix structure of the DNA molecule, building on research by Rosalind Franklin and Ray
Jacob Nathaniel Elordi is an Australian actor. His accolades include a Critics' Choice Award and three AACTA Awards, in addition to nominations for an Academy Award, three British Academy Film Awards and two Golden Globe Awards.
Mira Nair is an Indian American filmmaker. She has received two prizes from the Cannes Film Festival and four from the Venice Film Festival, as well as nominations for an Academy Award, two BAFTA Awards, a Golden Globe, and two César Awards.
Fuck is a profanity in the English language. It often refers to the act of sexual intercourse, but it is most commonly used as an intensifier or to convey disdain. While its origin is obscure, it is usually considered to be first attested to around 1475. In mo
Frankenstein; or, The Modern Prometheus is an 1818 Gothic novel written by English author Mary Shelley. Frankenstein tells the story of Victor Frankenstein, a young scientist who creates a sapient creature from different body parts in an unorthodox scientific
This is a list of lists of deaths of significant people, organized by year. New deaths articles are added to their respective month and then linked below.
Quentin Mcdonald Willson was an English television presenter and producer, motoring journalist, author and car dealer. He was best known as a presenter of the popular television motoring programmes Top Gear, Britain's Worst Driver and Fifth Gear.
Chester Alan Arthur was the 21st president of the United States, serving from 1881 to 1885. A Republican from New York, he served as the 20th vice president under President James A. Garfield in 1881, assuming the presidency after Garfield's assassination. Arth
Hannah Waddingham is an English actress, singer, and television presenter. She is known for roles on both stage and screen, and has received several accolades including a Primetime Emmy Award, two Critics' Choice Television Awards and a Screen Actors Guild Awa
1xBet is an online gambling company founded in 2007 and licensed by Curaçao eGaming License. 1xBet is one of the largest online casinos in the world. According to Forbes, its turnover exceeded $2 billion in 2020. The company sponsors major professional footbal
Charles Julius Guiteau was an American office seeker who assassinated the 20th President of the United States, James A. Garfield, in 1881. A failed lawyer suffering from mental illness, Guiteau delusionally believed he had played a major role in Garfield's ele
Mahmood Mamdani is a Ugandan anthropologist, academic, and political commentator. He is the Herbert Lehman Professor of Government and a professor of anthropology, political science, and African studies at Columbia University. He also served as the chancellor
Edward Theodore Gein, also known as the Butcher of Plainfield and the Plainfield Ghoul, was an American murderer and body snatcher. His crimes, committed around his hometown of Plainfield, Wisconsin, gathered widespread notoriety in 1957 after authorities disc
Jaafar Jeremiah Jackson is an American actor and singer. A member of the Jackson family, he released his debut single "Got Me Singing" in 2019 but gained popularity for portraying his uncle Michael Jackson in the record-breaking biographical film Michael (2026
6-7 was an Internet meme, slang term, and gesture that became popular in 2025 on TikTok and Instagram Reels. It has no fixed meaning.
Mia Gypsy Mello da Silva Goth is a British actress and model. After modelling as a teenager, Goth made her acting debut in the erotic drama Nymphomaniac (2013). She earned recognition with the films A Cure for Wellness (2016), High Life (2018), Suspiria (2018)
UPS Airlines Flight 2976 was a scheduled domestic cargo flight in the United States from Louisville Muhammad Ali International Airport in Louisville, Kentucky, to Honolulu, Hawaii. On November 4, 2025, the McDonnell Douglas MD-11 operating the flight suffered
Sydney Bernice Sweeney is an American actress. She gained early recognition for her roles in Everything Sucks!, The Handmaid's Tale, and Sharp Objects in 2018. She received wider acclaim for her performances in the drama series Euphoria (2019–2026) and the fir
Michael is a 2026 biographical film directed by Antoine Fuqua and written by John Logan. It follows the early life of the American singer Michael Jackson, from his time with the Jackson 5 in the 1960s to the Bad World Tour in the late 1980s. Jackson is portray
The 68th Annual Grammy Awards honored the best recordings, compositions, and artists from August 31, 2024, to August 30, 2025, as chosen by the members of the Recording Academy, on February 1, 2026. In its 23rd year at Crypto.com Arena in Los Angeles and for t
XXX may refer to:
Marshawn Kneeland was an American professional football defensive end for the Dallas Cowboys of the National Football League (NFL). He played two seasons with the Cowboys until his death in 2025. Kneeland played college football for the Western Michigan Bronco
Sanjay Khan is an Indian actor, businessman, producer and director known for his works in Hindi films and television. Sanjay Khan made his debut in Rajshri film Dosti (1964), which won the National Film Award for Best Feature Film in Hindi for that year, follo
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
CoFineLLM: Conformal Finetuning of LLMs for Language-Instructed Robot Planning
Large Language Models (LLMs) have recently emerged as planners for language-instructed agents, generating sequences of actions to accomplish natural language tasks. However, their reliability remains a challenge, especially in long-horizon tasks, since they often produce overconfident yet wrong outputs. Conformal Prediction (CP) has been leveraged to address this issue by wrapping LLM outputs into prediction sets tha
SteganoSNN: SNN-Based Audio-in-Image Steganography with Encryption
Secure data hiding remains a fundamental challenge in digital communication, requiring a careful balance between computational efficiency and perceptual transparency. The balance between security and performance is increasingly fragile with the emergence of generative AI systems capable of autonomously generating and optimising sophisticated cryptanalysis and steganalysis algorithms, thereby accelerating the exposure
Rep2Text: Decoding Full Text from a Single LLM Token Representation
Large language models (LLMs) have achieved remarkable progress across diverse tasks, yet their internal mechanisms remain largely opaque. In this work, we investigate a fundamental question: to what extent can the original input text be recovered from a single last-token representation in an LLM? To this end, we propose Rep2Text, a novel framework for decoding text from last-token representations. Rep2Text employs a
Breaking the Dyadic Barrier: Rethinking Fairness in Link Prediction Beyond Demographic Parity
Link prediction is a fundamental task in graph machine learning with applications, ranging from social recommendation to knowledge graph completion. Fairness in this setting is critical, as biased predictions can exacerbate societal inequalities. Prior work adopts a dyadic definition of fairness, enforcing fairness through demographic parity between intra-group and inter-group link predictions. However, we show that
Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising
Diffusion-based video generation can create realistic videos, yet existing image- and text-based conditioning fails to offer precise motion control. Prior methods for motion-conditioned synthesis typically require model-specific fine-tuning, which is computationally expensive and restrictive. We introduce Time-to-Move (TTM), a training-free, plug-and-play framework for motion- and appearance-controlled video generati
LLM For Loop Invariant Generation and Fixing: How Far Are We?
A loop invariant is a property of a loop that remains true before and after each execution of the loop. The identification of loop invariants is a critical step to support automated program safety assessment. Recent advancements in Large Language Models (LLMs) have demonstrated potential in diverse software engineering (SE) and formal verification tasks. However, we are not aware of the performance of LLMs to infer l
Machine learning systems exhibit diverse failure modes: unfairness toward protected groups, brittleness to spurious correlations, poor performance on minority sub-populations, which are typically studied in isolation by distinct research communities. We propose a unifying theoretical framework that characterizes when different bias mechanisms produce quantitatively equivalent effects on model performance. By formaliz
Ibom NLP: A Step Toward Inclusive Natural Language Processing for Nigeria's Minority Languages
Nigeria is the most populous country in Africa with a population of more than 200 million people. More than 500 languages are spoken in Nigeria and it is one of the most linguistically diverse countries in the world. Despite this, natural language processing (NLP) research has mostly focused on the following four languages: Hausa, Igbo, Nigerian-Pidgin, and Yoruba (i.e <1% of the languages spoken in Nigeria). This
TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation
In decision-making processes, stakeholders often rely on counterfactual explanations, which provide suggestions about what should be changed in the queried instance to alter the outcome of an AI system. However, generating these explanations for multivariate time series presents challenges due to their complex, multi-dimensional nature. Traditional Nearest Unlike Neighbor-based methods typically substitute subsequenc
FractalBench: Diagnosing Visual-Mathematical Reasoning Through Recursive Program Synthesis
Mathematical reasoning requires abstracting symbolic rules from visual patterns -- inferring the infinite from the finite. We investigate whether multimodal AI systems possess this capability through FractalBench, a benchmark evaluating fractal program synthesis from images. Fractals provide ideal test cases: Iterated Function Systems with only a few contraction maps generate complex self-similar patterns through sim
On the Analogy between Human Brain and LLMs: Spotting Key Neurons in Grammar Perception
Artificial Neural Networks, the building blocks of AI, were inspired by the human brain's network of neurons. Over the years, these networks have evolved to replicate the complex capabilities of the brain, allowing them to handle tasks such as image and language processing. In the realm of Large Language Models, there has been a keen interest in making the language learning process more akin to that of humans. While
Evo* 2025 -- Late-Breaking Abstracts Volume
Volume containing the Late-Breaking Abstracts submitted to the Evo* 2025 Conference, held in Trieste (Italy) from April 23rd to 25th. These extended abstracts showcase ongoing research and preliminary findings exploring the application of various Bioinspired Methods (primarily Evolutionary Computation) to a range of problems, many of which address real-world scenarios.
Rethinking what Matters: Effective and Robust Multilingual Realignment for Low-Resource Languages
Realignment is a promising strategy to improve cross-lingual transfer in multilingual language models. However, empirical results are mixed and often unreliable, particularly for typologically distant or low-resource languages (LRLs) compared to English. Moreover, word realignment tools often rely on high-quality parallel data, which can be scarce or noisy for many LRLs. In this work, we conduct an extensive empirica
A Low-Rank Method for Vision Language Model Hallucination Mitigation in Autonomous Driving
Vision Language Models (VLMs) are increasingly used in autonomous driving to help understand traffic scenes, but they sometimes produce hallucinations, which are false details not grounded in the visual input. Detecting and mitigating hallucinations is challenging when ground-truth references are unavailable and model internals are inaccessible. This paper proposes a novel self-contained low-rank approach to automati
Route Experts by Sequence, not by Token
Mixture-of-Experts (MoE) architectures scale large language models (LLMs) by activating only a subset of experts per token, but the standard TopK routing assigns the same fixed number of experts to all tokens, ignoring their varying complexity. Prior adaptive routing methods introduce additional modules and hyperparameters, often requiring costly retraining from scratch. We propose Sequence-level TopK (SeqTopK), a mi
Explainable AI For Early Detection Of Sepsis
Sepsis is a life-threatening condition that requires rapid detection and treatment to prevent progression to severe sepsis, septic shock, or multi-organ failure. Despite advances in medical technology, it remains a major challenge for clinicians. While recent machine learning models have shown promise in predicting sepsis onset, their black-box nature limits interpretability and clinical trust. In this study, we pres
Complex visual narratives, such as comics, present a significant challenge to Vision-Language Models (VLMs). Despite excelling on natural images, VLMs often struggle with stylized line art, onomatopoeia, and densely packed multi-panel layouts. To address this gap, we introduce AI4VA-FG, the first fine-grained and comprehensive benchmark for VLM-based comic understanding. It spans tasks from foundational recognition a
Beyond Correctness: Confidence-Aware Reward Modeling for Enhancing Large Language Model Reasoning
Recent advancements in large language models (LLMs) have shifted the post-training paradigm from traditional instruction tuning and human preference alignment toward reinforcement learning (RL) focused on reasoning capabilities. However, numerous technical reports indicate that purely rule-based reward RL frequently results in poor-quality reasoning chains or inconsistencies between reasoning processes and final answ
GHOST: Solving the Traveling Salesman Problem on Graphs of Convex Sets
We study GCS-TSP, a new variant of the Traveling Salesman Problem (TSP) defined over a Graph of Convex Sets (GCS) -- a powerful representation for trajectory planning that decomposes the configuration space into convex regions connected by a sparse graph. In this setting, edge costs are not fixed but depend on the specific trajectory selected through each convex region, making classical TSP methods inapplicable. We i
Brain-Inspired Planning for Better Generalization in Reinforcement Learning
Existing Reinforcement Learning (RL) systems encounter significant challenges when applied to real-world scenarios, primarily due to poor generalization across environments that differ from their training conditions. This thesis explores the direction of enhancing agents' zero-shot systematic generalization abilities by granting RL agents reasoning behaviors that are found to help systematic generalization in the hum
EchoMark: Perceptual Acoustic Environment Transfer with Watermark-Embedded Room Impulse Response
Acoustic Environment Matching (AEM) is the task of transferring clean audio into a target acoustic environment, enabling engaging applications such as audio dubbing and auditory immersive virtual reality (VR). Recovering similar room impulse response (RIR) directly from reverberant speech offers more accessible and flexible AEM solution. However, this capability also introduces vulnerabilities of arbitrary ``relocati
Large Language Models require substantial computational resources for inference, posing deployment challenges. While dynamic pruning offers superior efficiency over static methods through adaptive circuit selection, it exacerbates alignment degradation by retaining only input-dependent safety-critical circuit preservation across diverse inputs. As a result, addressing these heightened alignment vulnerabilities remain
A Multi-Agent System for Semantic Mapping of Relational Data to Knowledge Graphs
Enterprises often maintain multiple databases for storing critical business data in siloed systems, resulting in inefficiencies and challenges with data interoperability. A key to overcoming these challenges lies in integrating disparate data sources, enabling businesses to unlock the full potential of their data. Our work presents a novel approach for integrating multiple databases using knowledge graphs, focusing o
FLEX: Continuous Agent Evolution via Forward Learning from Experience
Autonomous agents driven by Large Language Models (LLMs) have revolutionized reasoning and problem-solving but remain static after training, unable to grow with experience as intelligent beings do during deployment. We introduce Forward Learning with EXperience (FLEX), a gradient-free learning paradigm that enables LLM agents to continuously evolve through accumulated experience. Specifically, FLEX cultivates scalabl
When AI Agents Collude Online: Financial Fraud Risks by Collaborative LLM Agents on Social Platforms
In this work, we study the risks of collective financial fraud in large-scale multi-agent systems powered by large language model (LLM) agents. We investigate whether agents can collaborate in fraudulent behaviors, how such collaboration amplifies risks, and what factors influence fraud success. To support this research, we present MultiAgentFraudBench, a large-scale benchmark for simulating financial fraud scenarios
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