{"date":"2026-03-10","schema_version":1,"captured_at":"2026-08-25T23:31:23.503Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Mojtaba Khamenei","views":517317,"rank":3,"extract":"Mojtaba Hosseini Khamenei is an Iranian Shia cleric and politician who has served as the third supreme leader of Iran since 2026. A member of the Khamenei family and the second son of second supreme leader Ali Khamenei, he previously served as Vakil of the Sup","url":"https://en.wikipedia.org/wiki/Mojtaba_Khamenei","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/c/c6/Portrait_of_Mojtaba_Khamenei.jpg/330px-Portrait_of_Mojtaba_Khamenei.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Jennifer Runyon","views":469337,"rank":4,"extract":"Jennifer Runyon was an American actress. 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the Age of AI","points":201,"comments":145,"url":"https://batsov.com/articles/2026/03/09/emacs-and-vim-in-the-age-of-ai/","discussion":"https://news.ycombinator.com/item?id=47319071"}],"research":[{"title":"Online Neural Networks for Change-Point Detection","abstract":"Moments when a time series changes its behavior are called change points. Occurrence of change point implies that the state of the system is altered and its timely detection might help to prevent unwanted consequences. In this paper, we present two change-point detection approaches based on neural networks and online learning. These algorithms demonstrate linear computational complexity and are suitable for change-po","authors":["Hushchyn, Mikhail","Arzymatov, Kenenbek","Derkach, Denis"],"url":"https://arxiv.org/abs/2010.01388","arxiv_id":"2010.01388","published":"2026-03-10"},{"title":"Accounting for shared covariates in semi-parametric Bayesian additive regression trees","abstract":"We propose some extensions to semi-parametric models based on Bayesian additive regression trees (BART). In the semi-parametric BART paradigm, the response variable is approximated by a linear predictor and a BART model, where the linear component is responsible for estimating the main effects and BART accounts for non-specified interactions and non-linearities. Previous semi-parametric models based on BART have assu","authors":["Prado, Estevão B.","Parnell, Andrew C.","Murphy, Keefe","McJames, Nathan","O'Shea, Ann","Moral, Rafael A."],"url":"https://arxiv.org/abs/2108.07636","arxiv_id":"2108.07636","published":"2026-03-10"},{"title":"A White-Box SVM Framework and its Swarm-Based Optimization for Supervision of Toothed Milling Cutter through Characterization of Spindle Vibrations","abstract":"In this paper, a white-Box support vector machine (SVM) framework and its swarm-based optimization is presented for supervision of toothed milling cutter through characterization of real-time spindle vibrations. The anomalous moments of vibration evolved due to in-process tool failures (i.e., flank and nose wear, crater and notch wear, edge fracture) have been investigated through time-domain response of acceleration","authors":["Deo, Tejas Y.","Deshmukh, B. B.","Jatakar, Keshav H.","Chhajed, Kamlesh M.","Pardeshi, S. S.","Jegadeeshwaran, R."],"url":"https://arxiv.org/abs/2112.08421","arxiv_id":"2112.08421","published":"2026-03-10"},{"title":"Differentiable Microscopy Designs an All Optical Phase Retrieval Microscope","abstract":"Designing new optical systems from the ground up for microscopy imaging tasks such as phase retrieval, requires substantial scientific expertise and creativity. To augment the traditional design process, we propose differentiable microscopy ($\\partialμ$), which introduces a top-down design approach. Using all optical phase retrieval as an illustrative example, we demonstrate the effectiveness of data-driven microscop","authors":["Herath, Kithmini","Kariyawasam, Hasindu","Hettiarachchi, Ramith","Haputhanthri, Udith","Jayakody, Dineth","Ahmad, Raja N."],"url":"https://arxiv.org/abs/2203.14944","arxiv_id":"2203.14944","published":"2026-03-10"},{"title":"Explainable classification of astronomical uncertain time series","abstract":"Exploring the expansion history of the universe, understanding its evolutionary stages, and predicting its future evolution are important goals in astrophysics. Today, machine learning tools are used to help achieving these goals by analyzing transient sources, which are modeled as uncertain time series. Although black-box methods achieve appreciable performance, existing interpretable time series methods failed to o","authors":["Mbouopda, Michael Franklin","Ishida, Emille E. O.","Nguifo, Engelbert Mephu","Gangler, Emmanuel"],"url":"https://arxiv.org/abs/2210.00869","arxiv_id":"2210.00869","published":"2026-03-10"},{"title":"Empirical Asset Pricing via Ensemble Gaussian Process Regression","abstract":"We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and lends itself to general online learning tasks. We conduct an empirical analysis on a large cross-section of US stocks from 1","authors":["Filipović, Damir","Pasricha, Puneet"],"url":"https://arxiv.org/abs/2212.01048","arxiv_id":"2212.01048","published":"2026-03-10"},{"title":"Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part I","abstract":"We study the task of learning state representations from potentially high-dimensional observations, with the goal of controlling an unknown partially observable system. We pursue a cost-driven approach, where a dynamic model in some latent state space is learned by predicting the costs without predicting the observations or actions. In particular, we focus on an intuitive cost-driven state representation learning met","authors":["Tian, Yi","Zhang, Kaiqing","Tedrake, Russ","Sra, Suvrit"],"url":"https://arxiv.org/abs/2212.14511","arxiv_id":"2212.14511","published":"2026-03-10"},{"title":"A Robust Multi-Item Auction Design with Statistical Learning","abstract":"We propose a novel statistical learning method for multi-item auctions that incorporates credible intervals. Our approach employs nonparametric density estimation to estimate credible intervals for bidder types based on historical data. We introduce two new strategies that leverage these credible intervals to reduce the time cost of implementing auctions. The first strategy screens potential winners' value region","authors":["Han, Jiale","Dai, Xiaowu"],"url":"https://arxiv.org/abs/2302.00941","arxiv_id":"2302.00941","published":"2026-03-10"},{"title":"Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation","abstract":"Current methods of blended targets domain adaptation (BTDA) usually infer or consider domain label information but underemphasize hybrid categorical feature structures of targets, which yields limited performance, especially under the label distribution shift. We demonstrate that domain labels are not directly necessary for BTDA if categorical distributions of various domains are sufficiently aligned even facing the ","authors":["Xu, Pengcheng","Wang, Boyu","Ling, Charles"],"url":"https://arxiv.org/abs/2302.01516","arxiv_id":"2302.01516","published":"2026-03-10"},{"title":"An Embedding-based Approach to Inconsistency-tolerant Reasoning with Inconsistent Ontologies","abstract":"Inconsistency handling is an important issue in knowledge management. Especially in ontology engineering, logical inconsistencies may occur during ontology construction. A natural way to reason with an inconsistent ontology is to utilize the maximal consistent subsets of the ontology. However, previous studies on selecting maximum consistent subsets have rarely considered the semantics of the axioms, which may result","authors":["Wang, Keyu","Li, Site","Li, Jiaye","Qi, Guilin","Ji, Qiu"],"url":"https://arxiv.org/abs/2304.01664","arxiv_id":"2304.01664","published":"2026-03-10"},{"title":"altiro3D: Scene representation from single image and novel view synthesis","abstract":"We introduce altiro3D, a free extended library developed to represent reality starting from a given original RGB image or flat video. It allows to generate a light-field (or Native) image or video and get a realistic 3D experience. To synthesize N-number of virtual images and add them sequentially into a Quilt collage, we apply MiDaS models for the monocular depth estimation, simple OpenCV and Telea inpainting techni","authors":["Canessa, E.","Tenze, L."],"url":"https://arxiv.org/abs/2304.11161","arxiv_id":"2304.11161","published":"2026-03-10"},{"title":"Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey","abstract":"Cognitive modeling, which explores the essence of cognition, including motivation, emotion, and perception, has been widely applied in the artificial intelligence (AI) agent domains, such as robotics. From the computational perspective, various cognitive functionalities have been developed through utility theory to provide a detailed and process-based understanding for specifying corresponding computational models of","authors":["Yang, Qin"],"url":"https://arxiv.org/abs/2306.09445","arxiv_id":"2306.09445","published":"2026-03-10"},{"title":"Temporal Smoothness Regularisers for Neural Link Predictors","abstract":"Most algorithms for representation learning and link prediction on relational data are designed for static data. However, the data to which they are applied typically evolves over time, including online social networks or interactions between users and items in recommender systems. This is also the case for graph-structured knowledge bases -- knowledge graphs -- which contain facts that are valid only for specific po","authors":["Dileo, Manuel","Minervini, Pasquale","Zignani, Matteo","Gaito, Sabrina"],"url":"https://arxiv.org/abs/2309.09045","arxiv_id":"2309.09045","published":"2026-03-10"},{"title":"Online Dispatching and Routing for Automated Guided Vehicles in Pickup and Delivery Systems on Loop-Based Graphs","abstract":"Automated guided vehicles (AGVs) are widely used in various industries, and scheduling and routing them in a conflict-free manner is crucial to their efficient operation. We propose a loop-based algorithm that solves the online, conflict-free scheduling and routing problem for AGVs with any capacity and ordered jobs in loop-based graphs. The proposed algorithm is compared against an exact method, a greedy heuristic a","authors":["Stubbe, Louis","Goemaere, Jens","Goedgebeur, Jan"],"url":"https://arxiv.org/abs/2310.02195","arxiv_id":"2310.02195","published":"2026-03-10"},{"title":"CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification","abstract":"Person re-identification (re-ID) is a challenging task that aims to learn discriminative features for person retrieval. In person re-ID, Jaccard distance is a widely used distance metric, especially in re-ranking and clustering scenarios. However, we discover that camera variation has a significant negative impact on the reliability of Jaccard distance. In particular, Jaccard distance calculates the distance based on","authors":["Chen, Yiyu","Fan, Zheyi","Chen, Zhaoru","Zhu, Yixuan"],"url":"https://arxiv.org/abs/2311.10605","arxiv_id":"2311.10605","published":"2026-03-10"},{"title":"On the Impact of Sampling on Deep Sequential State Estimation","abstract":"State inference and parameter learning in sequential models can be successfully performed with approximation techniques that maximize the evidence lower bound to the marginal log-likelihood of the data distribution. These methods may be referred to as Dynamical Variational Autoencoders, and our specific focus lies on the deep Kalman filter. It has been shown that the ELBO objective can oversimplify data representatio","authors":["Calatrava, Helena","Borsoi, Ricardo Augusto","Imbiriba, Tales","Closas, Pau"],"url":"https://arxiv.org/abs/2311.17006","arxiv_id":"2311.17006","published":"2026-03-10"},{"title":"DivCon: Divide and Conquer for Complex Numerical and Spatial Reasoning in Text-to-Image Generation","abstract":"Diffusion-driven text-to-image (T2I) generation has achieved remarkable advancements in recent years. To further improve T2I models' capability in numerical and spatial reasoning, layout is employed as an intermedium to bridge large language models and layout-based diffusion models. However, these methods often rely on closed-source, large-scale LLMs for layout prediction, limiting accessibility and scalability. ","authors":["Jia, Yuhao","Tan, Wenhan"],"url":"https://arxiv.org/abs/2403.06400","arxiv_id":"2403.06400","published":"2026-03-10"},{"title":"Deepfake Generation and Detection: A Benchmark and Survey","abstract":"Deepfake is a technology dedicated to creating highly realistic facial images and videos under specific conditions, which has significant application potential in fields such as entertainment, movie production, digital human creation, to name a few. With the advancements in deep learning, techniques primarily represented by Variational Autoencoders and Generative Adversarial Networks have achieved impressive generati","authors":["Pei, Gan","Zhang, Jiangning","Hu, Menghan","Zhang, Zhenyu","Wang, Chengjie","Wu, Yunsheng"],"url":"https://arxiv.org/abs/2403.17881","arxiv_id":"2403.17881","published":"2026-03-10"},{"title":"Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States","abstract":"Reducing computational scaling for simulating non-Markovian dissipative dynamics using artificial neural networks is both a major focus and formidable challenge in open quantum systems. To enable neural quantum states (NQSs), we encode environmental memory in dissipatons (quasiparticles with characteristic lifetimes), yielding the dissipaton-embedded quantum master equation (DQME). The resulting NQS-DQME framework ac","authors":["Cao, Long","Ge, Liwei","Zhang, Daochi","Li, Xiang","Wang, Yao","Xu, Rui-Xue"],"url":"https://arxiv.org/abs/2404.11093","arxiv_id":"2404.11093","published":"2026-03-10"},{"title":"LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention Networks","abstract":"Numerous real-world decisions rely on machine learning algorithms and require calibrated uncertainty estimates. However, modern methods often yield overconfident, uncalibrated predictions. The dominant approach to quantifying the uncertainty inherent in the model is to train an ensemble of separate predictors and measure their empirical variance. In an explicit implementation, the ensemble has a high computational co","authors":["Mühlematter, Dominik J.","Halbheer, Michelle","Becker, Alexander","Narnhofer, Dominik","Aasen, Helge","Schindler, Konrad"],"url":"https://arxiv.org/abs/2405.14438","arxiv_id":"2405.14438","published":"2026-03-10"},{"title":"Goldilocks Test Sets for Face Verification","abstract":"Reported face verification accuracy has reached a plateau on current well-known test sets. As a result, some difficult test sets have been assembled by reducing the image quality or adding artifacts to the image. However, we argue that test sets can be challenging without artificially reducing the image quality because the face recognition (FR) models suffer from correctly recognizing 1) the pairs from the same ident","authors":["Wu, Haiyu","Tian, Sicong","Bhatta, Aman","Gutierrez, Jacob","Bezold, Grace","Argueta, Genesis"],"url":"https://arxiv.org/abs/2405.15965","arxiv_id":"2405.15965","published":"2026-03-10"},{"title":"Fast Explanations via Policy Gradient-Optimized Explainer","abstract":"The challenge of delivering efficient explanations is a critical barrier that prevents the adoption of model explanations in real-world applications. Existing approaches often depend on extensive model queries for sample-level explanations or rely on expert's knowledge of specific model structures that trade general applicability for efficiency. To address these limitations, this paper introduces a novel framewor","authors":["Pan, Deng","Moniz, Nuno","Chawla, Nitesh"],"url":"https://arxiv.org/abs/2405.18664","arxiv_id":"2405.18664","published":"2026-03-10"},{"title":"Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks","abstract":"Few-shot fine-tuning of Diffusion Models (DMs) is a key advancement, significantly reducing training costs and enabling personalized AI applications. However, we explore the training dynamics of DMs and observe an unanticipated phenomenon: during the training process, image fidelity initially improves, then unexpectedly deteriorates with the emergence of noisy patterns, only to recover later with severe overfitting. ","authors":["Wu, Xiaoyu","Zhang, Jiaru","Hua, Yang","Lyu, Bohan","Wang, Hao","Song, Tao"],"url":"https://arxiv.org/abs/2405.19931","arxiv_id":"2405.19931","published":"2026-03-10"},{"title":"ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs","abstract":"Deep Neural Networks (DNNs) are extensively employed in safety-critical applications where ensuring hardware reliability is a primary concern. To enhance the reliability of DNNs against hardware faults, activation restriction techniques significantly mitigate the fault effects at the DNN structure level, irrespective of accelerator architectures. State-of-the-art methods offer either neuron-wise or layer-wise clippin","authors":["Mousavi, Seyedhamidreza","Ahmadilivani, Mohammad Hasan","Raik, Jaan","Jenihhin, Maksim","Daneshtalab, Masoud"],"url":"https://arxiv.org/abs/2406.06313","arxiv_id":"2406.06313","published":"2026-03-10"},{"title":"DKDL-Net: A Lightweight Bearing Fault Detection Model via Decoupled Knowledge Distillation and Low-Rank Adaptation Fine-tuning","abstract":"Rolling bearing fault detection has developed rapidly in the field of fault diagnosis technology, and it occupies a very important position in this field. Deep learning-based bearing fault diagnosis models have achieved significant success. At the same time, with the continuous improvement of new signal processing technologies such as Fourier transform, wavelet transform and empirical mode decomposition, the fault di","authors":["Petrosian, Ovanes","Pengyi, Li","Yulong, He","Jiarui, Liu","Zhaoruikun, Sun","Guofeng, Fu"],"url":"https://arxiv.org/abs/2406.06653","arxiv_id":"2406.06653","published":"2026-03-10"}],"history":{"events":[{"year":2019,"text":"Ethiopian Airlines Flight 302 crashed six minutes after take-off from Addis Ababa International Airport due to a fault within the software of the plane, resulting in the deaths of all 157 people on board.","url":"https://en.wikipedia.org/wiki/Ethiopian_Airlines_Flight_302"},{"year":2008,"text":"The New York Times revealed that Eliot Spitzer (pictured), Governor of New York, had patronized a prostitution ring.","url":"https://en.wikipedia.org/wiki/The_New_York_Times"},{"year":2006,"text":"NASA's Mars Reconnaissance Orbiter (artist's impression pictured) reached and entered orbit around Mars.","url":"https://en.wikipedia.org/wiki/NASA"},{"year":1990,"text":"Eighteen months after seizing power, Prosper Avril was ousted as the military head of state of Haiti.","url":"https://en.wikipedia.org/wiki/Prosper_Avril"},{"year":1977,"text":"Astronomers using NASA's Kuiper Airborne Observatory discovered a faint ring system around Uranus.","url":"https://en.wikipedia.org/wiki/NASA"},{"year":1975,"text":"Ho Chi Minh Campaign: North Vietnam began its final push for victory over South Vietnam with an attack on Ban Me Thuot.","url":"https://en.wikipedia.org/wiki/1975_spring_offensive"},{"year":1968,"text":"Vietnam War/Laotian Civil War: North Vietnamese and Pathet Lao forces overwhelmed the American, Laotian, Thai, and Hmong defenders of Lima Site 85.","url":"https://en.wikipedia.org/wiki/Vietnam_War"},{"year":1967,"text":"British progressive-rock band Pink Floyd released their first single, \"Arnold Layne\".","url":"https://en.wikipedia.org/wiki/Progressive_rock"},{"year":1966,"text":"Military prime minister of South Vietnam Nguyễn Cao Kỳ sacked rival General Nguyễn Chánh Thi, precipitating large-scale civil and military dissension in parts of the nation.","url":"https://en.wikipedia.org/wiki/Nguy%E1%BB%85n_Cao_K%E1%BB%B3"},{"year":1965,"text":"Thomas Playford, Premier of South Australia, left office after 27 years, the longest term of any democratically elected leader in the history of Australia.","url":"https://en.wikipedia.org/wiki/Thomas_Playford_IV"},{"year":1959,"text":"An anti-Chinese uprising began as thousands of Tibetans surrounded the Potala Palace in Lhasa to prevent the Dalai Lama from leaving or being removed by the Chinese army.","url":"https://en.wikipedia.org/wiki/1959_Tibetan_uprising"},{"year":1949,"text":"Mildred Gillars, nicknamed Axis Sally, was convicted of treason for working with the Nazis as a broadcaster.","url":"https://en.wikipedia.org/wiki/Mildred_Gillars"},{"year":1945,"text":"World War II: The United States Army Air Forces conducted a firebombing raid on Tokyo that killed at least 90,000 people.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1917,"text":"Russia and France reached an agreement' to support one another's territorial ambitions for Europe in the aftermath of World War I.","url":"https://en.wikipedia.org/wiki/1917_Franco-Russian_agreement"},{"year":1916,"text":"The final letter in the McMahon–Hussein Correspondence was written, agreeing that Britain would recognise Arab independence in return for the Sharif of Mecca launching a revolt against the Ottoman Empire.","url":"https://en.wikipedia.org/wiki/McMahon%E2%80%93Hussein_correspondence"},{"year":1915,"text":"The Battle of Neuve Chapelle, the first deliberately planned British offensive of the First World War, began.","url":"https://en.wikipedia.org/wiki/Battle_of_Neuve-Chapelle"},{"year":1695,"text":"Nine Years' War: At the Battle of Sant Esteve d'en Bas, Catalan miquelets attacked a column of French regular infantry and caused them to surrender.","url":"https://en.wikipedia.org/wiki/Nine_Years'_War"},{"year":-241,"text":"The Roman Republic defeated Carthaginian forces at the Battle of the Aegates, off the western coast of Sicily, in the final battle of the First Punic War.","url":"https://en.wikipedia.org/wiki/Roman_Republic"}],"births":[{"year":2004,"text":"Matt Poitras, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Matt_Poitras"},{"year":2002,"text":"Keon Johnson, American basketball player","url":"https://en.wikipedia.org/wiki/Keon_Johnson_(basketball%2C_born_2002)"},{"year":2000,"text":"Nick Bolton, American football player","url":"https://en.wikipedia.org/wiki/Nick_Bolton"},{"year":1999,"text":"Cole Kmet, American football player","url":"https://en.wikipedia.org/wiki/Cole_Kmet"},{"year":1998,"text":"Justin Herbert, American football player","url":"https://en.wikipedia.org/wiki/Justin_Herbert"},{"year":1997,"text":"Belinda Bencic, Swiss tennis player","url":"https://en.wikipedia.org/wiki/Belinda_Bencic"},{"year":1995,"text":"Zach LaVine, American basketball player","url":"https://en.wikipedia.org/wiki/Zach_LaVine"},{"year":1995,"text":"Sergey Mozgov, Russian ice dancer","url":"https://en.wikipedia.org/wiki/Sergey_Mozgov"}],"deaths":[{"year":2025,"text":"Stanley R. Jaffe, American film producer and director (born 1940)","url":"https://en.wikipedia.org/wiki/Stanley_R._Jaffe"},{"year":2025,"text":"Carl Lundström, Swedish businessman and activist (born 1960)","url":"https://en.wikipedia.org/wiki/Carl_Lundstr%C3%B6m"},{"year":2022,"text":"John Elliott, English historian and academic (born 1930)","url":"https://en.wikipedia.org/wiki/J._H._Elliott"},{"year":2016,"text":"Ken Adam, German-English production designer and art director (born 1921)","url":"https://en.wikipedia.org/wiki/Ken_Adam"},{"year":2016,"text":"Roberto Perfumo, Argentinian footballer and sportscaster (born 1942)","url":"https://en.wikipedia.org/wiki/Roberto_Perfumo"},{"year":2016,"text":"Jovito Salonga, Filipino lawyer and politician, 14th President of the Senate of the Philippines (born 1920)","url":"https://en.wikipedia.org/wiki/Jovito_Salonga"},{"year":2016,"text":"Anita Brookner, English novelist and art historian (born 1928)","url":"https://en.wikipedia.org/wiki/Anita_Brookner"},{"year":2015,"text":"Richard Glatzer, American director, producer, and screenwriter (born 1952)","url":"https://en.wikipedia.org/wiki/Richard_Glatzer"}]},"census":null,"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"},{"id":"frontier","name":"Hacker News","url":"https://news.ycombinator.com","licence":"Public API — titles and links, credited","attribution":"Hacker News / Y Combinator"},{"id":"research","name":"arXiv cs.AI","url":"https://arxiv.org","licence":"Open metadata, per arXiv API terms","attribution":"arXiv.org"},{"id":"history","name":"Wikipedia On this day","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia contributors"}],"licence":"Records are CC BY-SA 4.0, inheriting from Wikipedia. Every item links to its source."}