{"date":"2026-05-15","schema_version":1,"captured_at":"2026-08-25T23:08:39.565Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Wes Streeting","views":227168,"rank":4,"extract":"Wesley Paul William Streeting is a British politician who has served as Secretary of State for Defence since 2026. He previously served as Secretary of State for Health and Social Care from 2024 until his resignation in 2026. 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'Always free' and 'Inclusion' values from its site","points":271,"comments":143,"url":"https://www.fastcompany.com/91542655/bitwarden-scrubs-always-free-and-inclusion-values-from-its-website-as-longtime-execs-step-down","discussion":"https://news.ycombinator.com/item?id=48147637"},{"title":"Details of the Daring Airdrop at Tristan Da Cunha","points":268,"comments":104,"url":"https://www.tristandc.com/government/news-2026-05-11-airdrop.php","discussion":"https://news.ycombinator.com/item?id=48144380"},{"title":"Erlang/OTP 29.0","points":257,"comments":61,"url":"https://www.erlang.org/news/188","discussion":"https://news.ycombinator.com/item?id=48155297"},{"title":"How Claude Code works in large codebases","points":248,"comments":160,"url":"https://claude.com/blog/how-claude-code-works-in-large-codebases-best-practices-and-where-to-start","discussion":"https://news.ycombinator.com/item?id=48144494"},{"title":"O(x)Caml in 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in damage annually, with malicious hackers often sharing exploit code and techniques on underground forums. Identifying which organizations are targeted by these exploits is critical for proactive Cyber Threat Intelligence (CTI). To address that gap, we propose Temporal Representation and Classification of Exploits (TRACE), a vendor-conditioned contrastive learning framework bui","authors":["Ampel, Benjamin M."],"url":"https://arxiv.org/abs/2012.14425","arxiv_id":"2012.14425","published":"2026-05-15"},{"title":"Change of measure through the Legendre transform","abstract":"PAC-Bayes generalisation bounds are derived via change-of-measure inequalities that transfer concentration properties from a reference measure to all posterior measures. The specific choice of change of measure determines the assumptions required on the empirical risk; in particular, the classical Donsker--Varadhan theorem leads to bounds relying on bounded exponential moments. We study change-of-measure inequalities","authors":["Picard-Weibel, Antoine","Guedj, Benjamin"],"url":"https://arxiv.org/abs/2202.05568","arxiv_id":"2202.05568","published":"2026-05-15"},{"title":"Timing-Based Backpropagation in Spiking Neural Networks Without Single-Spike Restrictions","abstract":"We propose a novel backpropagation algorithm for training spiking neural networks (SNNs) that encodes information in the relative multiple spike timing of individual neurons without single-spike restrictions. The proposed algorithm inherits the advantages of conventional timing-based methods in that it computes accurate gradients with respect to spike timing, which promotes ideal temporal coding. Unlike conventional ","authors":["Yamamoto, Kakei","Sakemi, Yusuke","Aihara, Kazuyuki"],"url":"https://arxiv.org/abs/2211.16113","arxiv_id":"2211.16113","published":"2026-05-15"},{"title":"Improving robustness of jet tagging algorithms with adversarial training: exploring the loss surface","abstract":"In the field of high-energy physics, deep learning algorithms continue to gain in relevance and provide performance improvements over traditional methods, for example when identifying rare signals or finding complex patterns. From an analyst's perspective, obtaining highest possible performance is desirable, but recently, some attention has been shifted towards studying robustness of models to investigate how wel","authors":["Stein, Annika"],"url":"https://arxiv.org/abs/2303.14511","arxiv_id":"2303.14511","published":"2026-05-15"},{"title":"A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints","abstract":"Nonsmooth composite optimization with orthogonality constraints has a wide range of applications in statistical learning and data science. However, this problem is challenging due to its nonsmooth objective and computationally expensive nonconvex constraints. In this paper, we propose a new approach called \\textbf{OBCD}, which leverages block coordinate descent to address these challenges. \\textbf{OBCD} is a feasible","authors":["Yuan, Ganzhao"],"url":"https://arxiv.org/abs/2304.03641","arxiv_id":"2304.03641","published":"2026-05-15"},{"title":"Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces","abstract":"Recent advances have extended the scope of Bayesian optimization (BO) to expensive-to-evaluate black-box functions with dozens of dimensions, aspiring to unlock impactful applications, for example, in the life sciences, neural architecture search, and robotics. However, a closer examination reveals that the state-of-the-art methods for high-dimensional Bayesian optimization (HDBO) suffer from degrading performance as","authors":["Papenmeier, Leonard","Nardi, Luigi","Poloczek, Matthias"],"url":"https://arxiv.org/abs/2304.11468","arxiv_id":"2304.11468","published":"2026-05-15"},{"title":"Distributional Principal Autoencoders","abstract":"Dimension reduction techniques usually lose information in the sense that reconstructed data are not identical to the original data. However, we argue that it is possible to have reconstructed data identically distributed as the original data, irrespective of the retained dimension or the specific mapping. This can be achieved by learning a distributional model that matches the conditional distribution of data given ","authors":["Shen, Xinwei","Meinshausen, Nicolai"],"url":"https://arxiv.org/abs/2404.13649","arxiv_id":"2404.13649","published":"2026-05-15"},{"title":"DAPL: Integration of Positive and Negative Descriptions in Text-Based Person Search","abstract":"Text-based person search (TBPS) aims to retrieve specific images of individuals from large datasets using textual descriptions. Existing TBPS methods focus primarily on identifying explicit positive attributes, often neglecting the critical role of negative descriptions. This oversight can lead to false positives, where images that should be excluded based on negative descriptions are incorrectly included, due to par","authors":["Deng, Yuchuan","Hu, Zhanpeng","Xin, Zijie","Deng, Chuang","Zhao, Qijun"],"url":"https://arxiv.org/abs/2405.07459","arxiv_id":"2405.07459","published":"2026-05-15"},{"title":"Sequential Resource Trading Using Comparison-Based Gradient Estimation","abstract":"We study sequential multi-issue trading between two greedily rational agents who exchange resources from a finite set of categories. Each agent's utility depends on its allocation, but the offering agent does not know the responding agent's utility function and receives only accept or reject feedback. We propose a comparison-based algorithm that interprets acceptance and rejection responses as pairwise state ","authors":["Murthy, Surya","Karabag, Mustafa O.","Topcu, Ufuk"],"url":"https://arxiv.org/abs/2408.11186","arxiv_id":"2408.11186","published":"2026-05-15"},{"title":"Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes","abstract":"Automatic controller tuning is attractive for robotics and mechatronic systems whose dynamics are difficult to model accurately, but direct black-box optimization can be unsafe because each query is executed on the physical plant. Existing safe Bayesian optimization (BO) methods provide high-probability safety guarantees, yet their practical use in multi-loop control is limited by two coupled difficulties: the contro","authors":["Wang, Hongxuan","Li, Xiaocong","Zheng, Lihao","Bhaumik, Adrish","Vadakkepat, Prahlad"],"url":"https://arxiv.org/abs/2408.16307","arxiv_id":"2408.16307","published":"2026-05-15"},{"title":"On the Diagram of Thought","abstract":"Large Language Models (LLMs) excel at many tasks but often falter on complex problems that require structured, multi-step reasoning. We introduce the Diagram of Thought (DoT), a framework that enables a single LLM to build and navigate a mental map of its reasoning. Instead of thinking in a straight line, the model constructs a dynamic diagram of ideas, where it can propose different lines of thought, critique its ow","authors":["Zhang, Yifan","Yuan, Yang","Yao, Andrew Chi-Chih"],"url":"https://arxiv.org/abs/2409.10038","arxiv_id":"2409.10038","published":"2026-05-15"},{"title":"Manikin-Recorded Cardiopulmonary Sounds Dataset Using Digital Stethoscope","abstract":"Heart and lung sounds are crucial for healthcare monitoring. Recent improvements in stethoscope technology have made it possible to capture patient sounds with enhanced precision. In this dataset, we used a digital stethoscope to capture both heart and lung sounds, including individual and mixed recordings. To our knowledge, this is the first dataset to offer both separate and mixed cardiorespiratory sounds. The reco","authors":["Torabi, Yasaman","Shirani, Shahram","Reilly, James P."],"url":"https://arxiv.org/abs/2410.03280","arxiv_id":"2410.03280","published":"2026-05-15"},{"title":"Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs","abstract":"Accurate uncertainty quantification in large language models (LLMs) is essential for reliable confidence estimation, yet fine-tuned LLMs often become overconfident under limited adaptation data. Existing uncertainty methods for PEFT-based LLMs are largely post hoc, estimating uncertainty after fine-tuning rather than improving how adapters specialize to task-specific input-output relationships. We propose Functional-","authors":["Niu, Ruijia","Wu, Dongxia","Yu, Rose","Ma, Yi-An"],"url":"https://arxiv.org/abs/2410.06431","arxiv_id":"2410.06431","published":"2026-05-15"},{"title":"Conformal Prediction for Multimodal Regression","abstract":"This paper introduces multimodal conformal regression. Traditionally confined to scenarios with solely numerical input features, conformal prediction is now extended to multimodal contexts through our methodology, which harnesses internal features from complex neural network architectures processing images and unstructured text. Our findings highlight the potential for internal neural network features, extracted from","authors":["Bose, Alexis","Ethier, Jonathan","Guinand, Paul"],"url":"https://arxiv.org/abs/2410.19653","arxiv_id":"2410.19653","published":"2026-05-15"},{"title":"Training and Evaluating Language Models with Template-based Data Generation","abstract":"The rapid advancement of large language models (LLMs) such as GPT-3, PaLM, and Llama has significantly transformed natural language processing, showcasing remarkable capabilities in understanding and generating language. However, a fundamental bottleneck persists: these models often struggle with tasks requiring complex, multi-step reasoning, particularly in mathematical problem-solving. This deficiency stems from th","authors":["Zhang, Yifan"],"url":"https://arxiv.org/abs/2411.18104","arxiv_id":"2411.18104","published":"2026-05-15"},{"title":"How well behaved is finite dimensional Diffusion Maps?","abstract":"Under a set of assumptions on a family of submanifolds $\\subset {\\mathbb R}^D$, we derive a series of geometric properties that remain valid after finite-dimensional and almost isometric Diffusion Maps (DM), including almost uniform density, finite polynomial approximation and reach. Leveraging these properties, we establish rigorous bounds on the embedding errors introduced by the DM algorithm is $O\\left((\\frac{\\log","authors":["Bo, Wenyu","Meilă, Marina"],"url":"https://arxiv.org/abs/2412.03992","arxiv_id":"2412.03992","published":"2026-05-15"},{"title":"Projected gradient methods for nonconvex and stochastic smooth optimization: new complexities and auto-conditioned stepsizes","abstract":"We present a novel class of projected gradient (PG) methods for minimizing a smooth but not necessarily convex function over a convex compact set. We first provide a novel analysis of the constant-stepsize PG method, achieving the best-known iteration complexity for finding an approximate stationary point of the problem. We then develop an "auto-conditioned" projected gradient (AC-PG) variant that achieves th","authors":["Lan, Guanghui","Li, Tianjiao","Xu, Yangyang"],"url":"https://arxiv.org/abs/2412.14291","arxiv_id":"2412.14291","published":"2026-05-15"},{"title":"The Potential of Convolutional Neural Networks for Cancer Detection","abstract":"Early detection is crucial for successful cancer treatment and increasing survivability rates, particularly in the most common forms. Ten different cancers have been identified in most of these advances that effectively use CNNs (Convolutional Neural Networks) for classification. The distinct architectures of CNNs used in each study concentrate on pattern recognition for different types of cancer across various datas","authors":["Molaeian, Hossein","Karamjani, Kaveh","Teimouri, Sina","Roshani, Saeed","Roshani, Sobhan"],"url":"https://arxiv.org/abs/2412.17155","arxiv_id":"2412.17155","published":"2026-05-15"},{"title":"Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026)","abstract":"As foundation AI models continue to increase in size, an important question arises - is massive scale the only path forward? This survey of about 160 papers presents a family of Small Language Models (SLMs) in the 1 to 8 billion parameter range that demonstrate smaller models can perform as well, or even outperform large models. We explore task agnostic, general purpose SLMs, task-specific SLMs and techniques to crea","authors":["Gupta, Akanksha","Thomas, Bijo","Asnani, Harshita","Madduru, Phanindra Reddy","Feroze, Samia","Subramanian, Shreyas"],"url":"https://arxiv.org/abs/2501.05465","arxiv_id":"2501.05465","published":"2026-05-15"},{"title":"Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation","abstract":"We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two foundation components: a large-scale shape generation model -- Hunyuan3D-DiT, and a large-scale texture synthesis model -- Hunyuan3D-Paint. The shape generative model, built on a scalable flow-based diffusion transformer, aims to create geometry that properly aligns with a ","authors":["Zhao, Zibo","Lai, Zeqiang","Lin, Qingxiang","Zhao, Yunfei","Liu, Haolin","Yang, Shuhui"],"url":"https://arxiv.org/abs/2501.12202","arxiv_id":"2501.12202","published":"2026-05-15"},{"title":"A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization","abstract":"Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function's optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective by introducing ","authors":["Cheng, Nuojin","Papenmeier, Leonard","Becker, Stephen","Nardi, Luigi"],"url":"https://arxiv.org/abs/2501.18756","arxiv_id":"2501.18756","published":"2026-05-15"},{"title":"DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks","abstract":"The performance of an LLM depends heavily on the relevance of its training data to the downstream evaluation task. However, in practice, the data involved in an unseen evaluation task is often unknown (e.g., conversations between an LLM and a user are end-to-end encrypted). Hence, it is unclear what data are relevant for fine-tuning the LLM to maximize its performance on the specific unseen evaluation task. Instead, ","authors":["Chen, Zhiliang","Lau, Gregory Kang Ruey","Foo, Chuan-Sheng","Low, Bryan Kian Hsiang"],"url":"https://arxiv.org/abs/2502.00270","arxiv_id":"2502.00270","published":"2026-05-15"},{"title":"Physically consistent predictive reduced-order modeling by enhancing Operator Inference with state constraints","abstract":"Numerical simulations of complex multiphysics systems, such as char combustion considered herein, yield numerous state variables that inherently exhibit physical constraints. This paper presents a new approach to augment Operator Inference -- a methodology within scientific machine learning that enables learning from data a low-dimensional representation of a high-dimensional system governed by nonlinear partial diff","authors":["Kim, Hyeonghun","Kramer, Boris"],"url":"https://arxiv.org/abs/2502.03672","arxiv_id":"2502.03672","published":"2026-05-15"},{"title":"Exploring Exploration in Bayesian Optimization","abstract":"A well-balanced exploration-exploitation trade-off is crucial for successful acquisition functions in Bayesian optimization. However, there is a lack of quantitative measures for exploration, making it difficult to analyze and compare different acquisition functions. This work introduces two novel approaches - observation traveling salesman distance and observation entropy - to quantify the exploration characteristic","authors":["Papenmeier, Leonard","Cheng, Nuojin","Becker, Stephen","Nardi, Luigi"],"url":"https://arxiv.org/abs/2502.08208","arxiv_id":"2502.08208","published":"2026-05-15"},{"title":"Understanding High-Dimensional Bayesian Optimization","abstract":"Recent work reported that simple Bayesian optimization (BO) methods perform well for high-dimensional real-world tasks, seemingly contradicting prior work and tribal knowledge. This paper investigates why. We identify underlying challenges that arise in high-dimensional BO and explain why recent methods succeed. Our empirical analysis shows that vanishing gradients caused by Gaussian process (GP) initialization schem","authors":["Papenmeier, Leonard","Poloczek, Matthias","Nardi, Luigi"],"url":"https://arxiv.org/abs/2502.09198","arxiv_id":"2502.09198","published":"2026-05-15"}],"history":{"events":[{"year":2024,"text":"Prime Minister of Slovakia Robert Fico is hospitalised after an assassination attempt.","url":"https://en.wikipedia.org/wiki/Prime_Minister_of_Slovakia"},{"year":2010,"text":"Three days before her seventeenth birthday, Jessica Watson arrived in Sydney after sailing non-stop and unassisted around the world.","url":"https://en.wikipedia.org/wiki/Jessica_Watson"},{"year":2004,"text":"Arsenal became the first football team in England's top flight to finish a season undefeated since Preston North End did so in 1888–1889.","url":"https://en.wikipedia.org/wiki/Arsenal_F.C."},{"year":2001,"text":"A runaway train loaded with hazardous chemicals traveled driverless for 66 miles (106 km) through Ohio before being stopped near Kenton.","url":"https://en.wikipedia.org/wiki/CSX_8888_incident"},{"year":1990,"text":"Vincent van Gogh's Portrait of Dr. Gachet was sold at auction at Christie's in New York for US$82.5 million, making it the world's most expensive painting at the time.","url":"https://en.wikipedia.org/wiki/Vincent_van_Gogh"},{"year":1972,"text":"The Ryukyu Islands were returned to Japan by the United States, and the U.S. occupation government was abolished.","url":"https://en.wikipedia.org/wiki/Ryukyu_Islands"},{"year":1970,"text":"Police opened fire during a confrontation with a group of Jackson State College students, killing two students and injuring twelve others.","url":"https://en.wikipedia.org/wiki/Jackson_State_killings"},{"year":1966,"text":"Disapproving of General Tôn Thất Đính's handling of the Buddhist Uprising, South Vietnamese prime minister Nguyễn Cao Kỳ ordered an attack on his forces and ousted Đính from his post.","url":"https://en.wikipedia.org/wiki/T%C3%B4n_Th%E1%BA%A5t_%C4%90%C3%ADnh"},{"year":1957,"text":"The United Kingdom tested its first hydrogen bomb over Malden Island in Operation Grapple.","url":"https://en.wikipedia.org/wiki/Thermonuclear_weapon"},{"year":1953,"text":"Don Murphy organized the first pinewood derby, an event for Cub Scouts of the Boy Scouts of America where wooden cars built by the scouts are raced.","url":"https://en.wikipedia.org/wiki/Pinewood_derby"},{"year":1945,"text":"The British Army directed fleeing Croatian soldiers to surrender to the Yugoslav Partisans, beginning the Bleiburg repatriations.","url":"https://en.wikipedia.org/wiki/British_Army"},{"year":1928,"text":"Mickey and Minnie Mouse made their film debuts in the animated cartoon Plane Crazy.","url":"https://en.wikipedia.org/wiki/Mickey_Mouse"},{"year":1916,"text":"Jesse Washington, a teenage African-American farmhand, was lynched in Waco, Texas.","url":"https://en.wikipedia.org/wiki/Lynching_of_Jesse_Washington"},{"year":1912,"text":"During a match, baseball star Ty Cobb enters the stands and assaults a fan who had heckled him, leading to his suspension.","url":"https://en.wikipedia.org/wiki/Ty_Cobb"},{"year":1911,"text":"Mexican Revolution: A force of Maderistas captured Torreón and proceeded to massacre 303 of the city's Chinese residents.","url":"https://en.wikipedia.org/wiki/Mexican_Revolution"},{"year":1904,"text":"Russo-Japanese War: The Japanese battleships Hatsuse and Yashima sank after striking several mines off Port Arthur, China.","url":"https://en.wikipedia.org/wiki/Russo-Japanese_War"},{"year":1891,"text":"Pope Leo XIII issued the encyclical Rerum novarum, which addressed the condition of the working classes and is considered to be the foundation of modern Catholic social teaching.","url":"https://en.wikipedia.org/wiki/Pope_Leo_XIII"},{"year":1869,"text":"Susan B. Anthony and Elizabeth Cady Stanton founded the National Woman Suffrage Association, breaking away from the American Equal Rights Association which they had also previously founded.","url":"https://en.wikipedia.org/wiki/Susan_B._Anthony"}],"births":[{"year":2006,"text":"Haerin, Korean singer","url":"https://en.wikipedia.org/wiki/Haerin"},{"year":2002,"text":"Chase Hudson, American internet celebrity, singer, actor","url":"https://en.wikipedia.org/wiki/Huddy_(musician)"},{"year":2000,"text":"Dayana Yastremska, Ukrainian tennis player","url":"https://en.wikipedia.org/wiki/Dayana_Yastremska"},{"year":1999,"text":"Anastasia Gasanova, Russian tennis player","url":"https://en.wikipedia.org/wiki/Anastasia_Gasanova"},{"year":1998,"text":"Lucrezia Stefanini, Italian tennis player","url":"https://en.wikipedia.org/wiki/Lucrezia_Stefanini"},{"year":1997,"text":"Ousmane Dembélé, French footballer","url":"https://en.wikipedia.org/wiki/Ousmane_Demb%C3%A9l%C3%A9"},{"year":1997,"text":"Scott Drinkwater, Australian rugby league player","url":"https://en.wikipedia.org/wiki/Scott_Drinkwater"},{"year":1996,"text":"Birdy, English singer-songwriter","url":"https://en.wikipedia.org/wiki/Birdy_(singer)"}],"deaths":[{"year":2025,"text":"Robert Walls, Australian footballer, coach, and sportscaster (born 1950)","url":"https://en.wikipedia.org/wiki/Robert_Walls"},{"year":2024,"text":"Kamla Beniwal, Indian politician (born 1927)","url":"https://en.wikipedia.org/wiki/Kamla_Beniwal"},{"year":2022,"text":"Frank Curry, Australian rugby league player and coach (born 1950)","url":"https://en.wikipedia.org/wiki/Frank_Curry"},{"year":2022,"text":"Kay Mellor, English actress (born 1951)","url":"https://en.wikipedia.org/wiki/Kay_Mellor"},{"year":2021,"text":"Oliver Gillie, British journalist and scientist (born 1937)","url":"https://en.wikipedia.org/wiki/Oliver_Gillie"},{"year":2020,"text":"Fred Willard, American actor, comedian, and writer (born 1933)","url":"https://en.wikipedia.org/wiki/Fred_Willard"},{"year":2017,"text":"Herbert R. Axelrod American tropical fish expert, publisher of pet books, and entrepreneur (born 1927)","url":"https://en.wikipedia.org/wiki/Herbert_R._Axelrod"},{"year":2016,"text":"Jelesko Grancharoff, Bulgarian-Australian resistance fighter and anarchist (born 1925)","url":"https://en.wikipedia.org/wiki/Jack_the_Anarchist"}]},"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."}