{"date":"2026-06-24","schema_version":1,"captured_at":"2026-08-25T23:13:31.129Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"2026 FIFA World Cup","views":789442,"rank":3,"extract":"The 2026 FIFA World Cup was the 23rd FIFA World Cup, the quadrennial international men's soccer championship contested by the national teams of the member associations of FIFA. 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Existing remedies (checkpointing, invertible architectures, or gradient-approximation methods such as randomized automatic differentiation) either add significant computation, impose architectural constraints, or require non-trivial code changes. We propose XConv, a ","authors":["Thatipelli, Anirudh","Sam, Jeffrey","Louboutin, Mathias","Siahkoohi, Ali","Wang, Rongrong","Herrmann, Felix J."],"url":"https://arxiv.org/abs/2106.06998","arxiv_id":"2106.06998","published":"2026-06-24"},{"title":"Subtyping patients with chronic disease using longitudinal BMI patterns","abstract":"Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of obesity identified by cross-sectional BMI recordings has been heavily studied, the role of BMI trajectories is much less explored. In this study, we use a machine-learning approach to subtype individuals' risk of developing 18 major chronic diseases by using their BMI t","authors":["Mottalib, Md Mozaharul","Jones-Smith, Jessica C","Sheridan, Bethany","Beheshti, Rahmatollah"],"url":"https://arxiv.org/abs/2111.05385","arxiv_id":"2111.05385","published":"2026-06-24"},{"title":"Temporal Transductive Inference for Few-Shot Video Object Segmentation","abstract":"Few-shot video object segmentation (FS-VOS) aims at segmenting video frames using a few labelled examples of classes not seen during initial training. In this paper, we present a simple but effective temporal transductive inference (TTI) approach that leverages temporal consistency in the unlabelled video frames during few-shot inference. Key to our approach is the use of both global and local temporal constraints. T","authors":["Siam, Mennatullah","Derpanis, Konstantinos G.","Wildes, Richard P."],"url":"https://arxiv.org/abs/2203.14308","arxiv_id":"2203.14308","published":"2026-06-24"},{"title":"Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition","abstract":"Sampled point and voxel methods are usually employed to downsample the dense events into sparse ones. After that, one popular way is to leverage a graph model which treats the sparse points/voxels as nodes and adopts graph neural networks (GNNs) to learn the representation of event data. Although good performance can be obtained, however, their results are still limited mainly due to two issues. (1) Existing event GN","authors":["Zhang, Yuxiang","Yuan, Chengguo","Wang, Xiao","Jiang, Bo","Tang, Jin"],"url":"https://arxiv.org/abs/2306.05239","arxiv_id":"2306.05239","published":"2026-06-24"},{"title":"Full-resolution MLPs Empower Medical Dense Prediction","abstract":"Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation. The most popular vision model, Convolutional Neural Networks (CNNs), has reached bottlenecks due to the intrinsic locality of convolution operations. Recently, transformers have been widely adopted for dense prediction for their capability to capture long-range visual dependen","authors":["Meng, Mingyuan","Xue, Yuxin","Feng, Dagan","Bi, Lei","Kim, Jinman"],"url":"https://arxiv.org/abs/2311.16707","arxiv_id":"2311.16707","published":"2026-06-24"},{"title":"Evaluation Metrics as Averaged Outcomes of Fair Gambles","abstract":"In the current practices of machine learning, the evaluation of forecasts has become a cornerstone of scientific progress. A multitude of evaluation metrics have been suggested and used to qualify &#34;good&#34; forecasts. What do those metrics share? How are they related? In this work, we use a protocol borrowed from game-theoretic probability to show that a large part of evaluation metrics can be viewed as averaged","authors":["Derr, Rabanus","Williamson, Robert C."],"url":"https://arxiv.org/abs/2401.14483","arxiv_id":"2401.14483","published":"2026-06-24"},{"title":"Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse","abstract":"Whataboutism, a potent tool for disrupting narratives and sowing distrust, remains under-explored in quantitative NLP research. Moreover, past work has not distinguished its use as a strategy for misinformation and propaganda from its use as a tool for pragmatic and semantic framing. We introduce new datasets from Twitter and YouTube, revealing overlaps as well as distinctions between whataboutism, propaganda, and th","authors":["Phi, Khiem","Faramarzi, Noushin Salek","Wang, Chenlu","Banerjee, Ritwik"],"url":"https://arxiv.org/abs/2402.09934","arxiv_id":"2402.09934","published":"2026-06-24"},{"title":"A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network","abstract":"Binary neural networks utilize 1-bit quantized weights and activations to reduce both the model's storage demands and computational burden. However, advanced binary architectures still incorporate millions of inefficient and nonhardware-friendly full-precision multiplication operations. A&B BNN is proposed to directly remove part of the multiplication operations in a traditional BNN and replace the rest with ","authors":["Ma, Ruichen","Qiao, Guanchao","Liu, Yian","Meng, Liwei","Ning, Ning","Liu, Yang"],"url":"https://arxiv.org/abs/2403.03739","arxiv_id":"2403.03739","published":"2026-06-24"},{"title":"Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering","abstract":"In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without options to mimic clinical scenarios, along with clinician-approved reasoned answers. Additionally, we implement a prompt driven by Chain of Thought (CoT) reasoning, CLINICR, to mirror the prospective process of incremental reasoning, reaching a correct response to medical ques","authors":["Nachane, Saeel Sandeep","Gramopadhye, Ojas","Chanda, Prateek","Ramakrishnan, Ganesh","Jadhav, Kshitij Sharad","Nandwani, Yatin"],"url":"https://arxiv.org/abs/2403.04890","arxiv_id":"2403.04890","published":"2026-06-24"},{"title":"Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization","abstract":"Solving large-scale multistage stochastic programming (MSP) problems poses a significant challenge as commonly used stagewise decomposition algorithms, including stochastic dual dynamic programming (SDDP), face growing time complexity as the subproblem size and problem count increase. Traditional approaches approximate the value functions as piecewise linear convex functions by incrementally accumulating subgradient ","authors":["Kim, Chanyeong","Park, Jongwoong","Bae, Hyunglip","Kim, Woo Chang"],"url":"https://arxiv.org/abs/2404.02583","arxiv_id":"2404.02583","published":"2026-06-24"},{"title":"Configurable Holography: Towards Display and Scene Adaptation","abstract":"Rendering holograms for holographic displays is often an iterative and computationally costly process. Emerging learned holography methods have alleviated this bottleneck by enabling fast hologram rendering with improved reconstruction quality. However, existing methods still depend on fixed display hardware and scene parameters, requiring retraining for each new configuration. This limits rapid adaptation to differe","authors":["Zhan, Yicheng","Shi, Liang","Matusik, Wojciech","Sun, Qi","Akşit, Kaan"],"url":"https://arxiv.org/abs/2405.01558","arxiv_id":"2405.01558","published":"2026-06-24"},{"title":"Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian","abstract":"There has been a surge in the development of various Large Language Models (LLMs). However, text generation for languages other than English often faces significant challenges, including poor generation quality and reduced computational performance due to the disproportionate representation of tokens in the model's vocabulary. In this work, we address these issues by developing a pipeline for the adaptation of En","authors":["Nikolich, Aleksandr","Korolev, Konstantin","Bratchikov, Sergei","Kiselev, Igor","Shelmanov, Artem"],"url":"https://arxiv.org/abs/2405.13929","arxiv_id":"2405.13929","published":"2026-06-24"},{"title":"Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts","abstract":"Continuous-Time Dynamic Graphs (CTDGs) enable fine-grained modeling of evolving relational systems. However, most existing CTDG representation learning methods are tailored to in-distribution settings and exhibit limited robustness under out-of-distribution (OOD) shifts. Although recent causal approaches learn invariant representations via interventions, they are primarily designed for static or discrete-time graphs ","authors":["Fang, Lanting","Yang, Yulian","Zhang, Yawei","Feng, Shanshan","Feng, Kaiyu","Yuan, Hanning"],"url":"https://arxiv.org/abs/2405.19062","arxiv_id":"2405.19062","published":"2026-06-24"},{"title":"Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations","abstract":"Using partial knowledge of a quantum state to control multiqubit entanglement is a largely unexplored paradigm in the emerging field of quantum interactive dynamics with the potential to address outstanding challenges in quantum state preparation and compression, quantum control, and quantum complexity. We present a deep reinforcement learning (RL) approach using an actor-critic algorithm for constructing short disen","authors":["Tashev, Pavel","Petrov, Stefan","Diaz, Matthew T.","Metz, Friederike","Green, Alaina M.","Linke, Norbert M."],"url":"https://arxiv.org/abs/2406.07884","arxiv_id":"2406.07884","published":"2026-06-24"},{"title":"Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum","abstract":"Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least $\\mathcal{O}(\\varepsilon^{-4})$ sample complexity to find an $\\varepsilon$-stationary point. Some works indicate that this complexity can be improved to $\\mathcal{O}(\\varepsilon^{-3})$ when the stochastic loss gradient is Lipschitz continuous. The question of achieving e","authors":["Cai, Haoyuan","Alghunaim, Sulaiman A.","Sayed, Ali H."],"url":"https://arxiv.org/abs/2406.13041","arxiv_id":"2406.13041","published":"2026-06-24"},{"title":"Mamba-FSCIL: Dynamic Adaptation with Selective State Space Model for Few-Shot Class-Incremental Learning","abstract":"Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes from limited examples while preserving knowledge of previously learned classes. Existing methods face a critical dilemma: static architectures rely on a constant parameter space to learn from data that arrive sequentially, making them prone to overfitting to the current session, while dynamic architectures continually expand the par","authors":["Li, Xiaojie","Yang, Yibo","Wu, Jianlong","Yu, Yue","Yang, Ming-Hsuan","Nie, Liqiang"],"url":"https://arxiv.org/abs/2407.06136","arxiv_id":"2407.06136","published":"2026-06-24"},{"title":"Adversarial dynamical systems characterize when data-driven learning succeeds or fails","abstract":"Many systems resist analytical modeling, making data-driven inference of dynamics important. Yet data-driven methods can fail to converge or generalize, leaving open a central question: When can system behavior be learned reliably from data, and when is such learning impossible? We answer this question using adversarial dynamical systems to identify the boundary between accessible and inaccessible regimes. In Koopman","authors":["Colbrook, Matthew J.","Mezić, Igor","Stepanenko, Alexei"],"url":"https://arxiv.org/abs/2407.06312","arxiv_id":"2407.06312","published":"2026-06-24"},{"title":"Novel clustered federated learning based on local loss","abstract":"This paper proposes LCFL, a novel clustering metric for evaluating clients' data distributions in federated learning. LCFL aligns with federated learning requirements, accurately assessing client-to-client variations in data distribution. It offers advantages over existing clustered federated learning methods, addressing privacy concerns, improving applicability to non-convex models, and providing more accurate c","authors":["Gu, Endong","Chen, Yongxin","Wen, Hao","Cai, Xingju","Han, Deren"],"url":"https://arxiv.org/abs/2407.09360","arxiv_id":"2407.09360","published":"2026-06-24"},{"title":"The Dual Imperative: Innovation and Regulation in the AI Era","abstract":"This article addresses the societal costs associated with the lack of regulation in Artificial Intelligence and proposes a framework combining innovation and regulation. Over fifty years of AI research, catalyzed by declining computing costs and the proliferation of data, have propelled AI into the mainstream, promising significant economic benefits. Yet, this rapid adoption underscores risks, from bias amplification","authors":["Carvão, Paulo"],"url":"https://arxiv.org/abs/2407.12690","arxiv_id":"2407.12690","published":"2026-06-24"},{"title":"The Role of Temporal Hierarchy in Spiking Neural Networks","abstract":"Spiking Neural Networks (SNNs) have the potential for rich spatio-temporal signal processing thanks to exploiting both spatial and temporal parameters. The temporal dynamics such as time constants of the synapses and neurons and delays have been recently shown to have computational benefits that help reduce the overall number of parameters required in the network and increase the accuracy of the SNNs in solving tempo","authors":["Moro, Filippo","Aceituno, Pau Vilimelis","Kriener, Laura","Payvand, Melika"],"url":"https://arxiv.org/abs/2407.18838","arxiv_id":"2407.18838","published":"2026-06-24"},{"title":"When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments","abstract":"Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroeconomics, policy changes, company fundamentals, and global events)? These factors, which frequently influence trading behaviors, are critical elements in the quest for maximizing investors' profits. Our work attempts to solve this problem through large language model based ","authors":["Zhang, Chong","Liu, Xinyi","Zhang, Zhongmou","Jin, Mingyu","Li, Lingyao","Wang, Zhenting"],"url":"https://arxiv.org/abs/2407.18957","arxiv_id":"2407.18957","published":"2026-06-24"},{"title":"Generative AI for automatic topic labelling","abstract":"Topic Modeling has become a prominent tool for the study of scientific fields, as they allow for a large scale interpretation of research trends. Nevertheless, the output of these models is structured as a list of keywords which requires a manual interpretation for the labelling. This paper proposes to assess the reliability of three LLMs, namely flan, GPT-4o, and GPT-4 mini for topic labelling. Drawing on previous r","authors":["Kozlowski, Diego","Pradier, Carolina","Benz, Pierre"],"url":"https://arxiv.org/abs/2408.07003","arxiv_id":"2408.07003","published":"2026-06-24"},{"title":"Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text","abstract":"Social scientists quickly adopted large language models due to their ability to annotate documents without supervised training, an ability known as zero-shot learning. However, due to their compute demands, cost, and often proprietary nature, these models are often at odds with replication and open science standards. This paper introduces the Political DEBATE (DeBERTa Algorithm for Textual Entailment) language models","authors":["Burnham, Michael","Kahn, Kayla","Wang, Ryan Yank","Peng, Rachel X."],"url":"https://arxiv.org/abs/2409.02078","arxiv_id":"2409.02078","published":"2026-06-24"},{"title":"CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark","abstract":"AI agents have the potential to aid users on a variety of consequential tasks, including conducting scientific research. To spur the development of useful agents, we need benchmarks that are challenging, but more crucially, directly correspond to real-world tasks of interest. This paper introduces such a benchmark, designed to measure the accuracy of AI agents in tackling a crucial yet surprisingly challenging aspect","authors":["Siegel, Zachary S.","Kapoor, Sayash","Nadgir, Nitya","Stroebl, Benedikt","Narayanan, Arvind"],"url":"https://arxiv.org/abs/2409.11363","arxiv_id":"2409.11363","published":"2026-06-24"},{"title":"Neural delay differential equations: learning non-Markovian closures for partially known dynamical systems","abstract":"Recent advances in learning dynamical systems from data have shown significant promise. However, many existing methods assume access to the full state of the system -- an assumption that is rarely satisfied in practice, where systems are typically monitored through a limited number of sensors, leading to partial observability. To address this challenge, we draw inspiration from the Mori-Zwanzig formalism, which provi","authors":["Monsel, Thibault","Semeraro, Onofrio","Mathelin, Lionel","Charpiat, Guillaume"],"url":"https://arxiv.org/abs/2410.02843","arxiv_id":"2410.02843","published":"2026-06-24"}],"history":{"events":[{"year":2021,"text":"A portion of a 12-story condominium building collapsed (aftermath pictured) in Surfside, Florida, United States, killing 98 people and injuring 11 others.","url":"https://en.wikipedia.org/wiki/Surfside_condominium_collapse"},{"year":2010,"text":"Julia Gillard was sworn in as the first female prime minister of Australia after incumbent Kevin Rudd declined to contest a leadership spill in the Labor Party.","url":"https://en.wikipedia.org/wiki/Julia_Gillard"},{"year":2010,"text":"John Isner defeated Nicolas Mahut at the Wimbledon Championships, concluding the longest match in tennis history, which lasted 11 hours and 5 minutes over three days.","url":"https://en.wikipedia.org/wiki/John_Isner"},{"year":1989,"text":"Following the Tiananmen Square massacre, the 13th Central Committee of the Chinese Communist Party appointed Jiang Zemin as general secretary in place of Zhao Ziyang.","url":"https://en.wikipedia.org/wiki/1989_Tiananmen_Square_protests_and_massacre"},{"year":1943,"text":"Amid racial tensions, U.S. Army military police shot and killed a black serviceman after a confrontation at a pub in Bamber Bridge, England.","url":"https://en.wikipedia.org/wiki/United_States_Army"},{"year":1940,"text":"Second World War: The British Army carried out Operation Collar, its first commando raid into German-occupied France.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1939,"text":"The first of the Thai cultural mandates was issued, officially changing the country's name from Siam to Thailand.","url":"https://en.wikipedia.org/wiki/Thai_cultural_mandates"},{"year":1937,"text":"The U.S. Navy's first two fast battleships, North Carolina and Washington, of the North Carolina class, were respectively ordered from the New York and Philadelphia Naval Shipyards.","url":"https://en.wikipedia.org/wiki/Fast_battleship"},{"year":1932,"text":"A group of military officers and civilians engineered a bloodless coup in Siam, ending the absolute rule of the Chakri dynasty.","url":"https://en.wikipedia.org/wiki/Siamese_revolution_of_1932"},{"year":1880,"text":"\"O Canada\", the present-day national anthem of Canada, was first performed in Quebec City during a Saint-Jean-Baptiste Day banquet.","url":"https://en.wikipedia.org/wiki/O_Canada"},{"year":1812,"text":"Napoleonic Wars: Led by Napoleon, the French Grande Armée crossed the Neman, beginning their invasion of Russia.","url":"https://en.wikipedia.org/wiki/Napoleonic_Wars"},{"year":1724,"text":"On the Feast of St. John the Baptist, Bach led the first performance of Christ unser Herr zum Jordan kam, BWV 7, the third cantata of his chorale cantata cycle.","url":"https://en.wikipedia.org/wiki/Nativity_of_John_the_Baptist"},{"year":1717,"text":"The first Grand Lodge of Freemasonry, the Premier Grand Lodge of England, was founded in London.","url":"https://en.wikipedia.org/wiki/Grand_Lodge"},{"year":1559,"text":"The Book of Common Prayer, a major component of the Elizabethan religious settlement, was introduced as the liturgy of the Church of England through the Act of Uniformity 1558.","url":"https://en.wikipedia.org/wiki/Book_of_Common_Prayer_(1559)"},{"year":1374,"text":"An outbreak of dancing mania, in which crowds of people danced themselves to exhaustion, began in Aachen (in present-day Germany) before spreading to other parts of Europe.","url":"https://en.wikipedia.org/wiki/Dancing_mania"},{"year":1340,"text":"Hundred Years' War: The English fleet commanded by Edward III almost completely destroyed the French fleet at the Battle of Sluys.","url":"https://en.wikipedia.org/wiki/Hundred_Years'_War"},{"year":1314,"text":"In the decisive battle of the First War of Scottish Independence, Scottish forces led by Robert the Bruce defeated English troops under Edward II near Bannockburn, Scotland.","url":"https://en.wikipedia.org/wiki/First_War_of_Scottish_Independence"},{"year":474,"text":"Western Roman emperor Glycerius, who was not recognized by his Eastern counterpart Leo I, was forced to abdicate.","url":"https://en.wikipedia.org/wiki/Western_Roman_Empire"}],"births":[{"year":2008,"text":"Mathis Jangéal, French footballer","url":"https://en.wikipedia.org/wiki/Mathis_Jang%C3%A9al"},{"year":2000,"text":"Nehuén Pérez, Argentine footballer","url":"https://en.wikipedia.org/wiki/Nehu%C3%A9n_P%C3%A9rez"},{"year":1999,"text":"Darwin Núñez, Uruguayan footballer","url":"https://en.wikipedia.org/wiki/Darwin_N%C3%BA%C3%B1ez"},{"year":1998,"text":"Federico Gatti, Italian footballer","url":"https://en.wikipedia.org/wiki/Federico_Gatti"},{"year":1998,"text":"Pierre-Luc Dubois, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Pierre-Luc_Dubois"},{"year":1996,"text":"Duki, Argentine rapper","url":"https://en.wikipedia.org/wiki/Duki_(rapper)"},{"year":1992,"text":"David Alaba, Austrian footballer","url":"https://en.wikipedia.org/wiki/David_Alaba"},{"year":1991,"text":"Yasmin Paige, English actress","url":"https://en.wikipedia.org/wiki/Yasmin_Paige"}],"deaths":[{"year":2025,"text":"Bobby Sherman, American singer-songwriter and actor (born 1943)","url":"https://en.wikipedia.org/wiki/Bobby_Sherman"},{"year":2024,"text":"Shifty Shellshock, American vocalist (born 1974)","url":"https://en.wikipedia.org/wiki/Shifty_Shellshock"},{"year":2021,"text":"Benigno Aquino III, 15th President of the Philippines (born 1960)","url":"https://en.wikipedia.org/wiki/Benigno_Aquino_III"},{"year":2021,"text":"Trần Thiện Khiêm, 7th Prime Minister of South Vietnam and army officer (born 1925)","url":"https://en.wikipedia.org/wiki/Tr%E1%BA%A7n_Thi%E1%BB%87n_Khi%C3%AAm"},{"year":2015,"text":"Cristiano Araújo, Brazilian singer-songwriter (born 1986)","url":"https://en.wikipedia.org/wiki/Cristiano_Ara%C3%BAjo"},{"year":2015,"text":"Mario Biaggi, American police officer, politician and criminal (born 1917)","url":"https://en.wikipedia.org/wiki/Mario_Biaggi"},{"year":2015,"text":"Marva Collins, American author and educator (born 1936)","url":"https://en.wikipedia.org/wiki/Marva_Collins"},{"year":2015,"text":"Susan Ahn Cuddy, American lieutenant (born 1915)","url":"https://en.wikipedia.org/wiki/Susan_Ahn_Cuddy"}]},"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 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Every item links to its source."}