{"date":"2026-01-27","schema_version":1,"captured_at":"2026-08-25T23:25:38.464Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Sam Darnold","views":598462,"rank":3,"extract":"Samuel Richard Darnold is an American professional football quarterback for the Seattle Seahawks of the National Football League (NFL). 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In big data applications, however, many clustering algorithms are infeasible due to their high memory requirements and/or unfavorable runtime complexity. In contrast, Contraction Clustering (RASTER) is a single-pass algorithm for identifying density-based clusters with linear time complexity. Due to its favorable runtime and the f","authors":["Ulm, Gregor","Smith, Simon","Nilsson, Adrian","Gustavsson, Emil","Jirstrand, Mats"],"url":"https://arxiv.org/abs/1907.03620","arxiv_id":"1907.03620","published":"2026-01-27"},{"title":"Energy-Aware DNN Graph Optimization","abstract":"Unlike existing work in deep neural network (DNN) graphs optimization for inference performance, we explore DNN graph optimization for energy awareness and savings for power- and resource-constrained machine learning devices. We present a method that allows users to optimize energy consumption or balance between energy and inference performance for DNN graphs. This method efficiently searches through the space of equ","authors":["Wang, Yu","Ge, Rong","Qiu, Shuang"],"url":"https://arxiv.org/abs/2005.05837","arxiv_id":"2005.05837","published":"2026-01-27"},{"title":"Inferring manifolds using Gaussian processes","abstract":"It is often of interest to infer lower-dimensional structure underlying complex data. As a flexible class of non-linear structures, it is common to focus on Riemannian manifolds. Most existing manifold learning algorithms replace the original data with lower-dimensional coordinates without providing an estimate of the manifold or using the manifold to denoise the original data. This article proposes a new methodology","authors":["Dunson, David B","Wu, Nan"],"url":"https://arxiv.org/abs/2110.07478","arxiv_id":"2110.07478","published":"2026-01-27"},{"title":"GFlowNet Foundations","abstract":"Generative Flow Networks (GFlowNets) have been introduced as a method to sample a diverse set of candidates in an active learning context, with a training objective that makes them approximately sample in proportion to a given reward function. In this paper, we show a number of additional theoretical properties of GFlowNets. They can be used to estimate joint probability distributions and the corresponding marginal d","authors":["Bengio, Yoshua","Lahlou, Salem","Deleu, Tristan","Hu, Edward J.","Tiwari, Mo","Bengio, Emmanuel"],"url":"https://arxiv.org/abs/2111.09266","arxiv_id":"2111.09266","published":"2026-01-27"},{"title":"Detecting Dysfluencies in Stuttering Therapy Using wav2vec 2.0","abstract":"Stuttering is a varied speech disorder that harms an individual's communication ability. Persons who stutter (PWS) often use speech therapy to cope with their condition. Improving speech recognition systems for people with such non-typical speech or tracking the effectiveness of speech therapy would require systems that can detect dysfluencies while at the same time being able to detect speech techniques acquired","authors":["Bayerl, Sebastian P.","Wagner, Dominik","Nöth, Elmar","Riedhammer, Korbinian"],"url":"https://arxiv.org/abs/2204.03417","arxiv_id":"2204.03417","published":"2026-01-27"},{"title":"PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images","abstract":"We present PyMAF-X, a regression-based approach to recovering parametric full-body models from monocular images. This task is very challenging since minor parametric deviation may lead to noticeable misalignment between the estimated mesh and the input image. Moreover, when integrating part-specific estimations into the full-body model, existing solutions tend to either degrade the alignment or produce unnatural wris","authors":["Zhang, Hongwen","Tian, Yating","Zhang, Yuxiang","Li, Mengcheng","An, Liang","Sun, Zhenan"],"url":"https://arxiv.org/abs/2207.06400","arxiv_id":"2207.06400","published":"2026-01-27"},{"title":"CloSET: Modeling Clothed Humans on Continuous Surface with Explicit Template Decomposition","abstract":"Creating animatable avatars from static scans requires the modeling of clothing deformations in different poses. Existing learning-based methods typically add pose-dependent deformations upon a minimally-clothed mesh template or a learned implicit template, which have limitations in capturing details or hinder end-to-end learning. In this paper, we revisit point-based solutions and propose to decompose explicit garme","authors":["Zhang, Hongwen","Lin, Siyou","Shao, Ruizhi","Zhang, Yuxiang","Zheng, Zerong","Huang, Han"],"url":"https://arxiv.org/abs/2304.03167","arxiv_id":"2304.03167","published":"2026-01-27"},{"title":"Structured and Fast Optimization: The Kronecker SGD Algorithm","abstract":"Stochastic gradient descent (SGD) now acts as a fundamental part of optimization in current machine learning. Meanwhile, deep learning architectures have shown outstanding performance in a wide range of fields, such as natural language processing, bioinformatics, and computer vision. Nevertheless, as the parameter size $d$ increases, these models encounter serious efficiency challenges. Previous studies show that the","authors":["Song, Zhao","Yue, Song"],"url":"https://arxiv.org/abs/2305.08001","arxiv_id":"2305.08001","published":"2026-01-27"},{"title":"Patient Outcome Predictions Improve Operations at a Large Hospital Network","abstract":"Problem definition: Access to accurate predictions of patients' outcomes can enhance medical staff's decision-making, which ultimately benefits all stakeholders in the hospitals. A large hospital network in the US has been collaborating with academics and consultants to predict short-term and long-term outcomes for all inpatients across their seven hospitals. Methodology/results: We develop machine learning m","authors":["Na, Liangyuan","Carballo, Kimberly Villalobos","Pauphilet, Jean","Haddad-Sisakht, Ali","Kombert, Daniel","Boisjoli-Langlois, Melissa"],"url":"https://arxiv.org/abs/2305.15629","arxiv_id":"2305.15629","published":"2026-01-27"},{"title":"Near-Optimal Partially Observable Reinforcement Learning with Partial Online State Information","abstract":"Partially observable Markov decision processes (POMDPs) are a general framework for sequential decision-making under latent state uncertainty, yet learning in POMDPs is intractable in the worst case. Motivated by sensing and probing constraints in practice, we study how much online state information (OSI) is sufficient to enable efficient learning guarantees. We formalize a model in which the learner can query only p","authors":["Shi, Ming","Liang, Yingbin","Shroff, Ness B."],"url":"https://arxiv.org/abs/2306.08762","arxiv_id":"2306.08762","published":"2026-01-27"},{"title":"SAF-Net: Self-Attention Fusion Network for Myocardial Infarction Detection using Multi-View Echocardiography","abstract":"Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is substantial to prevent progressive damage to the myocardium. In this study, we propose a novel view-fusion model named self-attention fusion network (SAF-Net) to detect MI from multi-view echocardiography recordings. The proposed framework utilizes apical 2-chamber (A2C) and apical 4-chamber (A4C) view echoca","authors":["Adalioglu, Ilke","Ahishali, Mete","Degerli, Aysen","Kiranyaz, Serkan","Gabbouj, Moncef"],"url":"https://arxiv.org/abs/2309.15520","arxiv_id":"2309.15520","published":"2026-01-27"},{"title":"ELIP: Efficient Discriminative Language-Image Pre-training with Fewer Vision Tokens","abstract":"Learning a versatile language-image model is computationally prohibitive under a limited computing budget. This paper delves into the \\emph{efficient language-image pre-training}, an area that has received relatively little attention despite its importance in reducing computational cost and footprint. To that end, we propose a vision token pruning and merging method ELIP, to remove less influential tokens based on th","authors":["Guo, Yangyang","Zhang, Haoyu","Wong, Yongkang","Nie, Liqiang","Kankanhalli, Mohan"],"url":"https://arxiv.org/abs/2309.16738","arxiv_id":"2309.16738","published":"2026-01-27"},{"title":"Saliency-Bench: A Comprehensive Benchmark for Evaluating Visual Explanations","abstract":"Explainable AI (XAI) has gained significant attention for providing insights into the decision-making processes of deep learning models, particularly for image classification tasks through visual explanations visualized by saliency maps. Despite their success, challenges remain due to the lack of annotated datasets and standardized evaluation pipelines. In this paper, we introduce Saliency-Bench, a novel benchmark su","authors":["Zhang, Yifei","Song, James","Gu, Siyi","Jiang, Tianxu","Pan, Bo","Bai, Guangji"],"url":"https://arxiv.org/abs/2310.08537","arxiv_id":"2310.08537","published":"2026-01-27"},{"title":"Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization","abstract":"The graduated optimization approach is a method for finding global optimal solutions for nonconvex functions by using a function smoothing operation with stochastic noise. This paper makes three contributions regarding graduated optimization. First, we extend the definition of function smoothing that is traditionally achieved through convolution with Gaussian noise and characterize for the first time function smoothi","authors":["Sato, Naoki","Iiduka, Hideaki"],"url":"https://arxiv.org/abs/2311.08745","arxiv_id":"2311.08745","published":"2026-01-27"},{"title":"Stochastic-Constrained Stochastic Optimization with Markovian Data","abstract":"This paper considers stochastic-constrained stochastic optimization where the stochastic constraint is to satisfy that the expectation of a random function is below a certain threshold. In particular, we study the setting where data samples are drawn from a Markov chain and thus are not independent and identically distributed. We generalize the drift-plus-penalty framework, a primal-dual stochastic gradient method de","authors":["Kim, Yeongjong","Lee, Dabeen"],"url":"https://arxiv.org/abs/2312.04312","arxiv_id":"2312.04312","published":"2026-01-27"},{"title":"Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference","abstract":"Surrogate models are statistical or conceptual approximations for more complex simulation models. In this context, it is crucial to propagate the uncertainty induced by limited simulation budget and surrogate approximation error to predictions, inference, and subsequent decision-relevant quantities. However, quantifying and then propagating the uncertainty of surrogates is usually limited to special analytic cases or","authors":["Reiser, Philipp","Aguilar, Javier Enrique","Guthke, Anneli","Bürkner, Paul-Christian"],"url":"https://arxiv.org/abs/2312.05153","arxiv_id":"2312.05153","published":"2026-01-27"},{"title":"Inconsistency Masks: Harnessing Model Disagreement for Stable Semi-Supervised Segmentation","abstract":"A primary challenge in semi-supervised learning (SSL) for segmentation is the confirmation bias from noisy pseudo-labels, which destabilizes training and degrades performance. We propose Inconsistency Masks (IM), a framework that reframes model disagreement not as noise to be averaged away, but as a valuable signal for identifying uncertainty. IM leverages an ensemble of teacher models to generate a mask that explici","authors":["Vorndran, Michael R. H.","Roeck, Bernhard F."],"url":"https://arxiv.org/abs/2401.14387","arxiv_id":"2401.14387","published":"2026-01-27"},{"title":"Sound event localization and classification using WASN in Outdoor Environment","abstract":"Deep learning-based sound event localization and classification is an emerging research area within wireless acoustic sensor networks. However, current methods for sound event localization and classification typically rely on a single microphone array, making them susceptible to signal attenuation and environmental noise, which limits their monitoring range. Moreover, methods using multiple microphone arrays often fo","authors":["Zhang, Dongzhe","Chen, Jianfeng","Bai, Jisheng","Wang, Mou","Shi, Dongyuan","Niu, Qixiang"],"url":"https://arxiv.org/abs/2403.20130","arxiv_id":"2403.20130","published":"2026-01-27"},{"title":"A Multimodal Feature Distillation with Mamba-Transformer Network for Brain Tumor Segmentation with Incomplete Modalities","abstract":"Existing brain tumor segmentation methods usually utilize multiple Magnetic Resonance Imaging (MRI) modalities in brain tumor images for segmentation, which can achieve better segmentation performance. However, in clinical applications, some modalities are often missing due to resource constraints, resulting in significant performance degradation for methods that rely on complete modality segmentation. In this paper,","authors":["Kang, Ming","Ting, Fung Fung","Saw, Shier Nee","Phan, Raphaël C. -W.","Ge, Zongyuan","Ting, Chee-Ming"],"url":"https://arxiv.org/abs/2404.14019","arxiv_id":"2404.14019","published":"2026-01-27"},{"title":"Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond","abstract":"The softmax activation function plays a crucial role in the success of large language models (LLMs), particularly in the self-attention mechanism of the widely adopted Transformer architecture. However, the underlying learning dynamics that contribute to the effectiveness of softmax remain largely unexplored. As a step towards better understanding, this paper provides a theoretical study of the optimization and gener","authors":["Cao, Yang","Liang, Yingyu","Shi, Zhenmei","Song, Zhao"],"url":"https://arxiv.org/abs/2405.03251","arxiv_id":"2405.03251","published":"2026-01-27"},{"title":"Adversarial Robustness Guarantees for Quantum Classifiers","abstract":"Despite their ever more widespread deployment throughout society, machine learning algorithms remain critically vulnerable to being spoofed by subtle adversarial tampering with their input data. The prospect of near-term quantum computers being capable of running {quantum machine learning} (QML) algorithms has therefore generated intense interest in their adversarial vulnerability. Here we show that quantum propertie","authors":["Dowling, Neil","West, Maxwell T.","Southwell, Angus","Nakhl, Azar C.","Sevior, Martin","Usman, Muhammad"],"url":"https://arxiv.org/abs/2405.10360","arxiv_id":"2405.10360","published":"2026-01-27"},{"title":"Training Tensor Attention Efficiently: From Cubic to Almost Linear Time","abstract":"Tensor Attention, a multi-view attention that is able to capture high-order correlations among multiple modalities, can overcome the representational limitations of classical matrix attention. However, the $O(n^3)$ time complexity of tensor attention poses a significant obstacle to its utilization in transformers, where $n$ is the input sequence length. In this work, we prove that the backward gradient of tensor atte","authors":["Cao, Yang","Liang, Yingyu","Shi, Zhenmei","Song, Zhao"],"url":"https://arxiv.org/abs/2405.16411","arxiv_id":"2405.16411","published":"2026-01-27"},{"title":"Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA","abstract":"Long-form videos that span across wide temporal intervals are highly information redundant and contain multiple distinct events or entities that are often loosely related. Therefore, when performing long-form video question answering (LVQA), all information necessary to generate a correct response can often be contained within a small subset of frames. Recent literature leverage large language models (LLMs) in LVQA b","authors":["Park, Jongwoo","Ranasinghe, Kanchana","Kahatapitiya, Kumara","Ryu, Wonjeong","Kim, Donghyun","Ryoo, Michael S."],"url":"https://arxiv.org/abs/2406.09396","arxiv_id":"2406.09396","published":"2026-01-27"},{"title":"Exploring LGBTQ+ Bias in Generative AI Answers across Different Country and Religious Contexts","abstract":"Previous discussions have highlighted the need for generative AI tools to become more culturally sensitive, yet often neglect the complexities of handling content about minorities, who are perceived differently across cultures and religions. Our study examined how two generative AI systems respond to homophobic statements with varying cultural and religious context information. Findings showed ChatGPT 3.5's repli","authors":["Vicsek, Lilla","Vancsó, Anna","Zajko, Mike","Takacs, Judit"],"url":"https://arxiv.org/abs/2407.03473","arxiv_id":"2407.03473","published":"2026-01-27"},{"title":"FeatureSORT: Essential Features for Effective Tracking","abstract":"We introduce FeatureSORT, a simple yet effective online multiple object tracker that reinforces the DeepSORT baseline with a redesigned detector and additional feature cues. In contrast to conventional detectors that only provide bounding boxes, our modified YOLOX architecture is extended to output multiple appearance attributes, including clothing color, clothing style, and motion direction, alongside the bounding b","authors":["Hashempoor, Hamidreza","Koikara, Rosemary","Hwang, Yu Dong"],"url":"https://arxiv.org/abs/2407.04249","arxiv_id":"2407.04249","published":"2026-01-27"}],"history":{"events":[{"year":2011,"text":"Arab Spring: The Yemeni Revolution began as more than 16,000 protesters demonstrated in Sanaa to demand governmental changes.","url":"https://en.wikipedia.org/wiki/Arab_Spring"},{"year":2011,"text":"Astronomers documented H1504+65, a white dwarf in Ursa Minor (chart pictured) with the hottest surface temperature known at the time, at 200,000 kelvins (360,000 °F).","url":"https://en.wikipedia.org/wiki/H1504%2B65"},{"year":2010,"text":"Porfirio Lobo Sosa became the new president of Honduras, ending a constitutional crisis that had begun in 2009 when Manuel Zelaya was forcibly removed from office.","url":"https://en.wikipedia.org/wiki/Porfirio_Lobo_Sosa"},{"year":2003,"text":"The first selections for the United States National Recording Registry were announced by the Library of Congress.","url":"https://en.wikipedia.org/wiki/National_Recording_Registry"},{"year":1996,"text":"Mahamane Ousmane, the first democratically elected president of Niger, was deposed by Colonel Ibrahim Baré Maïnassara in a military coup d'état.","url":"https://en.wikipedia.org/wiki/Mahamane_Ousmane"},{"year":1980,"text":"Six American diplomats who had evaded capture in the Iran hostage crisis escaped with the help of Canadian government officials to Zürich, Switzerland.","url":"https://en.wikipedia.org/wiki/Iran_hostage_crisis"},{"year":1967,"text":"A fire during a launch simulation for the Apollo 1 mission at Cape Kennedy killed astronauts Gus Grissom, Ed White and Roger Chaffee.","url":"https://en.wikipedia.org/wiki/Apollo_1"},{"year":1965,"text":"South Vietnamese prime minister Trần Văn Hương was removed by the military junta of Nguyễn Khánh.","url":"https://en.wikipedia.org/wiki/Tr%E1%BA%A7n_V%C4%83n_H%C6%B0%C6%A1ng"},{"year":1945,"text":"The Soviet Red Army liberated about 7,000 prisoners left behind by the Nazis in Auschwitz concentration camp.","url":"https://en.wikipedia.org/wiki/Red_Army"},{"year":1927,"text":"A contaminated diphtheria vaccine was used in an Australian immunisation program, leading to the deaths of twelve children and the suspension of immunisation programs in several countries.","url":"https://en.wikipedia.org/wiki/Bundaberg_tragedy"},{"year":1869,"text":"Former members of the overthrown Tokugawa shogunate proclaimed Japan's second-largest island, Hokkaido, to be the independent Republic of Ezo.","url":"https://en.wikipedia.org/wiki/Tokugawa_shogunate"},{"year":1825,"text":"On the advice of John C. Calhoun, President James Monroe asked Congress to organize Indian Territory (map pictured) west of the Mississippi River, laying the groundwork for Indian removal in the United States.","url":"https://en.wikipedia.org/wiki/John_C._Calhoun"},{"year":1799,"text":"French Revolutionary Wars: In the Macau Incident, French and Spanish warships encountered a British Royal Navy escort squadron in the Wanshan Archipelago; subsequent events, including which side retreated, were disputed by the commanders present.","url":"https://en.wikipedia.org/wiki/French_Revolutionary_Wars"},{"year":1785,"text":"The University of Georgia, the oldest state-chartered public university in the United States, was founded.","url":"https://en.wikipedia.org/wiki/University_of_Georgia"},{"year":1726,"text":"J. S. Bach led the first performance of Alles nur nach Gottes Willen, BWV 72, concluding his third Christmas season in Leipzig on the Third Sunday after Epiphany.","url":"https://en.wikipedia.org/wiki/Johann_Sebastian_Bach"},{"year":1343,"text":"Clement VI issued the papal bull Unigenitus, justifying the power of the pope and the use of indulgences.","url":"https://en.wikipedia.org/wiki/Pope_Clement_VI"},{"year":945,"text":"The brothers Stephen and Constantine Lekapenos, having deposed their father as Byzantine emperor a few weeks earlier, were themselves overthrown by Constantine VII, their co-emperor.","url":"https://en.wikipedia.org/wiki/Stephen_Lekapenos"},{"year":98,"text":"Trajan succeeded his adoptive father Nerva as Roman emperor; the Roman Empire reached its maximum extent under his rule.","url":"https://en.wikipedia.org/wiki/AD_98"}],"births":[{"year":2003,"text":"Park Seong-hoon, South Korean footballer","url":"https://en.wikipedia.org/wiki/Park_Seong-hoon_(footballer)"},{"year":2000,"text":"Morgan Gibbs-White, English footballer","url":"https://en.wikipedia.org/wiki/Morgan_Gibbs-White"},{"year":2000,"text":"Aurélien Tchouaméni, French footballer","url":"https://en.wikipedia.org/wiki/Aur%C3%A9lien_Tchouam%C3%A9ni"},{"year":1998,"text":"Devin Druid, American actor","url":"https://en.wikipedia.org/wiki/Devin_Druid"},{"year":1996,"text":"Braeden Lemasters, American actor, musician, and singer","url":"https://en.wikipedia.org/wiki/Braeden_Lemasters"},{"year":1995,"text":"Harrison Reed, English footballer","url":"https://en.wikipedia.org/wiki/Harrison_Reed_(footballer)"},{"year":1994,"text":"Desiree Becker, German politician","url":"https://en.wikipedia.org/wiki/Desiree_Becker"},{"year":1994,"text":"Jack Stephens, English footballer","url":"https://en.wikipedia.org/wiki/Jack_Stephens_(footballer)"}],"deaths":[{"year":2022,"text":"Andy Devine, British TV actor (born 1942)","url":"https://en.wikipedia.org/wiki/Andy_Devine_(English_actor)"},{"year":2021,"text":"Cloris Leachman, American actress and comedian (born 1926)","url":"https://en.wikipedia.org/wiki/Cloris_Leachman"},{"year":2021,"text":"Nunuk Nuraini, Indonesian food scientist (born 1961)","url":"https://en.wikipedia.org/wiki/Nunuk_Nuraini"},{"year":2020,"text":"Lina Ben Mhenni, Tunisian Internet activist and blogger (born 1983)","url":"https://en.wikipedia.org/wiki/Lina_Ben_Mhenni"},{"year":2019,"text":"Countess Maya von Schönburg-Glauchau, German socialite (born 1958)","url":"https://en.wikipedia.org/wiki/Countess_Maya_von_Sch%C3%B6nburg-Glauchau"},{"year":2018,"text":"Ingvar Kamprad, Founder of IKEA (born 1926)","url":"https://en.wikipedia.org/wiki/Ingvar_Kamprad"},{"year":2018,"text":"Mort Walker, American cartoonist (born 1923)","url":"https://en.wikipedia.org/wiki/Mort_Walker"},{"year":2017,"text":"Emmanuelle Riva, French actress (born 1927)","url":"https://en.wikipedia.org/wiki/Emmanuelle_Riva"}]},"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."}