{"date":"2026-08-17","schema_version":1,"captured_at":"2026-08-25T23:20:07.648Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"Jason Arday","views":355195,"rank":4,"extract":"Jason Atta Kwei Arday was a British academic who was a professor of sociology of education at the University of Cambridge from 2023 to 2026. 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In the active linear regression problem, one would like to estimate the least squares solution $β^*$ minimizing $\\|Xβ- y\\|_2$ given the entire unlabeled dataset $X \\in \\mathbb{R}^{n \\times d}$ but only obse","authors":["Chen, Xue","Price, Eric"],"url":"https://arxiv.org/abs/1711.10051","arxiv_id":"1711.10051","published":"2026-08-17"},{"title":"Holdout predictive checks for Bayesian model criticism","abstract":"Bayesian modeling helps applied researchers articulate assumptions about their data and develop models tailored for specific applications. Thanks to good methods for approximate posterior inference, researchers can now easily build, use, and revise complicated Bayesian models for large and rich data. These capabilities, however, bring into focus the problem of model criticism. Researchers need tools to diagnose the f","authors":["Moran, Gemma E.","Blei, David M.","Ranganath, Rajesh"],"url":"https://arxiv.org/abs/1908.00882","arxiv_id":"1908.00882","published":"2026-08-17"},{"title":"I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling","abstract":"Reconstructing a high-precision and high-fidelity 3D human hand from a color image plays a central role in replicating a realistic virtual hand in human-computer interaction and virtual reality applications. The results of current methods are lacking in accuracy and fidelity due to various hand poses and severe occlusions. In this study, we propose an I2UV-HandNet model for accurate hand pose and shape estimation as ","authors":["Chen, Ping","Chen, Yujin","Yang, Dong","Wu, Fangyin","Li, Qin","Xia, Qingpei"],"url":"https://arxiv.org/abs/2102.03725","arxiv_id":"2102.03725","published":"2026-08-17"},{"title":"Investigating individual writing style as a contributor to gender gaps in science and technology","abstract":"Gender gaps in how scientific work is evaluated are well documented, but their sources remain debated. We ask whether an overlooked factor---the linguistic style of the writing itself---is gendered and consequential. Drawing on a framework that distinguishes informational features (which emphasize facts) from involved features (which emphasize relationships), we analyze single-authored abstracts of academic papers an","authors":["Kedrick, Kara","Levitskaya, Ekaterina","Funk, Russell J."],"url":"https://arxiv.org/abs/2204.13805","arxiv_id":"2204.13805","published":"2026-08-17"},{"title":"DAA: A Delta Age AdaIN operation for age estimation via binary code transformer","abstract":"Naked eye recognition of age is usually based on comparison with the age of others. However, this idea is ignored by computer tasks because it is difficult to obtain representative contrast images of each age. Inspired by the transfer learning, we designed the Delta Age AdaIN (DAA) operation to obtain the feature difference with each age, which obtains the style map of each age through the learned values representing","authors":["Chen, Ping","Zhang, Xingpeng","Li, Ye","Tao, Ju","Xiao, Bin","Wang, Bing"],"url":"https://arxiv.org/abs/2303.07929","arxiv_id":"2303.07929","published":"2026-08-17"},{"title":"Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation","abstract":"Clothes grasping and unfolding is a core step in robotic-assisted dressing. Most existing works leverage depth images of clothes to train a deep learning-based model to recognize suitable grasping points. These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection. However, the natural domain gap between synthetic and real images often leads to poor perfor","authors":["Zhu, Xingyu","Wang, Xin","Freer, Jonathan","Chang, Hyung Jin","Gao, Yixing"],"url":"https://arxiv.org/abs/2305.03259","arxiv_id":"2305.03259","published":"2026-08-17"},{"title":"Logarithmic Mathematical Morphology: Theory and applications","abstract":"In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring function is translated over the image domain and summed to the image. However, in an image presenting lighting variations, when the structuring function is added to this image, the amplitude of this translated structuring function should vary according to the image intensity. Suc","authors":["Noyel, Guillaume"],"url":"https://arxiv.org/abs/2309.02007","arxiv_id":"2309.02007","published":"2026-08-17"},{"title":"Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges","abstract":"Graph-based message-passing neural networks (MPNNs) have achieved remarkable success in both node and graph-level learning tasks. However, several identified problems, including over-smoothing (OSM), limited expressive power, and over-squashing (OSQ), still limit the performance of MPNNs. In particular, OSQ serves as the latest identified problem, where MPNNs gradually lose their learning accuracy when long-range dep","authors":["Shi, Dai","Han, Andi","Lin, Lequan","Guo, Yi","Gao, Junbin"],"url":"https://arxiv.org/abs/2311.07073","arxiv_id":"2311.07073","published":"2026-08-17"},{"title":"BAT: Learning to Reason about Spatial Sounds with Large Language Models","abstract":"Spatial sound reasoning is a fundamental human skill, enabling us to navigate and interpret our surroundings based on sound. In this paper we present BAT, which combines the spatial sound perception ability of a binaural acoustic scene analysis model with the natural language reasoning capabilities of a large language model (LLM) to replicate this innate ability. To address the lack of existing datasets of in-the-wil","authors":["Zheng, Zhisheng","Peng, Puyuan","Ma, Ziyang","Chen, Xie","Choi, Eunsol","Harwath, David"],"url":"https://arxiv.org/abs/2402.01591","arxiv_id":"2402.01591","published":"2026-08-17"},{"title":"Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature","abstract":"Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex and age. While these standards provide useful guidelines and help identify at-risk patients, they are not fully reliable for diagnosis due to the lack of demographic considerations. This study aims to","authors":["Guo, Yuting","Mousavi, Seyedeh Somayyeh","Sameni, Reza","Sarker, Abeed"],"url":"https://arxiv.org/abs/2402.01826","arxiv_id":"2402.01826","published":"2026-08-17"},{"title":"MLCC: A Congestion Control Technique to Accelerate ML Training","abstract":"We present MLCC, a novel technique to augment today's congestion control algorithms to accelerate DNN training jobs in shared GPU clusters in a fully distributed manner. At the heart of MLCC lies a straightforward principle: DNN training flows should scale their sending rate to shift other flows' communication into their compute periods, achieving interleaving. We show that integrating this principle into tod","authors":["Zabreyko, Anton A.","Narang, Sanjoli","Rajasekaran, Sudarsanan","Ghobadi, Manya"],"url":"https://arxiv.org/abs/2402.09589","arxiv_id":"2402.09589","published":"2026-08-17"},{"title":"Automated Inference of Graph Transformation Rules","abstract":"The explosion of data available in life sciences is fueling an increasing demand for expressive models and computational methods. Graph transformation is a model for dynamic systems with a large variety of applications. We introduce a novel method of the graph transformation model construction, combining generative and dynamical viewpoints to give a fully automated data-driven model inference method. The method takes","authors":["Andersen, Jakob L.","Davoodi, Akbar","Fagerberg, Rolf","Flamm, Christoph","Fontana, Walter","Kolčák, Juri"],"url":"https://arxiv.org/abs/2404.02692","arxiv_id":"2404.02692","published":"2026-08-17"},{"title":"Overparameterized Multiple Linear Regression as Hyper-Curve Fitting","abstract":"This work demonstrates that applying a fixed-effect multiple linear regression (MLR) model to an overparameterized dataset is mathematically equivalent to fitting a hyper-curve parameterized by a single scalar. This reformulation shifts the focus from global coefficients to individual predictors, allowing each to be modeled as a function of a common parameter. We prove that this overparameterized linear framework can","authors":["Atza, E.","Budko, N."],"url":"https://arxiv.org/abs/2404.07849","arxiv_id":"2404.07849","published":"2026-08-17"},{"title":"Separation capacity of linear reservoirs with random connectivity matrix","abstract":"A natural hypothesis for the success of reservoir computing in generic tasks is the ability of the untrained reservoir to map distinct input time series to separable reservoir states, a property we term separation capacity. In this work, we develop a rigorous mathematical framework for analysing the separation capacity of random linear reservoirs. We show that the expected separation induced by a random reservoir is ","authors":["Boutaib, Youness"],"url":"https://arxiv.org/abs/2404.17429","arxiv_id":"2404.17429","published":"2026-08-17"},{"title":"PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and Classification","abstract":"Numerous applications have resulted from the automation of agricultural disease segmentation using deep learning techniques. However, when applied to new conditions, these applications frequently face the difficulty of overfitting, resulting in lower segmentation performance. In the context of potato farming, where diseases have a large influence on yields, it is critical for the agricultural economy to quickly and p","authors":["Faria, Fatema Tuj Johora","Moin, Mukaffi Bin","Alam, Mohammad Shafiul","Wase, Ahmed Al","Sani, Md. Rabius","Hasib, Khan Md"],"url":"https://arxiv.org/abs/2405.07332","arxiv_id":"2405.07332","published":"2026-08-17"},{"title":"A Probabilistic Framework for Learnable Optimization Algorithms","abstract":"We propose a statistical-learning framework for optimization algorithms. The framework is based on probability distributions over optimization trajectories induced by a distribution of optimization problems and a learnable optimization algorithm. Within this setting, optimization performance is represented through measurable performance functionals, including stopping times, contraction factors, and trajectory-level ","authors":["Ochs, Peter","Sucker, Michael"],"url":"https://arxiv.org/abs/2408.11629","arxiv_id":"2408.11629","published":"2026-08-17"},{"title":"OTIS: Learning High-Quality Time Series Features With Tiny Encoders","abstract":"We introduce OTIS, an open time series encoder that yields high-quality time series features for downstream deployment on any system, including resource-constrained wearables and industrial sensors. Currently, the development of powerful general-purpose encoders relies on the scaling laws hypothesis, using large encoder sizes to memorise the heterogeneous distributions of multi-domain training data. However, this rel","authors":["Turgut, Özgün","Müller, Philip","Menten, Martin J.","Rueckert, Daniel"],"url":"https://arxiv.org/abs/2410.07299","arxiv_id":"2410.07299","published":"2026-08-17"},{"title":"Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directions","abstract":"Automated vehicles (AVs) promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due to rare and unexpected situations known as edge cases. While numerous approaches exist for detecting edge cases, a comprehensive survey reviewing these techniques is lacking. This paper bridges this gap by presenting a hierarchical review ","authors":["Rahmani, Saeed","Rieder, Sabine","de Gelder, Erwin","Sonntag, Marcel","Mallada, Jorge Lorente","Kalisvaart, Sytze"],"url":"https://arxiv.org/abs/2410.08491","arxiv_id":"2410.08491","published":"2026-08-17"},{"title":"Ordinal-Aware Calibration for Ordinal Classification","abstract":"Deep neural networks frequently produce overconfident, miscalibrated predictions. In ordinal classification, predictions must also adhere to a unimodal and order-consistent structure, a requirement that has dominated prior work while overlooking calibration. We formalize this joint challenge as ordinal calibration for the first time and propose the Ordinal loss for Calibration and Unimodality (ORCU). Unlike increment","authors":["Kim, Daehwan","Chung, Haejun","Jang, Ikbeom"],"url":"https://arxiv.org/abs/2410.15658","arxiv_id":"2410.15658","published":"2026-08-17"},{"title":"LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction","abstract":"Large language models (LLMs) are increasingly being used in materials science. However, little attention has been given to benchmarking and standardized evaluation for LLM-based materials property prediction, which hinders progress. We present LLM4Mat-Bench, the largest benchmark to date for evaluating the performance of LLMs in predicting the properties of crystalline materials. LLM4Mat-Bench contains about 1.9M cry","authors":["Rubungo, Andre Niyongabo","Li, Kangming","Hattrick-Simpers, Jason","Dieng, Adji Bousso"],"url":"https://arxiv.org/abs/2411.00177","arxiv_id":"2411.00177","published":"2026-08-17"},{"title":"Efficient transformer adaptation for analog in-memory computing via low-rank adapters","abstract":"Analog In-Memory Computing (AIMC) offers a promising solution to the von Neumann bottleneck. However, deploying transformer models on AIMC remains challenging due to their inherent need for flexibility and adaptability across diverse tasks. For the benefits of AIMC to be fully realized, weights of static vector-matrix multiplications must be mapped and programmed to analog devices in a weight-stationary manner. This ","authors":["Li, Chen","Ferro, Elena","Lammie, Corey","Gallo, Manuel Le","Boybat, Irem","Rajendran, Bipin"],"url":"https://arxiv.org/abs/2411.17367","arxiv_id":"2411.17367","published":"2026-08-17"},{"title":"Musical Agent Systems: MACAT and MACataRT","abstract":"Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces. We introduce MACAT and MACataRT, two distinct musical agent systems crafted to enhance interactive music-making between human musicians and AI. MACAT is optimized for agent-led performance, employing real-time synthesis and ","authors":["Lee, Keon Ju M.","Pasquier, Philippe"],"url":"https://arxiv.org/abs/2502.00023","arxiv_id":"2502.00023","published":"2026-08-17"},{"title":"Generative Modeling with Bayesian Sample Inference","abstract":"We present a novel view of diffusion-like generative modeling from the perspective of iterative Gaussian posterior inference. By treating the generated sample as an unknown variable, we formulate the sampling process in the language of Bayesian probability: at each step, a model predicts the unknown sample from our current belief state and we compute a posterior belief from that prediction. Based on this formulation,","authors":["Lienen, Marten","Kollovieh, Marcel","Günnemann, Stephan"],"url":"https://arxiv.org/abs/2502.07580","arxiv_id":"2502.07580","published":"2026-08-17"},{"title":"AI Models Still Lag Behind Traditional Numerical Models in Predicting Sudden-Turning Typhoons","abstract":"Given the interpretability, accuracy, and stability of numerical weather prediction (NWP) models, current operational weather forecasting relies heavily on the NWP approach. In the past two years, the rapid development of Artificial Intelligence (AI) has provided an alternative solution for medium-range (1-10 days) weather forecasting. Bi et al. (2023) (hereafter Bi23) introduced the first AI-based weather prediction","authors":["Xu, Daosheng","Lu, Zebin","Leung, Jeremy Cheuk-Hin","Zhao, Dingchi","Li, Yi","Shi, Yang"],"url":"https://arxiv.org/abs/2502.16036","arxiv_id":"2502.16036","published":"2026-08-17"},{"title":"From Field Data to Global Food Systems Intelligence: A Semantic Graph Framework for Sustainable Wheat Production","abstract":"In response to the growing need for structured, interoperable agricultural data, this paper presents the Sustainable Wheat Production Datahub, a modular, graph-based framework that brings diverse wheat production datasets together into a single, queryable store. Using the Knowledge Acquisition and Representation Methodology (KNARM), with domain experts in the loop, we developed ontologies for nutrient management and ","authors":["Gelal, Nirmal","Gautam, Aastha","Abadifard, Soheil","Giordano, Nico","Sarma, Moumita Sen","Norouzi, Sanaz Saki"],"url":"https://arxiv.org/abs/2502.19507","arxiv_id":"2502.19507","published":"2026-08-17"}],"history":{"events":[{"year":2008,"text":"Michael Phelps won his eighth gold medal of the Summer Olympics in Beijing, setting the record for the most gold medals won by an athlete at a single games.","url":"https://en.wikipedia.org/wiki/Michael_Phelps"},{"year":1959,"text":"American musician Miles Davis released Kind of Blue, which became one of the best-selling and most critically acclaimed jazz recordings of all time.","url":"https://en.wikipedia.org/wiki/Miles_Davis"},{"year":1950,"text":"Korean War: Forty-two American prisoners of war were massacred by the Korean People's Army on a hill above Waegwan, South Korea.","url":"https://en.wikipedia.org/wiki/Korean_War"},{"year":1945,"text":"Animal Farm, George Orwell's satirical allegory of Soviet totalitarianism, was first published.","url":"https://en.wikipedia.org/wiki/Animal_Farm"},{"year":1945,"text":"The independence of Indonesia was proclaimed, igniting a revolution against the Dutch Empire.","url":"https://en.wikipedia.org/wiki/Proclamation_of_Indonesian_Independence"},{"year":1943,"text":"World War II: The Royal Air Force began a strategic bombing campaign against Nazi Germany's V-weapon programme by attacking the Peenemünde Army Research Center.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1943,"text":"Winston Churchill and Franklin D. Roosevelt met in a secret conference in Quebec.","url":"https://en.wikipedia.org/wiki/Winston_Churchill"},{"year":1915,"text":"A category 4 hurricane made landfall in Galveston, Texas, leaving at least 275 people dead.","url":"https://en.wikipedia.org/wiki/1915_Galveston_hurricane"},{"year":1914,"text":"World War I: Ignoring orders to retreat, Hermann von François led a successful counterattack defending East Prussia at the Battle of Stallupönen and scored the first German victory in the Eastern Front.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1907,"text":"Pike Place Market (pictured), one of the oldest continuously operated public farmers' markets in the U.S. and a popular tourist attraction, opened in Seattle, Washington.","url":"https://en.wikipedia.org/wiki/Pike_Place_Market"},{"year":1876,"text":"The premiere of Götterdämmerung by Richard Wagner (pictured) closed the first Bayreuth Festival.","url":"https://en.wikipedia.org/wiki/G%C3%B6tterd%C3%A4mmerung"},{"year":1676,"text":"Scanian War: Swedish forces defeated Danish troops at the Battle of Halmstad.","url":"https://en.wikipedia.org/wiki/Scanian_War"},{"year":1668,"text":"An earthquake struck the North Anatolia region, killing over 8,000 people.","url":"https://en.wikipedia.org/wiki/1668_North_Anatolia_earthquake"},{"year":1560,"text":"The Scottish Reformation Parliament approved a Protestant confession of faith, initiating the Scottish Reformation and disestablishing Catholicism as the national religion.","url":"https://en.wikipedia.org/wiki/Scottish_Reformation_Parliament"},{"year":986,"text":"Byzantine–Bulgarian wars: The Bulgarians defeated Byzantine forces at the battle of the Gates of Trajan near present-day Ihtiman, with Emperor Basil II barely escaping.","url":"https://en.wikipedia.org/wiki/Byzantine%E2%80%93Bulgarian_wars"}],"births":[{"year":2003,"text":"Rayan Cherki, French footballer","url":"https://en.wikipedia.org/wiki/Rayan_Cherki"},{"year":2003,"text":"Nastasja Schunk, German tennis player","url":"https://en.wikipedia.org/wiki/Nastasja_Schunk"},{"year":2003,"text":"The Kid Laroi, Australian rapper and songwriter","url":"https://en.wikipedia.org/wiki/The_Kid_Laroi"},{"year":2000,"text":"Lil Pump, American rapper and songwriter","url":"https://en.wikipedia.org/wiki/Lil_Pump"},{"year":1998,"text":"Yoshinobu Yamamoto, Japanese baseball player","url":"https://en.wikipedia.org/wiki/Yoshinobu_Yamamoto"},{"year":1996,"text":"Jake Virtanen, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Jake_Virtanen"},{"year":1995,"text":"Gracie Gold, American figure skater","url":"https://en.wikipedia.org/wiki/Gracie_Gold"},{"year":1995,"text":"Dallin Watene-Zelezniak, New Zealand rugby league player","url":"https://en.wikipedia.org/wiki/Dallin_Watene-Zelezniak"}],"deaths":[{"year":2025,"text":"Terence Stamp, English actor (born 1938)","url":"https://en.wikipedia.org/wiki/Terence_Stamp"},{"year":2024,"text":"Virginia Ogilvy, Countess of Airlie, British countess (born 1933)","url":"https://en.wikipedia.org/wiki/Virginia_Ogilvy%2C_Countess_of_Airlie"},{"year":2024,"text":"Silvio Santos, Brazilian media mogul and television host (born 1930)","url":"https://en.wikipedia.org/wiki/Silvio_Santos"},{"year":2016,"text":"Arthur Hiller, Canadian actor, director, and producer (born 1923)","url":"https://en.wikipedia.org/wiki/Arthur_Hiller"},{"year":2015,"text":"Yvonne Craig, American ballet dancer and actress (born 1937)","url":"https://en.wikipedia.org/wiki/Yvonne_Craig"},{"year":2015,"text":"Gerhard Mayer-Vorfelder, German businessman (born 1933)","url":"https://en.wikipedia.org/wiki/Gerhard_Mayer-Vorfelder"},{"year":2015,"text":"László Paskai, Hungarian cardinal (born 1927)","url":"https://en.wikipedia.org/wiki/L%C3%A1szl%C3%B3_Paskai"},{"year":2014,"text":"Børre Knudsen, Norwegian minister and activist (born 1937)","url":"https://en.wikipedia.org/wiki/B%C3%B8rre_Knudsen"}]},"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."}