{"date":"2026-06-19","schema_version":1,"captured_at":"2026-08-25T23:12:55.759Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Daveigh Chase","views":728789,"rank":3,"extract":"Daveigh Elizabeth Chase was an American actress.","url":"https://en.wikipedia.org/wiki/Daveigh_Chase","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/a/a5/Daveigh_Chase_LF_adjusted.jpg/330px-Daveigh_Chase_LF_adjusted.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"2026 FIFA World Cup","views":581652,"rank":4,"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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Our string of innovations are 1) robust topological features are used to encode behavioral information, 2) statistical models are fitted to distributions over these topological features, and 3) the target type classification methods of Wigren and Bar Shalom et al. are employed","authors":["Bendich, Paul","Chin, Sang","Clarke, Jesse","deSena, Jonathan","Harer, John","Munch, Elizabeth"],"url":"https://arxiv.org/abs/1406.0214","arxiv_id":"1406.0214","published":"2026-06-19"},{"title":"Using Persistent Homology to Quantify a Diurnal Cycle in Hurricane Felix","abstract":"The diurnal cycle of tropical cyclones (TCs) is a daily cycle in clouds that appears in satellite images and may have implications for TC structure and intensity. The diurnal pattern can be seen in infrared (IR) satellite imagery as cyclical pulses in the cloud field that propagate radially outward from the center of nearly all Atlantic-basin TCs. These diurnal pulses, a distinguishing characteristic of the TC diurna","authors":["Tymochko, Sarah","Munch, Elizabeth","Dunion, Jason","Corbosiero, Kristen","Torn, Ryan"],"url":"https://arxiv.org/abs/1902.06202","arxiv_id":"1902.06202","published":"2026-06-19"},{"title":"Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings","abstract":"Unstructured text provides decision-makers with a rich data source in many domains, ranging from product reviews in retail to nursing notes in healthcare. To leverage this information, words are typically translated into word embeddings -- vectors that encode the semantic relationships between words -- through unsupervised learning algorithms such as matrix factorization. However, learning word embeddings from new do","authors":["Xu, Kan","Zhao, Xuanyi","Bastani, Hamsa","Bastani, Osbert"],"url":"https://arxiv.org/abs/2104.08928","arxiv_id":"2104.08928","published":"2026-06-19"},{"title":"IdealGPT: Iteratively Decomposing Vision and Language Reasoning via Large Language Models","abstract":"The field of vision-and-language (VL) understanding has made unprecedented progress with end-to-end large pre-trained VL models (VLMs). However, they still fall short in zero-shot reasoning tasks that require multi-step inferencing. To achieve this goal, previous works resort to a divide-and-conquer pipeline. In this paper, we argue that previous efforts have several inherent shortcomings: 1) They rely on domain-spec","authors":["You, Haoxuan","Sun, Rui","Wang, Zhecan","Chen, Long","Wang, Gengyu","Ayyubi, Hammad A."],"url":"https://arxiv.org/abs/2305.14985","arxiv_id":"2305.14985","published":"2026-06-19"},{"title":"Constructing Colloquial Dataset for Persian Sentiment Analysis of Social Microblogs","abstract":"Introduction: Microblogging websites have massed rich data sources for sentiment analysis and opinion mining. In this regard, sentiment classification has frequently proven inefficient because microblog posts typically lack syntactically consistent terms and representatives since users on these social networks do not like to write lengthy statements. Also, there are some limitations to low-resource languages. The Per","authors":["Mazoochi, Mojtaba","Rabiei, Leila","Rahmani, Farzaneh","Rajabi, Zeinab"],"url":"https://arxiv.org/abs/2306.12679","arxiv_id":"2306.12679","published":"2026-06-19"},{"title":"Benign overfitting beyond prediction: The ordinary least squares interpolator","abstract":"Recent advances in deep learning have highlighted the phenomenon of benign overfitting in overparameterized statistical models, sparking significant interest in understanding its foundations. Owing to its simplicity and practical relevance, the ordinary least squares (OLS) interpolator has become a key object of study for gaining theoretical insight into this phenomenon. While the properties of OLS are well understoo","authors":["Shen, Dennis","Song, Dogyoon","Ding, Peng","Sekhon, Jasjeet S."],"url":"https://arxiv.org/abs/2309.15769","arxiv_id":"2309.15769","published":"2026-06-19"},{"title":"Analysing Rescaling, Discretisation, and Linearisation in RNNs for Neural System Modelling","abstract":"Recurrent Neural Networks (RNNs) are widely used to model neural activity in Computational Neuroscience. Here, we explore the mathematical foundations of three fundamental procedures that can be implemented: temporal rescaling, discretisation, and linearisation. These techniques provide crucial tools for characterising the behaviour of RNNs, offering insights into their temporal dynamics, facilitating practical compu","authors":["Caruso, Mariano","Jarne, Cecilia"],"url":"https://arxiv.org/abs/2312.15974","arxiv_id":"2312.15974","published":"2026-06-19"},{"title":"Representing Piecewise-Linear Functions by Functions with Minimal Arity","abstract":"Any continuous piecewise-linear function $F\\colon \\mathbb{R}^{n}\\to \\mathbb{R}$ can be represented as a linear combination of $\\max$ functions of at most $n+1$ affine-linear functions. In our previous paper [``Representing piecewise linear functions by functions with small arity'', AAECC, 2023], we showed that this upper bound of $n+1$ arguments is tight. In the present paper, we extend this result by establi","authors":["Koutschan, Christoph","Ponomarchuk, Anton","Schicho, Josef"],"url":"https://arxiv.org/abs/2406.02421","arxiv_id":"2406.02421","published":"2026-06-19"},{"title":"Self-attention-based non-linear basis transformations for compact latent space modelling of dynamic optical fibre transmission matrices","abstract":"Multimode optical fibres are hair-thin strands of glass that efficiently transport light. They promise next-generation medical endoscopes that provide unprecedented sub-cellular image resolution deep inside the body. However, confining light to such fibres means that images are inherently scrambled in transit. Conventionally, this scrambling has been compensated by pre-calibrating how a specific fibre scrambles light","authors":["Zheng, Yijie","Kilpatrick, Robert J.","Phillips, David B.","Gordon, George S. D."],"url":"https://arxiv.org/abs/2406.07775","arxiv_id":"2406.07775","published":"2026-06-19"},{"title":"RadEx: A Framework for Structured Information Extraction from Radiology Reports based on Large Language Models","abstract":"Annually and globally, over three billion radiography examinations and computer tomography scans result in mostly unstructured radiology reports containing free text. Despite the potential benefits of structured reporting, its adoption is limited by factors such as established processes, resource constraints and potential loss of information. However, structured information would be necessary for various use cases, i","authors":["Reichenpfader, Daniel","Knupp, Jonas","Sander, André","Denecke, Kerstin"],"url":"https://arxiv.org/abs/2406.15465","arxiv_id":"2406.15465","published":"2026-06-19"},{"title":"Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinations","abstract":"Multi-view learning often struggles to effectively leverage images captured from diverse angles and locations. Learning methods for unstructured multi-view images remain largely underexplored. We propose a novel Hierarchical Mutual Distillation for Multi-View Fusion (HMDMV) method, which can handle both structured and unstructured multi-view scenarios. It makes predictions utilizing all possible view combinations: si","authors":["Yang, Jiwoong","Chung, Haejun","Jang, Ikbeom"],"url":"https://arxiv.org/abs/2411.10077","arxiv_id":"2411.10077","published":"2026-06-19"},{"title":"Evaluating deep learning models for fault diagnosis of a rotating machinery with epistemic and aleatoric uncertainty","abstract":"Uncertainty-aware deep learning (DL) models recently gained attention in fault diagnosis as a way to promote the reliable detection of faults when out-of-distribution (OOD) data arise from unseen faults (epistemic uncertainty) or the presence of noise (aleatoric uncertainty). In this paper, we present the first comprehensive comparative study of state-of-the-art uncertainty-aware DL architectures for fault diagnosis ","authors":["Jalayer, Reza","Jalayer, Masoud","Mor, Andrea","Orsenigo, Carlotta","Vercellis, Carlo"],"url":"https://arxiv.org/abs/2412.18980","arxiv_id":"2412.18980","published":"2026-06-19"},{"title":"An Experimental Study on Fairness-aware Machine Learning for Credit Scoring Problems","abstract":"The digitalization of credit scoring has become essential for financial institutions and commercial banks, especially in the era of digital transformation. Machine learning techniques are commonly used to evaluate customers' creditworthiness. However, the predicted outcomes of machine learning models can be biased toward protected attributes, such as race or gender. Numerous fairness-aware machine learning models","authors":["Thu, Huyen Giang Thi","Doan, Thang Viet","Ban, Ha-Bang","Quy, Tai Le"],"url":"https://arxiv.org/abs/2412.20298","arxiv_id":"2412.20298","published":"2026-06-19"},{"title":"UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation","abstract":"Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the primary challenges include behavioral multimodality and closed-loop distributional shifts. In this study, we formulate a unified mixture model (UniMM) framework for generating multimodal agent behaviors, which can cover the mainstream methods ","authors":["Lin, Longzhong","Lin, Xuewu","Xu, Kechun","Lu, Haojian","Huang, Lichao","Xiong, Rong"],"url":"https://arxiv.org/abs/2501.17015","arxiv_id":"2501.17015","published":"2026-06-19"},{"title":"A Unified Perspective on the Dynamics of Deep Transformers","abstract":"Transformers, which are state-of-the-art in most machine learning tasks, represent the data as sequences of vectors called tokens. This representation is then exploited by the attention function, which learns dependencies between tokens and is key to the success of Transformers. However, the iterative application of attention across layers induces complex dynamics that remain to be fully understood. To analyze these ","authors":["Castin, Valérie","Ablin, Pierre","Carrillo, José Antonio","Peyré, Gabriel"],"url":"https://arxiv.org/abs/2501.18322","arxiv_id":"2501.18322","published":"2026-06-19"},{"title":"Adversarial Dependence Minimization","abstract":"Minimally redundant representations are typically learned by minimizing feature covariance. However, covariance-based methods fail to eliminate all dependencies/redundancies, as linearly uncorrelated variables can still exhibit nonlinear relationships. To address this, we introduce ADM, a differentiable algorithm that minimizes statistical dependence between feature dimensions through an adversarial game: auxiliary n","authors":["De Plaen, Pierre-François","Tuytelaars, Tinne","Proesmans, Marc","Van Gool, Luc"],"url":"https://arxiv.org/abs/2502.03227","arxiv_id":"2502.03227","published":"2026-06-19"},{"title":"Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies","abstract":"The drastic changes in the global economy, geopolitical conditions, and disruptions such as the COVID-19 pandemic have impacted the cost of living and quality of life. It is essential to comprehend the long-term implications of the cost of living and quality of life in major economies. A transparent and comprehensive living index must include multiple dimensions of living conditions. In this study, we present an appr","authors":["Selvaraj, Arun Kumar","Panat, Tanay","Chandra, Rohitash"],"url":"https://arxiv.org/abs/2502.06866","arxiv_id":"2502.06866","published":"2026-06-19"},{"title":"Simulation of Language Evolution under Regulated Social Media Platforms: A Synergistic Approach of Large Language Models and Genetic Algorithms","abstract":"Social media platforms frequently impose restrictive policies to moderate user content, prompting the emergence of creative evasion language strategies. This paper presents a multi-agent framework based on Large Language Models (LLMs) to simulate the iterative evolution of language strategies under regulatory constraints. In this framework, participant agents, as social media users, continuously evolve their language","authors":["Cai, Jinyu","Ishimizu, Yusei","Zhang, Mingyue","Li, Munan","Li, Jialong","Tei, Kenji"],"url":"https://arxiv.org/abs/2502.19193","arxiv_id":"2502.19193","published":"2026-06-19"},{"title":"MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing","abstract":"We introduce MeshPad, a generative approach that creates 3D meshes from sketch inputs. Building on recent advances in artist-reminiscent triangle mesh generation, our approach addresses the need for interactive mesh creation. To this end, we focus on enabling consistent edits by decomposing editing into 'deletion' of regions of a mesh, followed by 'addition' of new mesh geometry. Both operations are i","authors":["Li, Haoxuan","Erkoc, Ziya","Li, Lei","Sirigatti, Daniele","Rosov, Vladislav","Dai, Angela"],"url":"https://arxiv.org/abs/2503.01425","arxiv_id":"2503.01425","published":"2026-06-19"},{"title":"A Deep Generative Model for Resting-State EEG Synthesis and Transferable Representation Learning","abstract":"Resting-state EEG provides a non-invasive view of spontaneous brain activity, but extracting meaningful patterns is often limited by scarce high-quality data and reliance on manually engineered features. Generative adversarial networks (GANs) can synthesize neural signals and learn transferable representations directly from raw data, a dual capability that remains underexplored in EEG research. Here, we introduce RES","authors":["Farahzadi, Yeganeh","Ansarinia, Morteza","Kekecs, Zoltan"],"url":"https://arxiv.org/abs/2503.02636","arxiv_id":"2503.02636","published":"2026-06-19"},{"title":"The Morse Transform for Discrete Shape Analysis","abstract":"The geometry of an object plays a vital role in modulating its interactions with the physical world. It nevertheless remains difficult to describe geometric information numerically for the purposes of statistical inference or classification tasks. Here, we introduce a new topological transform which leverages directional piecewise-linear Morse theory to quantify the geometry of an embedded object by cataloguing criti","authors":["Tanaka, Alexander M.","Asaad, Aras T.","Cooper, Richard","Nanda, Vidit"],"url":"https://arxiv.org/abs/2503.04507","arxiv_id":"2503.04507","published":"2026-06-19"},{"title":"A graph neural network surrogate model for mesh-based crashworthiness prediction of vehicle panel components","abstract":"Crashworthiness is a key performance measure in the design of safety-critical vehicle panel components such as B-pillars. Finite element (FE) simulations are widely used to evaluate crash responses but remain computationally expensive for large-scale, nonlinear impact scenarios, particularly when integrated into iterative design and optimisation processes. Although machine learning-based surrogate models have been de","authors":["Li, Haoran","Zhao, Yingxue","Zhou, Haosu","Pfaff, Tobias","Li, Nan"],"url":"https://arxiv.org/abs/2503.17386","arxiv_id":"2503.17386","published":"2026-06-19"},{"title":"OncoReg: Medical Image Registration for Oncological Challenges","abstract":"In modern cancer research, the vast volume of medical data generated is often underutilised due to challenges related to patient privacy. The OncoReg Challenge addresses this issue by enabling researchers to develop and validate image registration methods through a two-phase framework that ensures patient privacy while fostering the development of more generalisable AI models. Phase one involves working with a public","authors":["Heyer, Wiebke","Elser, Yannic","Berkel, Lennart","Song, Xinrui","Xu, Xuanang","Yan, Pingkun"],"url":"https://arxiv.org/abs/2503.23179","arxiv_id":"2503.23179","published":"2026-06-19"},{"title":"Med-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation","abstract":"Automated medical report generation (MRG) is increasingly used to reduce the burden of manual reporting and for decision support. Large vision-language models (LVLMs) hold great promise for automated MRG due to their fine-grained image-text alignment and advanced text-generation capabilities. Currently, state-of-the-art MRGs primarily focus on adapting pre-trained LVLMs with direct supervised fine-tuning (SFT), a fin","authors":["Wang, Hao","Ye, Shuchang","Lin, Jinghao","Naseem, Usman","Kim, Jinman"],"url":"https://arxiv.org/abs/2504.02885","arxiv_id":"2504.02885","published":"2026-06-19"},{"title":"TerraMind: Large-Scale Generative Multimodality for Earth Observation","abstract":"We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale representations combining both token-level and pixel-level data across modalities. On a token level, TerraMind encodes high-level contextual information to learn cross-modal relationships, while on a pixel level, TerraMind leverages fine-g","authors":["Jakubik, Johannes","Yang, Felix","Blumenstiel, Benedikt","Scheurer, Erik","Sedona, Rocco","Maurogiovanni, Stefano"],"url":"https://arxiv.org/abs/2504.11171","arxiv_id":"2504.11171","published":"2026-06-19"}],"history":{"events":[{"year":2012,"text":"Facing allegations of sexual assault in Sweden, Julian Assange (pictured), the founder of WikiLeaks, requested asylum at the Ecuadorian embassy in London.","url":"https://en.wikipedia.org/wiki/Assange_v_Swedish_Prosecution_Authority"},{"year":2010,"text":"The royal wedding of Victoria, Crown Princess of Sweden, and Daniel Westling took place in Stockholm Cathedral.","url":"https://en.wikipedia.org/wiki/Wedding_of_Victoria%2C_Crown_Princess_of_Sweden%2C_and_Daniel_Westling"},{"year":2009,"text":"War in Afghanistan: British forces began Operation Panther's Claw, in which more than 350 troops made an aerial assault on Taliban positions in southern Afghanistan.","url":"https://en.wikipedia.org/wiki/War_in_Afghanistan_(2001%E2%80%932021)"},{"year":2009,"text":"Mass rioting broke out in Shishou, China, over the dubious circumstances surrounding the death of a local chef.","url":"https://en.wikipedia.org/wiki/Shishou_incident"},{"year":2005,"text":"Only six race cars competed in the United States Grand Prix at the Indianapolis Motor Speedway in Indianapolis, Indiana, after all the Michelin-shod entrants were withdrawn due to safety concerns.","url":"https://en.wikipedia.org/wiki/Auto_racing"},{"year":1987,"text":"The Basque separatist group ETA detonated a car bomb at a Hipercor shopping centre in Barcelona, killing 21 people and injuring 45 others.","url":"https://en.wikipedia.org/wiki/Basque_nationalism"},{"year":1970,"text":"The international Patent Cooperation Treaty was signed, providing a unified procedure for filing patent applications to protect inventions in each of its contracting states.","url":"https://en.wikipedia.org/wiki/Patent_Cooperation_Treaty"},{"year":1965,"text":"Nguyễn Cao Kỳ, the commander of the South Vietnam Air Force, was appointed prime minister at the head of a military regime.","url":"https://en.wikipedia.org/wiki/Nguy%E1%BB%85n_Cao_K%E1%BB%B3"},{"year":1953,"text":"Americans Julius and Ethel Rosenberg (pictured) were executed as spies for passing nuclear weapons secrets to the Soviet Union.","url":"https://en.wikipedia.org/wiki/Julius_and_Ethel_Rosenberg"},{"year":1939,"text":"American baseball player Lou Gehrig (pictured) was diagnosed with amyotrophic lateral sclerosis, now commonly known in the United States as \"Lou Gehrig's disease\".","url":"https://en.wikipedia.org/wiki/Lou_Gehrig"},{"year":1926,"text":"King Roger, an opera about Roger II of Sicily by Karol Szymanowski (pictured), was premiered at the Grand Theatre in Warsaw.","url":"https://en.wikipedia.org/wiki/King_Roger_(opera)"},{"year":1867,"text":"Second French intervention in Mexico: Emperor Maximilian I of Mexico was executed by firing squad in Querétaro City.","url":"https://en.wikipedia.org/wiki/Second_French_intervention_in_Mexico"},{"year":1846,"text":"The first officially recorded baseball game in U.S. history using modern rules was played in Hoboken, New Jersey, with the \"New York Nine\" defeating the New York Knickerbockers 23–1.","url":"https://en.wikipedia.org/wiki/Baseball"},{"year":1838,"text":"The Maryland province of the Jesuits contracted to sell 272 slaves to buyers in Louisiana in one of the largest slave sales in American history.","url":"https://en.wikipedia.org/wiki/Maryland"},{"year":1785,"text":"The proprietors of King's Chapel, Boston, voted to adopt James Freeman's Book of Common Prayer, thus establishing the first Unitarian church in the Americas.","url":"https://en.wikipedia.org/wiki/King's_Chapel"},{"year":1718,"text":"An earthquake on the Tibetan Plateau led to the deaths of more than 73,000 people.","url":"https://en.wikipedia.org/wiki/1718_Tongwei%E2%80%93Gansu_earthquake"}],"births":[{"year":2004,"text":"Millie Gibson, English actress","url":"https://en.wikipedia.org/wiki/Millie_Gibson"},{"year":2002,"text":"Bennedict Mathurin, Canadian basketball player","url":"https://en.wikipedia.org/wiki/Bennedict_Mathurin"},{"year":2002,"text":"Nuno Mendes, Portuguese footballer","url":"https://en.wikipedia.org/wiki/Nuno_Mendes_(footballer%2C_born_2002)"},{"year":1999,"text":"Jordan Poole, American basketball player","url":"https://en.wikipedia.org/wiki/Jordan_Poole"},{"year":1998,"text":"Atticus Shaffer, American actor and YouTuber","url":"https://en.wikipedia.org/wiki/Atticus_Shaffer"},{"year":1998,"text":"Joshua Da Silva, Trinidadian cricketer","url":"https://en.wikipedia.org/wiki/Joshua_Da_Silva"},{"year":1994,"text":"Lejla Njemčević, Bosnian cross-country and mountain bike cyclist","url":"https://en.wikipedia.org/wiki/Lejla_Njem%C4%8Devi%C4%87"},{"year":1993,"text":"KSI, English YouTuber","url":"https://en.wikipedia.org/wiki/KSI"}],"deaths":[{"year":2020,"text":"Ian Holm, British actor (born 1931)","url":"https://en.wikipedia.org/wiki/Ian_Holm"},{"year":2019,"text":"Etika, American YouTuber and streamer (born 1990)","url":"https://en.wikipedia.org/wiki/Etika"},{"year":2018,"text":"Koko, western lowland gorilla and user of American Sign Language (born 1971)","url":"https://en.wikipedia.org/wiki/Koko_(gorilla)"},{"year":2017,"text":"Otto Warmbier, American college student detained in North Korea (born 1994)","url":"https://en.wikipedia.org/wiki/Otto_Warmbier"},{"year":2016,"text":"Anton Yelchin, American actor (born 1989)","url":"https://en.wikipedia.org/wiki/Anton_Yelchin"},{"year":2015,"text":"James Salter, American novelist and short-story writer (born 1925)","url":"https://en.wikipedia.org/wiki/James_Salter"},{"year":2014,"text":"Oskar-Hubert Dennhardt, German general (born 1915)","url":"https://en.wikipedia.org/wiki/Oskar-Hubert_Dennhardt"},{"year":2014,"text":"Gerry Goffin, American songwriter (born 1939)","url":"https://en.wikipedia.org/wiki/Gerry_Goffin"}]},"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."}