{"date":"2026-09-07","schema_version":1,"captured_at":"2026-09-08T09:12:21.227Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Killing of the Clancy children","views":466193,"rank":4,"extract":"On January 24, 2023, Lindsay Clancy fatally strangled her three children—five-year-old Cora, three-year-old Dawson, and eight-month-old Callan—at the family's home in Duxbury, Massachusetts, United States. 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A stacking ensemble of gradient boosted tree, random forest, and neural network yields a value-weighted annualized Sharpe ratio of 2.08 for classification and 1.39 for regression. This outperformance strengthens with class granularity and persists across subsamples and after transaction costs. Spanning tests show t","authors":["Bai, Yang","Pukthuanthong, Kuntara"],"url":"https://arxiv.org/abs/2108.02283","arxiv_id":"2108.02283","published":"2026-09-07"},{"title":"Collaboration between parallel connected neural networks -- A possible criterion for distinguishing artificial neural networks from natural organs","abstract":"We find experimentally that when artificial neural networks are connected in parallel and trained together, they display the following properties. (i) When the parallel-connected neural network (PNN) is optimized, each sub-network in the connection is not optimized. (ii) The contribution of an inferior sub-network to the whole PNN can be on par with that of the superior sub-network. (iii) The PNN can output the corre","authors":["He, Guang Ping"],"url":"https://arxiv.org/abs/2208.09983","arxiv_id":"2208.09983","published":"2026-09-07"},{"title":"Quality-diversity in dissimilarity spaces","abstract":"The theory of magnitude provides a mathematical framework for quantifying and maximizing diversity. We apply this framework to formulate quality-diversity algorithms in generic dissimilarity spaces. In particular, we instantiate and demonstrate a very general version of Go-Explore with promising performance.","authors":["Huntsman, Steve"],"url":"https://arxiv.org/abs/2211.12337","arxiv_id":"2211.12337","published":"2026-09-07"},{"title":"A Neural-preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions","abstract":"We introduce a neural-preconditioned iterative solver for Poisson equations with mixed boundary conditions. Typical Poisson discretizations yield large, ill-conditioned linear systems. Iterative solvers can be effective for these problems, but only when equipped with powerful preconditioners. Unfortunately, effective preconditioners like multigrid require costly setup phases that must be re-executed every time domain","authors":["Lan, Kai Weixian","Gueidon, Elias","Kaneda, Ayano","Panetta, Julian","Teran, Joseph"],"url":"https://arxiv.org/abs/2310.00177","arxiv_id":"2310.00177","published":"2026-09-07"},{"title":"OpenMedLM: Prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models","abstract":"LLMs have become increasingly capable at accomplishing a range of specialized-tasks and can be utilized to expand equitable access to medical knowledge. Most medical LLMs have involved extensive fine-tuning, leveraging specialized medical data and significant, thus costly, amounts of computational power. Many of the top performing LLMs are proprietary and their access is limited to very few research groups. However, ","authors":["Maharjan, Jenish","Garikipati, Anurag","Singh, Navan Preet","Cyrus, Leo","Sharma, Mayank","Ciobanu, Madalina"],"url":"https://arxiv.org/abs/2402.19371","arxiv_id":"2402.19371","published":"2026-09-07"},{"title":"Measuring proximity to standard planes during fetal brain ultrasound scanning","abstract":"This paper presents a pipeline designed to bring ultrasound (US) plane pose estimation closer to clinical use, demonstrating the feasibility of continuous, real-time proximity feedback for navigation to the standard planes (SPs) in the fetal brain. We propose a semi-supervised segmentation model that uses labeled SPs and unlabeled slices from 3D US volumes (non-SPs), achieving 0.93 mean Intersection over Union (mIoU)","authors":["Di Vece, Chiara","Cirigliano, Antonio","Lous, Meala Le","Napolitano, Raffaele","David, Anna L.","Peebles, Donald"],"url":"https://arxiv.org/abs/2404.07124","arxiv_id":"2404.07124","published":"2026-09-07"},{"title":"Momentum-based gradient descent methods for Lie groups","abstract":"Polyak's Heavy Ball (PHB; Polyak, 1964), a.k.a. Classical Momentum, and Nesterov's Accelerated Gradient (NAG; Nesterov, 1983) are well-established momentum-descent methods for optimization. Although the latter generally outperforms the former, primarily, generalizations of PHB-like methods to nonlinear spaces have not been sufficiently explored in the literature. In this paper, we propose a generalization of ","authors":["Campos, Cédric M.","de Diego, David Martín","Torrente-Teruel, José"],"url":"https://arxiv.org/abs/2404.09363","arxiv_id":"2404.09363","published":"2026-09-07"},{"title":"A Survey on Semantic Modeling for Building Energy Management","abstract":"Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector. Although IoT technologies now provide extensive operational data, heterogeneous data models, device descriptions, and contextual representations continue to limit semantic interoperability, limiting the development of generalisable, autonomous, context-aware BEM applications. Ontologies address this challenge ","authors":["Aniakor, Miracle","Cogo, Vinicius V.","Ferreira, Pedro M."],"url":"https://arxiv.org/abs/2404.11716","arxiv_id":"2404.11716","published":"2026-09-07"},{"title":"An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders","abstract":"Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained for, and investigate whether their embeddings form meaningful clusters. Our suite of benchmarking experiments uses encoders pretrained solely on ImageNet-1k with either supervised or self-supervised training techniques, deployed on image datasets that were not seen during traini","authors":["Lowe, Scott C.","Haurum, Joakim Bruslund","Oore, Sageev","Moeslund, Thomas B.","Taylor, Graham W."],"url":"https://arxiv.org/abs/2406.02465","arxiv_id":"2406.02465","published":"2026-09-07"},{"title":"Procedural Content Generation via Generative Artificial Intelligence","abstract":"The attempt to utilize machine learning in procedural content generation (PCG) has been made in the past. In this survey paper, we investigate how generative artificial intelligence (AI), which saw a significant increase in interest in the mid-2010s, is being used for PCG. We review applications of generative AI for the creation of various types of content, including terrains, items, and even storylines. While genera","authors":["Mao, Xinyu","Yu, Wanli","Okawara, Yuya","Zhan, Xueying","Yamada, Kazunori D.","Zielewski, Michael R."],"url":"https://arxiv.org/abs/2407.09013","arxiv_id":"2407.09013","published":"2026-09-07"},{"title":"Small Molecule Optimization with Large Language Models","abstract":"Molecular optimization, the process of designing molecules with desirable properties, represents a critical challenge in drug discovery. Recent advancements in large language models (LLMs) have opened new opportunities for their integration with traditional molecular optimization algorithms to improve performance. In this work, we propose Molecular Language Model powered Evolutionary Algorithm (Mol-E), an evolutionar","authors":["Guevorguian, Philipp","Bedrosian, Menua","Fahradyan, Tigran","Chilingaryan, Gayane","Aghajanyan, Armen","Khachatrian, Hrant"],"url":"https://arxiv.org/abs/2407.18897","arxiv_id":"2407.18897","published":"2026-09-07"},{"title":"Multilingual Models for Check-Worthy Social Media Posts Detection","abstract":"This work presents an extensive study of transformer-based NLP models application for detection of social media posts that contain verifiable factual claims and harmful claims. The study covers various activities, including dataset collection, dataset pre-processing, architecture selection, setup of settings, model training (fine-tuning), model testing, and implementation. The study includes a comprehensive analysis ","authors":["Kula, Sebastian"],"url":"https://arxiv.org/abs/2408.06737","arxiv_id":"2408.06737","published":"2026-09-07"},{"title":"The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures","abstract":"Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research attention in recent years. Operator approximations can serve as efficient surrogate models for problems in computational science and engineering, complementing traditional methods. However, despite their empirical success, our understanding of the underlying mathematical","authors":["Adcock, Ben","Griebel, Michael","Maier, Gregor"],"url":"https://arxiv.org/abs/2410.23440","arxiv_id":"2410.23440","published":"2026-09-07"},{"title":"Explainable Clustering of Mixture Models","abstract":"The explainable clustering problem was first posed by Moshkovitz et al. (ICML 2020) and studies how well an axis-aligned decision tree with $K$ leaves can approximate a given clustering. The performance of the tree is measured via the \\textit{price of explainability}, defined as the ratio between the clustering cost of the tree (where every leaf is a cluster) and the optimal cost. Several recent works have given wors","authors":["Fleissner, Maximilian","Zarvandi, Maedeh","Ghoshdastidar, Debarghya"],"url":"https://arxiv.org/abs/2411.01576","arxiv_id":"2411.01576","published":"2026-09-07"},{"title":"Hyperedge Anomaly Detection with Hypergraph Neural Network","abstract":"Hypergraph is a data structure that enables us to model higher-order associations among data entities. Conventional graph-structured data can represent pairwise relationships only, whereas hypergraph enables us to associate any number of entities, which is essential in many real-life applications. Hypergraph learning algorithms have been well-studied for numerous problem settings, such as node classification, link pr","authors":["Alam, Md. Tanvir","Rahman, Md. Mahmudur","Arefin, Md. Fahim","Ahmed, Chowdhury Farhan","Mahmud, Zisan","Sakib, Md. Sadman"],"url":"https://arxiv.org/abs/2412.05641","arxiv_id":"2412.05641","published":"2026-09-07"},{"title":"Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points","abstract":"Security vulnerabilities in software can have severe consequences; however, manual vulnerability detection is costly and does not scale, especially as agentic coding frameworks increase the rate of code production. Over the last decade, a large body of research has applied machine learning machine learning to automate vulnerability detection (ML4AVD), yet self-reported performance on the most popular datasets shows n","authors":["Ristea, Dan","McFadden, Shae","Shereen, Ezzeldin","Dwyer, Madeleine","Vyas, Sanyam","Hicks, Chris"],"url":"https://arxiv.org/abs/2412.11194","arxiv_id":"2412.11194","published":"2026-09-07"},{"title":"DeltaGNN: Graph Neural Network with Information Flow Control","abstract":"Graph Neural Networks (GNNs) are popular deep learning models designed to process graph-structured data through recursive neighborhood aggregations in the message passing process. When applied to semi-supervised node classification, the message-passing enables GNNs to understand short-range spatial interactions, but also causes them to suffer from over-smoothing and over-squashing. These challenges hinder model expre","authors":["Mancini, Kevin","Rekik, Islem"],"url":"https://arxiv.org/abs/2501.06002","arxiv_id":"2501.06002","published":"2026-09-07"},{"title":"AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications","abstract":"We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its ``eyes," which is the emerging sensing and perception like object detection and tracking, what really distinguishes the DT from a traditional simulator lies in its ``brain," the prediction and decision making capabilities of extracting patterns and ma","authors":["Fu, Yongjie","Turkcan, Mehmet K.","Ghasemi, Mahshid","Mo, Zhaobin","Zang, Chengbo","Adhikari, Abhishek"],"url":"https://arxiv.org/abs/2501.10396","arxiv_id":"2501.10396","published":"2026-09-07"},{"title":"TSMini: A Simple Yet Highly Effective Trajectory Similarity Learning Model","abstract":"Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approximate conventional trajectory similarity measures, exploiting their fast inference time once trained. Although efficient inference has been reported, challenges remain in similarity approximation accuracy due to difficulties in trajectory granularity modeling and in exploiting si","authors":["Chang, Yanchuan","Lyu, Dingyang","Cai, Xu","Jensen, Christian S.","Qi, Jianzhong"],"url":"https://arxiv.org/abs/2502.00285","arxiv_id":"2502.00285","published":"2026-09-07"},{"title":"FSPGD: Rethinking Black-box Attacks on Semantic Segmentation","abstract":"Black-box adversarial attacks on semantic segmentation remain a challenging problem, particularly in the black-box transfer attack setting where perturbations crafted on a surrogate model are expected to mislead unseen target models. Existing methods typically operate only on output logits and thus fail to account for the spatial structure and class-wise feature relationships that are crucial for dense prediction. To","authors":["Park, Eun-Sol","Park, MiSo","Shin, Yong-Goo"],"url":"https://arxiv.org/abs/2502.01262","arxiv_id":"2502.01262","published":"2026-09-07"},{"title":"Graph Foundation Models for Recommendation: A Comprehensive Survey","abstract":"Recommender systems (RS) serve as a fundamental tool for navigating the vast expanse of online information, with deep learning advancements playing an increasingly important role in improving ranking accuracy. Among these, graph neural networks (GNNs) excel at extracting higher-order structural information, while large language models (LLMs) are designed to process and comprehend natural language, making both approac","authors":["Wu, Bin","Wang, Yihang","Zeng, Yuanhao","Liu, Jiawei","Zhao, Jiashu","Yang, Cheng"],"url":"https://arxiv.org/abs/2502.08346","arxiv_id":"2502.08346","published":"2026-09-07"},{"title":"How far can we go with ImageNet for Text-to-Image generation?","abstract":"Recent text-to-image (T2I) generation models have achieved remarkable sucess by training on billion-scale datasets, following a `bigger is better' paradigm that prioritizes data quantity over availability (closed vs open source) and reproducibility (data decay vs established collections). We challenge this established paradigm by demonstrating that one can achieve capabilities of models trained on massive web-scr","authors":["Degeorge, L.","Ghosh, A.","Dufour, N.","Picard, D.","Kalogeiton, V."],"url":"https://arxiv.org/abs/2502.21318","arxiv_id":"2502.21318","published":"2026-09-07"},{"title":"Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks","abstract":"The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering systems; nuclear reactors represent particularly challenging applications for this task due to the complexity of the strongly coupled physics involved and the extremely harsh and hostile environments, especially for new technologies such as Generation-IV reactors. Data-driven ","authors":["Riva, Stefano","Introini, Carolina","Kutz, J. Nathan","Cammi, Antonio"],"url":"https://arxiv.org/abs/2503.08904","arxiv_id":"2503.08904","published":"2026-09-07"},{"title":"AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports","abstract":"Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existing driving video generation methods may produce visually realistic videos, they often fail to deliver physically realistic simulations because they lack the capability to generate accurate post-collision trajectories. In this paper, we introduce AccidentSim, a novel framework th","authors":["Zhang, Xiangwen","Zhang, Qian","Han, Longfei","Qu, Qiang","Chen, Xiaoming","Cai, Weidong"],"url":"https://arxiv.org/abs/2503.20654","arxiv_id":"2503.20654","published":"2026-09-07"},{"title":"Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models","abstract":"Recent advancements in Large Language Models (LLMs) have significantly enhanced their ability to perform complex reasoning tasks, transitioning from fast and intuitive thinking (System 1) to slow and deep reasoning (System 2). While System 2 reasoning improves task accuracy, it often incurs substantial computational costs due to its slow thinking nature and inefficient or unnecessary reasoning behaviors. In contrast,","authors":["Wang, Rui","Wang, Hongru","Xue, Boyang","Pang, Jianhui","Liu, Shudong","Chen, Yi"],"url":"https://arxiv.org/abs/2503.24377","arxiv_id":"2503.24377","published":"2026-09-07"}],"history":{"events":[{"year":2011,"text":"Yak-Service Flight 9633, carrying the players and coaching staff of the ice hockey team Lokomotiv Yaroslavl, crashed on take-off near Yaroslavl, Russia, resulting in the deaths of 44 of the 45 people on board.","url":"https://en.wikipedia.org/wiki/Lokomotiv_Yaroslavl_plane_crash"},{"year":2010,"text":"A Chinese fishing trawler operating in disputed waters collided with Japan Coast Guard patrol boats near the Senkaku Islands, sparking a major diplomatic dispute between the two countries.","url":"https://en.wikipedia.org/wiki/Fishing_trawler"},{"year":2004,"text":"Hurricane Ivan made landfall on Grenada, devastating at least 85 per cent of buildings on the island.","url":"https://en.wikipedia.org/wiki/Hurricane_Ivan"},{"year":1999,"text":"Three weeks after an earthquake struck northwestern Turkey, a second earthquake struck Athens, causing Greece and Turkey to initiate \"earthquake diplomacy\".","url":"https://en.wikipedia.org/wiki/1999_%C4%B0zmit_earthquake"},{"year":1996,"text":"American rapper Tupac Shakur was fatally shot in Paradise, Nevada, dying six days later.","url":"https://en.wikipedia.org/wiki/Tupac_Shakur"},{"year":1986,"text":"Desmond Tutu became the first black leader of the Anglican Church of Southern Africa.","url":"https://en.wikipedia.org/wiki/Desmond_Tutu"},{"year":1984,"text":"An explosion on board a Maltese patrol boat that was disposing of illegal fireworks at sea off Gozo killed seven soldiers and policemen.","url":"https://en.wikipedia.org/wiki/C23_tragedy"},{"year":1940,"text":"Second World War: The Luftwaffe changed their strategy in the Battle of Britain and began bombing London and other cities and towns.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1936,"text":"The last thylacine died in captivity in Hobart Zoo, Australia.","url":"https://en.wikipedia.org/wiki/Thylacine"},{"year":1916,"text":"World War I: The Supreme War Command was established to oversee the armed forces of all the Central Powers.","url":"https://en.wikipedia.org/wiki/World_War_I"},{"year":1901,"text":"With Beijing occupied by foreign troops from the Eight-Nation Alliance, Qing China was forced to sign the Boxer Protocol, an unequal treaty that ended the Boxer Rebellion.","url":"https://en.wikipedia.org/wiki/Eight-Nation_Alliance"},{"year":1822,"text":"Pedro I declared the independence of Brazil from Portugal, establishing the Empire of Brazil (flag pictured).","url":"https://en.wikipedia.org/wiki/Pedro_I_of_Brazil"},{"year":1822,"text":"Pedro I declared the independence of Brazil from Portugal, establishing the Empire of Brazil (flag pictured).","url":"https://en.wikipedia.org/wiki/Pedro_I_of_Brazil"},{"year":1778,"text":"Anglo-French War: Having established an alliance with the United States, France invaded the Caribbean island of Dominica and captured its British fort.","url":"https://en.wikipedia.org/wiki/Anglo-French_War_(1778%E2%80%931783)"},{"year":1652,"text":"Chinese peasants on Formosa (now Taiwan) began a rebellion against Dutch rule which was suppressed four days later.","url":"https://en.wikipedia.org/wiki/Geography_of_Taiwan"},{"year":1642,"text":"First English Civil War: Royalist and Parliamentarian forces clashed in the Battle of Babylon Hill, after which both sides claimed victory.","url":"https://en.wikipedia.org/wiki/First_English_Civil_War"},{"year":1191,"text":"Third Crusade: Crusaders under Richard I of England defeated Ayyubid troops under Saladin at the Battle of Arsuf (depicted) in present-day Israel.","url":"https://en.wikipedia.org/wiki/Third_Crusade"},{"year":1159,"text":"Pope Alexander III was chosen to succeed of Adrian IV in a disputed election.","url":"https://en.wikipedia.org/wiki/Pope_Alexander_III"}],"births":[{"year":2006,"text":"Ian Chen, American actor","url":"https://en.wikipedia.org/wiki/Ian_Chen_(actor)"},{"year":2004,"text":"Tsugumi Aritomo, Japanese entertainer","url":"https://en.wikipedia.org/wiki/Tsugumi_Aritomo"},{"year":2000,"text":"Ariarne Titmus, Australian swimmer","url":"https://en.wikipedia.org/wiki/Ariarne_Titmus"},{"year":1999,"text":"Gracie Abrams, American singer-songwriter","url":"https://en.wikipedia.org/wiki/Gracie_Abrams"},{"year":1999,"text":"Laurie Jussaume, Canadian cyclist","url":"https://en.wikipedia.org/wiki/Laurie_Jussaume"},{"year":1997,"text":"Dean-Charles Chapman, English actor","url":"https://en.wikipedia.org/wiki/Dean-Charles_Chapman"},{"year":1996,"text":"Donovan Mitchell, American basketball player","url":"https://en.wikipedia.org/wiki/Donovan_Mitchell"},{"year":1994,"text":"Elinor Barker, Welsh track cyclist","url":"https://en.wikipedia.org/wiki/Elinor_Barker"}],"deaths":[{"year":2024,"text":"Dan Morgenstern, German-American jazz writer and editor (born 1929)","url":"https://en.wikipedia.org/wiki/Dan_Morgenstern"},{"year":2023,"text":"Wanda Janicka, Polish architect, participant in the Warsaw Uprising (born 1923)","url":"https://en.wikipedia.org/wiki/Wanda_Janicka"},{"year":2018,"text":"Pedro Jirón, Nicaraguan footballer (born 1939)","url":"https://en.wikipedia.org/wiki/Pedro_Jir%C3%B3n"},{"year":2018,"text":"Mac Miller, American rapper (born 1992)","url":"https://en.wikipedia.org/wiki/Mac_Miller"},{"year":2015,"text":"Guillermo Rubalcaba, Cuban pianist, composer, and bandleader (born 1927)","url":"https://en.wikipedia.org/wiki/Guillermo_Rubalcaba"},{"year":2015,"text":"Voula Zouboulaki, Greek actress (born 1924)","url":"https://en.wikipedia.org/wiki/Voula_Zouboulaki"},{"year":2014,"text":"Kwon Ri-se, South Korean singer (born 1991)","url":"https://en.wikipedia.org/wiki/Kwon_Ri-se"},{"year":2014,"text":"Raul M. Gonzalez, Filipino lawyer and politician, 42nd Filipino Secretary of Justice (born 1930)","url":"https://en.wikipedia.org/wiki/Raul_M._Gonzalez"}]},"census":{"panel_version":2,"probed":14770,"error_rate":37.56,"degraded":true,"rates":{"head":9.5,"tail":3.7,"ai_native":75.45}},"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","license":"CC BY-SA 4.0","attribution":"Wikipedia contributors"},{"id":"frontier","name":"Hacker News","url":"https://news.ycombinator.com","license":"Public API — titles and links, credited","attribution":"Hacker News / Y Combinator"},{"id":"research","name":"arXiv cs.AI","url":"https://arxiv.org","license":"Open metadata, per arXiv API terms","attribution":"arXiv.org"},{"id":"history","name":"Wikipedia On this day","url":"https://api.wikimedia.org","license":"CC BY-SA 4.0","attribution":"Wikipedia contributors"}],"license":"Records are CC BY-SA 4.0, inheriting from Wikipedia. Every item links to its source."}