{"date":"2026-07-14","schema_version":1,"captured_at":"2026-08-25T23:16:07.247Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":17},"attention":[{"title":"Sam Neill","views":2453026,"rank":2,"extract":"Sir Nigel John Dermot \"Sam\" Neill was a New Zealand actor. Known as a leading man in film and television, he received nominations for three Primetime Emmy Awards and two Golden Globe Awards. 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Linux","points":230,"comments":174,"url":"https://parksb.github.io/en/article/41.html","discussion":"https://news.ycombinator.com/item?id=48907063"},{"title":"Indian scientists produce most detailed 3D atlas of the human brainstem","points":219,"comments":22,"url":"https://www.bbc.com/news/articles/cg53l737v1qo","discussion":"https://news.ycombinator.com/item?id=48903082"},{"title":"Dependabot version updates introduce default package cooldown","points":209,"comments":143,"url":"https://github.blog/changelog/2026-07-14-dependabot-version-updates-introduce-default-package-cooldown/","discussion":"https://news.ycombinator.com/item?id=48913050"},{"title":"Microsoft has released software updates to plug at least 570 security holes","points":208,"comments":122,"url":"https://krebsonsecurity.com/2026/07/microsoft-patches-a-record-570-security-flaws/","discussion":"https://news.ycombinator.com/item?id=48913190"},{"title":"The Zen of Parallel Programming","points":189,"comments":43,"url":"https://smolnero.com/posts/the-zen-of-parallel-programming","discussion":"https://news.ycombinator.com/item?id=48907390"},{"title":"Proof of care in the age of AI","points":185,"comments":110,"url":"https://jacobfilipp.com/care/","discussion":"https://news.ycombinator.com/item?id=48906125"}],"research":[{"title":"Improved Answer Selection with Pre-Trained Word Embeddings","abstract":"This paper evaluates existing and newly proposed answer selection methods based on pre-trained word embeddings. Word embeddings are highly effective in various natural language processing tasks and their integration into traditional information retrieval (IR) systems allows for the capture of semantic relatedness between questions and answers. Empirical results on three publicly available data sets show significant g","authors":["Chakravarti, Rishav","Navratil, Jiri","Santos, Cicero Nogueira dos"],"url":"https://arxiv.org/abs/1708.04326","arxiv_id":"1708.04326","published":"2026-07-14"},{"title":"Learning to Schedule in Parallel-Server Queues with Stochastic Bilinear Rewards","abstract":"We consider the problem of scheduling in multi-class, parallel-server queuing systems with uncertain rewards from job-server assignments. In this scenario, jobs incur holding costs while awaiting completion, and job-server assignments yield observable stochastic rewards with unknown mean values. The mean rewards for job-server assignments are assumed to follow a bilinear model with respect to features that characteri","authors":["Kim, Jung-hun","Vojnovic, Milan"],"url":"https://arxiv.org/abs/2112.06362","arxiv_id":"2112.06362","published":"2026-07-14"},{"title":"Research on Cross-media Science and Technology Information Data Retrieval","abstract":"Since the era of big data, the Internet has been flooded with all kinds of information. Browsing information through the Internet has become an integral part of people's daily life. Unlike news data and social data on the Internet, cross-media science and technology information data has different characteristics. This data has become an important basis for researchers and scholars to track current hot spots and e","authors":["Jiang, Yang","Xue, Zhe","Li, Ang"],"url":"https://arxiv.org/abs/2204.04887","arxiv_id":"2204.04887","published":"2026-07-14"},{"title":"Research on Intellectual Property Resource Profile and Evolution Law","abstract":"In the era of big data, intellectual property-oriented scientific and technological resources show the trend of large data scale, high information density, and low value density, which brings severe challenges to the effective use of intellectual property resources, and the demand for mining hidden information in intellectual property is increasing. This makes intellectual property-oriented science and technology res","authors":["Wang, Yuhui","Shao, Yingxia","Li, Ang"],"url":"https://arxiv.org/abs/2204.06221","arxiv_id":"2204.06221","published":"2026-07-14"},{"title":"Profiling and Evolution of Intellectual Property","abstract":"In recent years, with the rapid growth of Internet data, the number and types of scientific and technological resources are also rapidly expanding. However, the increase in the number and category of information data will also increase the cost of information acquisition. For technology-based enterprises or users, in addition to general papers, patents, and other resources, policies related to technology or the devel","authors":["Yu, Bowen","Shao, Yingxia","Li, Ang"],"url":"https://arxiv.org/abs/2204.09333","arxiv_id":"2204.09333","published":"2026-07-14"},{"title":"Unmatched uncertainty mitigation through neural network supported model predictive control","abstract":"This paper presents a deep learning based model predictive control (MPC) algorithm for systems with unmatched and bounded state-action dependent uncertainties of unknown structure. We utilize a deep neural network (DNN) as an oracle in the underlying optimization problem of learning based MPC (LBMPC) to estimate unmatched uncertainties. Generally, non-parametric oracles such as DNN are considered difficult to employ ","authors":["Gasparino, Mateus V.","Mishra, Prabhat K.","Chowdhary, Girish"],"url":"https://arxiv.org/abs/2304.11315","arxiv_id":"2304.11315","published":"2026-07-14"},{"title":"Interventions Against Machine-Assisted Statistical Discrimination","abstract":"I study statistical discrimination driven by verifiable beliefs, such as those generated by machine learning, rather than by humans. When beliefs are verifiable, interventions against statistical discrimination can move beyond simple belief-free designs, like affirmative action and blinding, to more sophisticated belief-contingent ones. I analyze a belief-contingent intervention, common identity, and show that it can","authors":["Zhu, John Y."],"url":"https://arxiv.org/abs/2310.04585","arxiv_id":"2310.04585","published":"2026-07-14"},{"title":"New Advances in Body Composition Assessment with ShapedNet: A Single Image Deep Regression Approach","abstract":"We introduce a novel technique called ShapedNet to enhance body composition assessment. This method employs a deep neural network capable of estimating Body Fat Percentage (BFP), performing individual identification, and enabling localization using a single photograph. The accuracy of ShapedNet is validated through comprehensive comparisons against the gold standard method, Dual-Energy X-ray Absorptiometry (DXA), uti","authors":["Nascimento, Navar Medeiros M.","Junior, Pedro Cavalcante de Sousa","Nunes, Pedro Yuri Rodrigues","da Silva, Suane Pires Pinheiro","Loureiro, Luiz Lannes","Bittencourt, Victor Zaban"],"url":"https://arxiv.org/abs/2310.09709","arxiv_id":"2310.09709","published":"2026-07-14"},{"title":"Federated Topic Model and Model Pruning Based on Variational Autoencoder","abstract":"Topic modeling has emerged as a valuable tool for discovering patterns and topics within large collections of documents. However, when cross-analysis involves multiple parties, data privacy becomes a critical concern. Federated topic modeling has been developed to address this issue, allowing multiple parties to jointly train models while protecting privacy. However, there are communication and performance challenges","authors":["Ma, Chengjie","Li, Yawen","Liang, Meiyu","Li, Ang"],"url":"https://arxiv.org/abs/2311.00314","arxiv_id":"2311.00314","published":"2026-07-14"},{"title":"Dress-Me-Up: A Dataset & Method for Self-Supervised 3D Garment Retargeting","abstract":"We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON). Existing self-supervised 3D retargeting methods only support parametric and canonical garments, which can only be draped over parametric body, e.g. SMPL. To facilitate the non-parametric garments and body, we propose a novel method that intr","authors":["Naik, Shanthika","Singh, Kunwar","Srivastava, Astitva","Sirikonda, Dhawal","Raj, Amit","Jampani, Varun"],"url":"https://arxiv.org/abs/2401.03108","arxiv_id":"2401.03108","published":"2026-07-14"},{"title":"HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA","abstract":"Retrieval-augmented generation (RAG) has rapidly advanced the language model field, particularly in question-answering (QA) systems. By integrating external documents during the response generation phase, RAG significantly enhances the accuracy and reliability of language models. This method elevates the quality of responses and reduces the frequency of hallucinations, where the model generates incorrect or misleadin","authors":["Chen, Xinyue","Gao, Pengyu","Song, Jiangjiang","Tan, Xiaoyang"],"url":"https://arxiv.org/abs/2402.01767","arxiv_id":"2402.01767","published":"2026-07-14"},{"title":"Randomized Confidence Bounds for Stochastic Partial Monitoring","abstract":"The partial monitoring (PM) framework provides a theoretical formulation of sequential learning problems with incomplete feedback. On each round, a learning agent plays an action while the environment simultaneously chooses an outcome. The agent then observes a feedback signal that is only partially informative about the (unobserved) outcome. The agent leverages the received feedback signals to select actions that mi","authors":["Heuillet, Maxime","Ahmad, Ola","Durand, Audrey"],"url":"https://arxiv.org/abs/2402.05002","arxiv_id":"2402.05002","published":"2026-07-14"},{"title":"Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms","abstract":"The sim-to-real gap, which represents the disparity between training and testing environments, poses a significant challenge in reinforcement learning (RL). A promising approach to addressing this challenge is distributionally robust RL, often framed as a robust Markov decision process (RMDP). In this framework, the objective is to find a robust policy that achieves good performance under the worst-case scenario amon","authors":["Lu, Miao","Zhong, Han","Zhang, Tong","Blanchet, Jose"],"url":"https://arxiv.org/abs/2404.03578","arxiv_id":"2404.03578","published":"2026-07-14"},{"title":"Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing","abstract":"Deep learning-based malware detection systems are vulnerable to adversarial EXEmples - carefully-crafted malicious programs that evade detection with minimal perturbation. As such, the community is dedicating effort to develop mechanisms to defend against adversarial EXEmples. However, current randomized smoothing-based defenses are still vulnerable to attacks that inject blocks of adversarial content. In this paper,","authors":["Gibert, Daniel","Demetrio, Luca","Zizzo, Giulio","Le, Quan","Planes, Jordi","Biggio, Battista"],"url":"https://arxiv.org/abs/2405.00392","arxiv_id":"2405.00392","published":"2026-07-14"},{"title":"Neural Active Learning Meets the Partial Monitoring Framework","abstract":"We focus on the online-based active learning (OAL) setting where an agent operates over a stream of observations and trades-off between the costly acquisition of information (labelled observations) and the cost of prediction errors. We propose a novel foundation for OAL tasks based on partial monitoring, a theoretical framework specialized in online learning from partially informative actions. We show that previously","authors":["Heuillet, Maxime","Ahmad, Ola","Durand, Audrey"],"url":"https://arxiv.org/abs/2405.08921","arxiv_id":"2405.08921","published":"2026-07-14"},{"title":"Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need","abstract":"The introduction of 5G technology has revolutionized communications, enabling unprecedented capacity, connectivity, and ultra-fast, reliable communications. However, this leap has led to a substantial increase in energy consumption, presenting a critical challenge for network sustainability. Accurate energy consumption modeling is essential for developing energy-efficient strategies, enabling operators to optimize re","authors":["Chen, Tingwei","Wang, Yantao","Chen, Hanzhi","Zhao, Zijian","Li, Xinhao","Piovesan, Nicola"],"url":"https://arxiv.org/abs/2406.16929","arxiv_id":"2406.16929","published":"2026-07-14"},{"title":"PanDORA: Casual HDR Radiance Acquisition of Indoor Scenes for Image-based Lighting","abstract":"Most novel view synthesis methods -- including Neural Radiance Fields (NeRF) -- struggle to capture the high dynamic range (HDR) radiance required for realistic image-based lighting (IBL). This limitation stems from a reliance on low dynamic range (LDR) imagery, which fails to capture the intensity of light sources found in indoor environments. While exposure bracketing can recover this range, it is often too slow fo","authors":["Dastjerdi, Mohammad Reza Karimi","Tanguay-Gaudreau, Dominique","Fortier-Chouinard, Frédéric","Hold-Geoffroy, Yannick","Kalantari, Nima","Lalonde, Jean-François"],"url":"https://arxiv.org/abs/2407.06150","arxiv_id":"2407.06150","published":"2026-07-14"},{"title":"A DeepONet for inverting the Neumann-to-Dirichlet Operator in Electrical Impedance Tomography: An approximation theoretic perspective and numerical results","abstract":"In this work, we consider the non-invasive medical imaging modality of Electrical Impedance Tomography (EIT), where the goal is to recover the conductivity in a medium from boundary current-to-voltage measurements, i.e., the Neumann-to-Dirichlet (N--t--D) operator. We formulate this inverse problem as an operator-learning task, where the aim is to approximate the implicitly defined map from N--t--D operators to admis","authors":["Abhishek, Anuj","Strauss, Thilo"],"url":"https://arxiv.org/abs/2407.17182","arxiv_id":"2407.17182","published":"2026-07-14"},{"title":"Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models","abstract":"The imitation of cursive handwriting is mainly limited to generating handwritten words or lines. Multiple synthetic outputs must be stitched together to create paragraphs or whole pages, whereby consistency and layout information are lost. To close this gap, we propose a method for imitating handwriting at the paragraph level that also works for unseen writing styles. Therefore, we introduce a modified latent diffusi","authors":["Mayr, Martin","Dreier, Marcel","Kordon, Florian","Seuret, Mathias","Zöllner, Jochen","Wu, Fei"],"url":"https://arxiv.org/abs/2409.00786","arxiv_id":"2409.00786","published":"2026-07-14"},{"title":"Training on Irrelevant States Implies Data Augmentation: Generalization in Contextual MDPs","abstract":"In the zero-shot policy transfer (ZSPT) setting for contextual Markov decision processes (CMDP), agents train on a fixed, finite set of contexts and must generalize to new ones. Recent work has demonstrated that training on additional states, even if they are irrelevant for solving the current context, can improve generalization to unseen contexts. In this paper, we demonstrate that training on these states can indee","authors":["Weltevrede, Max","Horsch, Caroline","Spaan, Matthijs T. J.","Böhmer, Wendelin"],"url":"https://arxiv.org/abs/2410.03565","arxiv_id":"2410.03565","published":"2026-07-14"},{"title":"Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning","abstract":"A hallmark of intelligent agents is the ability to learn reusable skills purely from unsupervised interaction with the environment. However, existing unsupervised skill discovery methods often learn entangled skills where one skill variable simultaneously influences many entities in the environment, making downstream skill chaining extremely challenging. We propose Disentangled Unsupervised Skill Discovery (DUSDi), a","authors":["Hu, Jiaheng","Wang, Zizhao","Stone, Peter","Martín-Martín, Roberto"],"url":"https://arxiv.org/abs/2410.11251","arxiv_id":"2410.11251","published":"2026-07-14"},{"title":"On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes","abstract":"This paper explores the impact of occlusions in video action detection. We facilitate this study by introducing five new benchmark datasets namely O-UCF and O-JHMDB consisting of synthetically controlled static/dynamic occlusions, OVIS-UCF and OVIS-JHMDB consisting of occlusions with realistic motions and Real-OUCF for occlusions in realistic-world scenarios. We formally confirm an intuitive expectation: existing mod","authors":["Modi, Rajat","Vineet, Vibhav","Rawat, Yogesh Singh"],"url":"https://arxiv.org/abs/2410.19553","arxiv_id":"2410.19553","published":"2026-07-14"},{"title":"Asynchronous Perception Machine For Efficient Test-Time-Training","abstract":"In this work, we propose Asynchronous Perception Machine (APM), a computationally-efficient architecture for test-time-training (TTT). APM can process patches of an image one at a time in any order asymmetrically and still encode semantic-awareness in the net. We demonstrate APM's ability to recognize out-of-distribution images without dataset-specific pre-training, augmentation or any-pretext task. APM offers co","authors":["Modi, Rajat","Rawat, Yogesh Singh"],"url":"https://arxiv.org/abs/2410.20535","arxiv_id":"2410.20535","published":"2026-07-14"},{"title":"Big data approach to Kazhdan-Lusztig polynomials","abstract":"We investigate the structure of Kazhdan-Lusztig polynomials of the symmetric group by leveraging computational approaches from big data, including exploratory and topological data analysis, applied to the polynomials for symmetric groups of up to 11 strands.","authors":["Lacabanne, Abel","Tubbenhauer, Daniel","Vaz, Pedro"],"url":"https://arxiv.org/abs/2412.01283","arxiv_id":"2412.01283","published":"2026-07-14"},{"title":"SparseLGS: Sparse View Language Embedded Gaussian Splatting","abstract":"Recently, several studies have combined Gaussian Splatting to obtain scene representations with language embeddings for open-vocabulary 3D scene understanding. While these methods perform well, they essentially require very dense multi-view inputs, limiting their applicability in real-world scenarios. In this work, we propose SparseLGS to address the challenge of 3D scene understanding with pose-free and sparse view ","authors":["Hu, Jun","Chen, Zhang","Li, Zhong","Xu, Yi","Zhang, Juyong"],"url":"https://arxiv.org/abs/2412.02245","arxiv_id":"2412.02245","published":"2026-07-14"}],"history":{"events":[{"year":2016,"text":"A man deliberately drove a truck into crowds in Nice, France, resulting in 86 deaths.","url":"https://en.wikipedia.org/wiki/2016_Nice_truck_attack"},{"year":2014,"text":"Lightning strikes started four fires in the Methow Valley in the U.S. state of Washington, collectively known as the Carlton Complex Fire.","url":"https://en.wikipedia.org/wiki/Methow_River"},{"year":2003,"text":"Valerie Plame's identity as a CIA operative was leaked to and published by journalist Robert Novak.","url":"https://en.wikipedia.org/wiki/Valerie_Plame"},{"year":1987,"text":"More than 100 mm (3.9 in) of rain fell in a two-and-a-half-hour period in parts of Montreal, causing severe flooding.","url":"https://en.wikipedia.org/wiki/Montreal_flood_of_1987"},{"year":1960,"text":"Northwest Orient Airlines Flight 1-11 ditched off Polillo Island in the Philippines, killing one person and injuring 44 others.","url":"https://en.wikipedia.org/wiki/Northwest_Orient_Airlines_Flight_1-11"},{"year":1950,"text":"Korean War: North Korean troops began attacking the headquarters of the American 24th Infantry Division in present-day Daejeon, South Korea.","url":"https://en.wikipedia.org/wiki/Korean_War"},{"year":1916,"text":"The Battle of Delville Wood began as an action within the Battle of the Somme, lasting until 3 September 1916.","url":"https://en.wikipedia.org/wiki/Battle_of_Delville_Wood"},{"year":1902,"text":"The medieval St Mark's Campanile in Venice collapsed, also demolishing the Loggetta del Sansovino.","url":"https://en.wikipedia.org/wiki/St_Mark's_Campanile"},{"year":1902,"text":"An expedition led by Peruvian explorer and farmer Agustín Lizárraga discovered the Incan city of Machu Picchu (pictured).","url":"https://en.wikipedia.org/wiki/Agust%C3%ADn_Liz%C3%A1rraga"},{"year":1881,"text":"While on the run from a death sentence, American outlaw Billy the Kid was shot and killed by Sherriff Pat Garrett in Fort Sumner, New Mexico.","url":"https://en.wikipedia.org/wiki/Billy_the_Kid"},{"year":1874,"text":"A fire destroyed 812 structures and killed 20 people in Chicago, leading to reforms in the city's fire-prevention and firefighting efforts.","url":"https://en.wikipedia.org/wiki/Chicago_Fire_of_1874"},{"year":1865,"text":"A seven-man mountaineering team made the first ascent of the Matterhorn, marking the end of the golden age of alpinism.","url":"https://en.wikipedia.org/wiki/First_ascent_of_the_Matterhorn"},{"year":1798,"text":"The Sedition Act became law, making it a federal crime to write, publish, or utter false or malicious statements about the U.S. federal government.","url":"https://en.wikipedia.org/wiki/Alien_and_Sedition_Acts"},{"year":1791,"text":"The Priestley Riots, targeting religious dissenters such as Joseph Priestley, began in Birmingham, England.","url":"https://en.wikipedia.org/wiki/Priestley_Riots"},{"year":1789,"text":"The Bastille, a fortress and prison in Paris, was stormed by a crowd during the flashpoint of the French Revolution.","url":"https://en.wikipedia.org/wiki/Bastille"},{"year":1455,"text":"1454–1466 Thirteen Years' War: The Battle for Kneiphof ended with a decisive victory for the Teutonic Order.","url":"https://en.wikipedia.org/wiki/Thirteen_Years'_War_(1454%E2%80%931466)"},{"year":1223,"text":"Louis VIII (seal pictured) began his three-year reign as King of France.","url":"https://en.wikipedia.org/wiki/Louis_VIII_of_France"}],"births":[{"year":2004,"text":"Noah Clowney, American basketball player","url":"https://en.wikipedia.org/wiki/Noah_Clowney"},{"year":2003,"text":"Haley Winn, American hockey player","url":"https://en.wikipedia.org/wiki/Haley_Winn"},{"year":1997,"text":"Neekolul, American internet personality","url":"https://en.wikipedia.org/wiki/Neekolul"},{"year":1995,"text":"Harrison Butker, American football player","url":"https://en.wikipedia.org/wiki/Harrison_Butker"},{"year":1995,"text":"Kim In-hyeok, South Korean volleyball player (died 2022)","url":"https://en.wikipedia.org/wiki/Kim_In-hyeok"},{"year":1994,"text":"Lucas Giolito, American baseball player","url":"https://en.wikipedia.org/wiki/Lucas_Giolito"},{"year":1990,"text":"Paulo Muacho, Portuguese politician","url":"https://en.wikipedia.org/wiki/Paulo_Muacho"},{"year":1988,"text":"Conor McGregor, Irish mixed martial artist","url":"https://en.wikipedia.org/wiki/Conor_McGregor"}],"deaths":[{"year":2025,"text":"B. Saroja Devi, Indian actress (born 1938)","url":"https://en.wikipedia.org/wiki/B._Saroja_Devi"},{"year":2025,"text":"Andrea Gibson, American poet and activist (born 1975)","url":"https://en.wikipedia.org/wiki/Andrea_Gibson"},{"year":2025,"text":"John MacArthur, American evangelical preacher (born 1939)","url":"https://en.wikipedia.org/wiki/John_MacArthur_(American_pastor)"},{"year":2025,"text":"Fauja Singh, British-Indian centenarian marathon runner","url":"https://en.wikipedia.org/wiki/Fauja_Singh"},{"year":2024,"text":"Jacoby Jones, American football player (born 1984)","url":"https://en.wikipedia.org/wiki/Jacoby_Jones"},{"year":2022,"text":"Ivana Trump, Czech-American socialite and model (born 1949)","url":"https://en.wikipedia.org/wiki/Ivana_Trump"},{"year":2020,"text":"Rosa, Spanish-born cow on French television (born 2001)","url":"https://en.wikipedia.org/wiki/Rosa_(cow)"},{"year":2017,"text":"Maryam Mirzakhani, Iranian mathematician (born 1977)","url":"https://en.wikipedia.org/wiki/Maryam_Mirzakhani"}]},"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."}