{"date":"2026-07-17","schema_version":1,"captured_at":"2026-08-25T23:16:32.361Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"The Odyssey (2026 film)","views":614398,"rank":4,"extract":"The Odyssey is a 2026 epic action fantasy film written and directed by Christopher Nolan, who produced it with his wife Emma Thomas. 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We propose the 'Cross-Cluster Weighted Forest' (CCWF), an ensembling approach that explicitly leverages heterogeneity in the feature distribution to produce more accurate and more generalizable predictors than the standard Random Fores","authors":["Ramchandran, Maya","Mukherjee, Rajarshi","Parmigiani, Giovanni"],"url":"https://arxiv.org/abs/2105.07610","arxiv_id":"2105.07610","published":"2026-07-17"},{"title":"Beyond Interestingness: Semantic and Context-Aware Natural Language Query Recommendations for Visual Data Analysis","abstract":"Recent advances in large language models (LLMs) have made natural language interfaces (NLIs) widely accessible for data exploration, yet analysts who have a broad analytical objective still face the challenge of decomposing it into effective step-by-step queries, especially over unfamiliar, multi-table relational databases. Rather than generating high-level analytical agendas, we investigate how to augment an NLI wit","authors":["Wang, Xingbo","Li, Siyuan","Cheng, Furui","Wang, Yong","Long, Jiang","Lu, Hong"],"url":"https://arxiv.org/abs/2201.04868","arxiv_id":"2201.04868","published":"2026-07-17"},{"title":"Bridging the Gap between Newton-Raphson Method and Regularized Policy Iteration","abstract":"Regularization is a cornerstone of modern reinforcement learning. Regularized policy iteration (RPI) provides a fundamental scheme for solving regularized Markov decision processes (RMDPs), and the widely used soft actor-critic algorithm arises as a special case when the regularizer is Shannon entropy. Despite its empirical success, the theoretical underpinnings of RPI remain unclear. In this paper, we address this g","authors":["Li, Zeyang","Hu, Chuxiong","Wang, Yunan","Zhan, Guojian","Li, Jie","Lyu, Yao"],"url":"https://arxiv.org/abs/2310.07211","arxiv_id":"2310.07211","published":"2026-07-17"},{"title":"All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Media","abstract":"Online polarization has attracted the attention of researchers for many years. Its effects on society are a cause for concern, and the design of personalized depolarization strategies appears to be a key solution. Such strategies should rely on a fine and accurate measurement, and a clear understanding of polarization behaviors. However, the literature still lacks ways to characterize them finely. We propose GRAIL, t","authors":["Treuillier, Celina","Castagnos, Sylvain","Brun, Armelle"],"url":"https://arxiv.org/abs/2312.04603","arxiv_id":"2312.04603","published":"2026-07-17"},{"title":"Seeing Through Uncertainty: Free-Energy-Inspired Real-Time Adaptation for Robust Visual Navigation","abstract":"Navigation in the natural world is a feat of adaptive inference, where biological organisms maintain goal-directed behaviour despite noisy and incomplete sensory streams. Central to this ability is the Free Energy Principle (FEP), which posits that perception is a generative process where the brain minimises Variational Free Energy (VFE) to maintain accurate internal models of the world. While Deep Neural Networks (D","authors":["Piriyajitakonkij, Maytus","Yadav, Rishabh Dev","Sun, Mingfei","Zhang, Mengmi","Pan, Wei"],"url":"https://arxiv.org/abs/2403.01977","arxiv_id":"2403.01977","published":"2026-07-17"},{"title":"A short review on the maximum clique problem algorithms with classical, AI, and quantum methods","abstract":"This manuscript provides a comprehensive review of the Maximum Clique Problem, a computational problem that involves finding subsets of vertices in a graph that are all pairwise adjacent to each other. As such, this review is a continuation of the series of previous reviews from 1994, 1999 and 2014. The manuscript covers in a simple way classical algorithms and includes a review of recent developments in graph neural","authors":["Marino, Raffaele","Buffoni, Lorenzo","Zavalnij, Bogdan"],"url":"https://arxiv.org/abs/2403.09742","arxiv_id":"2403.09742","published":"2026-07-17"},{"title":"Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network","abstract":"The cellular network of magnetic Induction (MI) communication holds promise in long-distance underground environments. In the traditional MI communication, there is no fast-fading channel since the MI channel is treated as a quasi-static channel. However, for the vehicle (mobile) MI (VMI) communication, the unpredictable antenna vibration brings the remarkable fast-fading. As such fast-fading cannot be modeled by the","authors":["Ma, Honglei","Liu, Erwu","Fang, Zhijun","Wang, Rui","Gao, Yongbin","Yu, Wenjun"],"url":"https://arxiv.org/abs/2406.04737","arxiv_id":"2406.04737","published":"2026-07-17"},{"title":"QDA-SQL: Questions Enhanced Dialogue Augmentation for Multi-Turn Text-to-SQL","abstract":"Fine-tuning large language models (LLMs) for specific domain tasks has achieved great success in Text-to-SQL tasks. However, these fine-tuned models often face challenges with multi-turn Text-to-SQL tasks caused by ambiguous or unanswerable questions. It is desired to enhance LLMs to handle multiple types of questions in multi-turn Text-to-SQL tasks. To address this, we propose a novel data augmentation method, calle","authors":["Sun, Yinggang","Guo, Ziming","Yu, Haining","Liu, Chuanyi","Li, Xiang","Wang, Bingxuan"],"url":"https://arxiv.org/abs/2406.10593","arxiv_id":"2406.10593","published":"2026-07-17"},{"title":"Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis","abstract":"Deep neural networks have demonstrated remarkable effectiveness across a wide range of tasks such as semantic segmentation. Nevertheless, these networks are vulnerable to adversarial attacks that add imperceptible perturbations to the input image, leading to false predictions. This vulnerability is particularly dangerous in safety-critical applications like automated driving. While adversarial examples and defense st","authors":["Maag, Kira","Resner, Roman","Fischer, Asja"],"url":"https://arxiv.org/abs/2408.10021","arxiv_id":"2408.10021","published":"2026-07-17"},{"title":"Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities","abstract":"Machine Learning (ML) has become central to Autonomous Vehicles (AVs), supporting perception, prediction, planning, control, and decision-making in dynamic environments. However, achieving full autonomy in cluttered and complex scenarios, such as intricate intersections, diverse scenes, varied trajectories, and complex missions, remains challenging; moreover, data labeling is still a major bottleneck. These limitatio","authors":["Emami, Yousef","Homaei, Mohammadhossein","Gaitán, Miguel Gutiérrez","Almeida, Luis","Li, Kai","Huang, Hui"],"url":"https://arxiv.org/abs/2408.12548","arxiv_id":"2408.12548","published":"2026-07-17"},{"title":"Empirical evidence of Large Language Model's influence on human spoken communication","abstract":"From the printing press to social media, innovations in communication technology have repeatedly reshaped how ideas spread through human culture. Chatbots powered by generative artificial intelligence constitute a new medium, encoding cultural patterns in their neural representations and disseminating them in conversations with hundreds of millions of people. Whether these patterns transmit into human language, and u","authors":["Yakura, Hiromu","Lopez-Lopez, Ezequiel","Brinkmann, Levin","de la Serna, Ignacio","Kirfel, Lara","Gupta, Prateek"],"url":"https://arxiv.org/abs/2409.01754","arxiv_id":"2409.01754","published":"2026-07-17"},{"title":"When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?","abstract":"The deployment of large language models (LLMs) like ChatGPT and Gemini has shown their powerful natural language generation capabilities. However, these models can inadvertently learn and retain sensitive information and harmful content during training, raising significant ethical and legal concerns. To address these issues, machine unlearning has been introduced as a potential solution. While existing unlearning met","authors":["Wang, Shang","Zhu, Tianqing","Ye, Dayong","Zhou, Wanlei"],"url":"https://arxiv.org/abs/2410.15267","arxiv_id":"2410.15267","published":"2026-07-17"},{"title":"PERL: Pinyin Enhanced Rephrasing Language Model for Chinese ASR N-best Error Correction","abstract":"Chinese ASR correction is challenging because errors are often \\emph{phonetic} (many characters share similar Pinyin) while the correction model must also obey a \\emph{length constraint} under noisy N-best hypotheses. Existing approaches either exploit Pinyin only at the prompt/feature level without integrating it into model representations or rely on generative decoding that can drift in length. We propose \\textbf{P","authors":["Liang, Junhong","Zhang, Bojun"],"url":"https://arxiv.org/abs/2412.03230","arxiv_id":"2412.03230","published":"2026-07-17"},{"title":"Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces","abstract":"We study distributionally robust optimization (DRO) for robust inference when the worst-case distribution is continuous, leading to significant computational challenges due to the infinite-dimensional nature of the optimization problem. Unlike traditional discrete DRO approaches, which often suffer from scalability issues, limited generalization, and costly worst-case inference, our framework exploits Brenier's t","authors":["Zhu, Linglingzhi","Zhu, Yunqin","Xie, Yao"],"url":"https://arxiv.org/abs/2412.20556","arxiv_id":"2412.20556","published":"2026-07-17"},{"title":"Federated Deep Subspace Clustering","abstract":"This paper introduces FDSC, a private-protected subspace clustering (SC) approach with federated learning (FC) schema. In each client, there is a deep subspace clustering network accounting for grouping the isolated data, composed of a encode network, a self-expressive layer, and a decode network. FDSC is achieved by uploading the encode network to communicate with other clients in the server. Besides, FDSC is also e","authors":["Zhang, Yupei","Feng, Ruojia","Wang, Yifei","Shang, Xuequn"],"url":"https://arxiv.org/abs/2501.00230","arxiv_id":"2501.00230","published":"2026-07-17"},{"title":"The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models","abstract":"The recent rise in the popularity of large language models has spurred the development of extensive code datasets needed to train them. This has left limited code available for collection and use in the downstream investigation of specific behaviors, or evaluation of large language models without suffering from data contamination. To address this problem, we release The Heap, a large multilingual dataset covering 57 ","authors":["Katzy, Jonathan","Popescu, Razvan Mihai","van Deursen, Arie","Izadi, Maliheh"],"url":"https://arxiv.org/abs/2501.09653","arxiv_id":"2501.09653","published":"2026-07-17"},{"title":"GenTL: A General Transfer Learning Model for Building Thermal Dynamics","abstract":"Transfer Learning (TL) is an emerging field in modeling building thermal dynamics. This method reduces the data required for a data-driven model of a target building by leveraging knowledge from a source building. Consequently, it enables the creation of data-efficient models that can be used for advanced control and fault detection & diagnosis. A major limitation of the TL approach is its inconsistent performanc","authors":["Raisch, Fabian","Krug, Thomas","Goebel, Christoph","Tischler, Benjamin"],"url":"https://arxiv.org/abs/2501.13703","arxiv_id":"2501.13703","published":"2026-07-17"},{"title":"A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization","abstract":"We study a class of stochastic nonsmooth optimization problems in which an outer variable minimizes the expectation of a pointwise maximum. This minimization--expectation--maximization (minEmax) problem arises in Wasserstein distributionally robust optimization and adversarially robust training, and it cannot in general be reformulated as a finite-dimensional minimax problem when the underlying distribution is not em","authors":["Liu, Wei","Khan, Muhammad","Mancino-Ball, Gabriel","Xu, Yangyang"],"url":"https://arxiv.org/abs/2502.17602","arxiv_id":"2502.17602","published":"2026-07-17"},{"title":"Simulating Automotive Radar with Lidar and Camera Inputs","abstract":"Low-cost millimeter automotive radar has received more and more attention due to its ability to handle adverse weather and lighting conditions in autonomous driving. However, the lack of quality datasets hinders research and development. We report a new method that is able to simulate 4D millimeter wave radar signals including pitch, yaw, range, and Doppler velocity along with radar signal strength (RSS) using camera","authors":["Song, Peili","Song, Dezhen","Yang, Yifan","Lan, Enfan","Liu, Jingtai"],"url":"https://arxiv.org/abs/2503.08068","arxiv_id":"2503.08068","published":"2026-07-17"},{"title":"Reinforcement Learning in Switching Non-Stationary Markov Decision Processes: Algorithms and Convergence Analysis","abstract":"We introduce the Switching Non-Stationary Markov Decision Process (SNS-MDP) framework, in which the environment transitions among a finite set of MDPs governed by a latent Markov chain while the agent observes only the external state. We show that the long-term effect of this switching is equivalent to stationary dynamics parameterized by the stationary distribution of the hidden Markov chain. For fixed policies, we ","authors":["Amiri, Mohsen","Magnússon, Sindri"],"url":"https://arxiv.org/abs/2503.18607","arxiv_id":"2503.18607","published":"2026-07-17"},{"title":"Scaling Evaluation-time Compute with Reasoning Models as Evaluators","abstract":"As language model (LM) outputs get more and more natural, it is becoming more difficult than ever to evaluate their quality. Simultaneously, increasing LMs' "thinking" time through scaling test-time compute has proven an effective technique to solve challenging problems in domains such as math and code. This raises a natural question: can an LM's evaluation capability also be improved by spending more","authors":["Kim, Seungone","Wu, Ian","Lee, Jinu","Yue, Xiang","Lee, Seongyun","Moon, Mingyeong"],"url":"https://arxiv.org/abs/2503.19877","arxiv_id":"2503.19877","published":"2026-07-17"},{"title":"Limits of Discrete Energy of Families of Increasing Sets","abstract":"The Hausdorff dimension of a set can be detected using the Riesz energy. Here, we consider situations where a sequence of points, $\\{x_n\\}$, ``fills in'' a set $E \\subset \\mathbb{R}^d$ in an appropriate sense and investigate the degree to which the discrete analog to the Riesz energy of these sets can be used to bound the Hausdorff dimension of $E$. We also discuss applications to data science and Erdős/Falco","authors":["Nathan, Hari Sarang"],"url":"https://arxiv.org/abs/2504.11302","arxiv_id":"2504.11302","published":"2026-07-17"},{"title":"Deep Reinforcement Learning Based Navigation with Macro Actions and Topological Maps","abstract":"This paper addresses the challenge of navigation in large, visually complex environments with sparse rewards. We propose a method that uses object-oriented macro actions grounded in a topological map, allowing a simple Deep Q-Network (DQN) to learn effective navigation policies. The agent builds a map by detecting objects from RGBD input and selecting discrete macro actions that correspond to navigating to these obje","authors":["Hakenes, Simon","Glasmachers, Tobias"],"url":"https://arxiv.org/abs/2504.18300","arxiv_id":"2504.18300","published":"2026-07-17"},{"title":"Primal-dual algorithm for contextual stochastic combinatorial optimization","abstract":"This paper introduces a novel approach to contextual stochastic optimization, integrating operations research and machine learning to address decision-making under uncertainty. Traditional methods often fail to leverage contextual information, which underscores the necessity for new algorithms. In this study, we utilize neural networks with combinatorial optimization layers to encode policies. Our goal is to minimize","authors":["Bouvier, Louis","Prunet, Thibault","Leclère, Vincent","Parmentier, Axel"],"url":"https://arxiv.org/abs/2505.04757","arxiv_id":"2505.04757","published":"2026-07-17"},{"title":"Conditioning Residuals for Diffusion Models via Representation Feedback","abstract":"Diffusion models now serve as a common foundation for multimedia generation, and useful intermediate representations emerge during their generative training. Standard architectures, however, propagate these representations through the main feature stream, without explicitly reintroducing their encoded semantics to later denoising layers. Meanwhile, such backbones already provide a conditioning pathway for global modu","authors":["Xiang, Weilai","Yang, Hongyu","Huang, Di","Wang, Yunhong"],"url":"https://arxiv.org/abs/2505.10999","arxiv_id":"2505.10999","published":"2026-07-17"}],"history":{"events":[{"year":2014,"text":"Malaysia Airlines Flight 17 was shot down over eastern Ukraine, killing all 298 people on board.","url":"https://en.wikipedia.org/wiki/Malaysia_Airlines_Flight_17"},{"year":2007,"text":"TAM Airlines Flight 3054 overran the runway at Congonhas Airport in São Paulo, Brazil, killing 199 people.","url":"https://en.wikipedia.org/wiki/TAM_Airlines_Flight_3054"},{"year":1996,"text":"TWA Flight 800 exploded in mid-air and crashed into the Atlantic Ocean near East Moriches, New York.","url":"https://en.wikipedia.org/wiki/TWA_Flight_800"},{"year":1994,"text":"Brazil won the FIFA World Cup final against Italy 3–2 on penalties, following a 0–0 draw after extra time.","url":"https://en.wikipedia.org/wiki/Brazil_national_football_team"},{"year":1992,"text":"The Manchester Metrolink, the first modern street-running light-rail system in the United Kingdom, was officially opened.","url":"https://en.wikipedia.org/wiki/Manchester_Metrolink"},{"year":1968,"text":"Led by Ahmed Hassan al-Bakr (pictured), the Arab Socialist Ba'ath Party overthrew Iraqi president Abdul Rahman Arif in a bloodless coup.","url":"https://en.wikipedia.org/wiki/Ahmed_Hassan_al-Bakr"},{"year":1948,"text":"In Olympia, Greece, the Summer Olympics torch relay, nicknamed the \"relay of peace\", began.","url":"https://en.wikipedia.org/wiki/Olympia%2C_Greece"},{"year":1944,"text":"Laden with munitions for World War II, two ships exploded at the Port Chicago Naval Magazine in California, killing 320 people and injuring more than 400 others.","url":"https://en.wikipedia.org/wiki/Port_Chicago_disaster"},{"year":1936,"text":"Nationalist military officers launch a coup d'état against the Spanish Republic, beginning the Spanish Civil War","url":"https://en.wikipedia.org/wiki/Nationalist_faction_(Spanish_Civil_War)"},{"year":1918,"text":"RMS Carpathia, which had rescued survivors of the 1912 Titanic sinking, was sunk by a German U-boat with the loss of five crew.","url":"https://en.wikipedia.org/wiki/RMS_Carpathia"},{"year":1918,"text":"Russian Revolution: Tsar Nicholas II and his family (pictured) were murdered by Bolsheviks at Yekaterinburg.","url":"https://en.wikipedia.org/wiki/Russian_Revolution"},{"year":1863,"text":"The New Zealand Wars resumed as British forces led by General Duncan Cameron began the invasion of the Waikato.","url":"https://en.wikipedia.org/wiki/New_Zealand_Wars"},{"year":1862,"text":"The garrotting and robbery of James Pilkington, a British member of Parliament, led to a moral panic in London.","url":"https://en.wikipedia.org/wiki/Garrote"},{"year":1850,"text":"William Cranch Bond and John Adams Whipple took a daguerreotype of Vega, the first astrophotograph of a star other than the Sun.","url":"https://en.wikipedia.org/wiki/William_Cranch_Bond"},{"year":1771,"text":"Dene men who were acting as guides to Samuel Hearne on his exploration of the Coppermine River in present-day Nunavut, Canada, massacred a group of about twenty Copper Inuit.","url":"https://en.wikipedia.org/wiki/Dene"},{"year":1453,"text":"The Battle of Castillon, the last engagement of the Hundred Years' War, ended with the English losing all holdings in France except the Pale of Calais.","url":"https://en.wikipedia.org/wiki/Battle_of_Castillon"}],"births":[{"year":2005,"text":"Connor Bedard, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Connor_Bedard"},{"year":2002,"text":"Jordan Lawlar, American baseball player","url":"https://en.wikipedia.org/wiki/Jordan_Lawlar"},{"year":1998,"text":"Rosana Serrano, Cuban rower","url":"https://en.wikipedia.org/wiki/Rosana_Serrano"},{"year":1997,"text":"OG Anunoby, British basketball player","url":"https://en.wikipedia.org/wiki/OG_Anunoby"},{"year":1996,"text":"Wonwoo, South Korean rapper and singer","url":"https://en.wikipedia.org/wiki/Wonwoo"},{"year":1996,"text":"Grace Caroline Currey, American actress","url":"https://en.wikipedia.org/wiki/Grace_Caroline_Currey"},{"year":1994,"text":"Kali Uchis, American singer-songwriter","url":"https://en.wikipedia.org/wiki/Kali_Uchis"},{"year":1992,"text":"Billie Lourd, American actress","url":"https://en.wikipedia.org/wiki/Billie_Lourd"}],"deaths":[{"year":2025,"text":"Felix Baumgartner, Austrian daredevil (born 1969)","url":"https://en.wikipedia.org/wiki/Felix_Baumgartner"},{"year":2025,"text":"Alan Bergman, American songwriter (born 1925)","url":"https://en.wikipedia.org/wiki/Alan_and_Marilyn_Bergman"},{"year":2025,"text":"Joanna Kołaczkowska, Polish cabaret performer (born 1966)","url":"https://en.wikipedia.org/wiki/Joanna_Ko%C5%82aczkowska"},{"year":2024,"text":"Cheng Pei-pei, Chinese actress (born 1946)","url":"https://en.wikipedia.org/wiki/Cheng_Pei-pei"},{"year":2024,"text":"Mary Gibby, British botanist and professor (born 1949)","url":"https://en.wikipedia.org/wiki/Mary_Gibby"},{"year":2024,"text":"Bernice Johnson Reagon, American singer, songwriter and scholar (born 1942)","url":"https://en.wikipedia.org/wiki/Bernice_Johnson_Reagon"},{"year":2024,"text":"Pat Williams, American basketball player (born 1940)","url":"https://en.wikipedia.org/wiki/Pat_Williams_(basketball)"},{"year":2020,"text":"John Lewis, American civil rights activist and politician (born 1940)","url":"https://en.wikipedia.org/wiki/John_Lewis"}]},"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."}