{"date":"2025-12-17","schema_version":1,"captured_at":"2026-08-25T23:05:36.115Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Rob Reiner","views":2209431,"rank":2,"extract":"Robert Reiner was an American filmmaker, actor, and political activist. He directed a series of acclaimed studio films in a career that spanned comedy, drama, romance, and documentary. Reiner received numerous accolades, including winning two Primetime Emmy Aw","url":"https://en.wikipedia.org/wiki/Rob_Reiner","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/8/89/Rob_Reiner_in_2016_%283x4_cropped%29.jpg/330px-Rob_Reiner_in_2016_%283x4_cropped%29.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"Dhurandhar","views":464310,"rank":5,"extract":"Dhurandhar is a 2025 Indian Hindi-language spy action thriller film written and directed by Aditya Dhar. 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Well over 40 qualitative calculi have been proposed so far, mostly in the spatial and temporal domains, with several practical applications such as naval traffic monitoring, warehouse process optimisation and robot manipulation. Even if a number ","authors":["Baryannis, George","Tachmazidis, Ilias","Batsakis, Sotiris","Antoniou, Grigoris","Alviano, Mario","Papadakis, Emmanuel"],"url":"https://arxiv.org/abs/2008.01519","arxiv_id":"2008.01519","published":"2025-12-17"},{"title":"Holistic Generalized Linear Models","abstract":"Holistic linear regression extends the classical best subset selection problem by adding additional constraints designed to improve the model quality. These constraints include sparsity-inducing constraints, sign-coherence constraints and linear constraints. The $\\textsf{R}$ package $\\texttt{holiglm}$ provides functionality to model and fit holistic generalized linear models. By making use of state-of-the-art conic m","authors":["Schwendinger, Benjamin","Schwendinger, Florian","Vana, Laura"],"url":"https://arxiv.org/abs/2205.15447","arxiv_id":"2205.15447","published":"2025-12-17"},{"title":"On Non-Linear operators for Geometric Deep Learning","abstract":"This work studies operators mapping vector and scalar fields defined over a manifold $\\mathcal{M}$, and which commute with its group of diffeomorphisms $\\text{Diff}(\\mathcal{M})$. We prove that in the case of scalar fields $L^p_ω(\\mathcal{M,\\mathbb{R}})$, those operators correspond to point-wise non-linearities, recovering and extending known results on $\\mathbb{R}^d$. In the context of Neural Networks defined over $","authors":["Sergeant-Perthuis, Grégoire","Maier, Jakob","Bruna, Joan","Oyallon, Edouard"],"url":"https://arxiv.org/abs/2207.03485","arxiv_id":"2207.03485","published":"2025-12-17"},{"title":"Meta-Reinforcement Learning for Building Energy Management System","abstract":"The building sector is one of the largest contributors to global energy consumption. Improving its energy efficiency is essential for reducing operational costs and greenhouse gas emissions. Energy management systems (EMS) play a key role in monitoring and controlling building appliances efficiently and reliably. With the increasing integration of renewable energy, intelligent EMS solutions have received growing atte","authors":["Zhang, Huiliang","Wu, Di","Zinflou, Arnaud","Boulet, Benoit"],"url":"https://arxiv.org/abs/2210.12590","arxiv_id":"2210.12590","published":"2025-12-17"},{"title":"Reformulation Techniques for Automated Planning: A Systematic Review","abstract":"Automated planning is a prominent area of Artificial Intelligence, and an important component for intelligent autonomous agents. A cornerstone of domain-independent planning is the separation between planning logic, i.e. the automated reasoning side, and the knowledge model, that encodes a formal representation of domain knowledge needed to reason upon a given problem to synthesise a solution plan. Such a separation ","authors":["Alarnaouti, Diaeddin","Baryannis, George","Vallati, Mauro"],"url":"https://arxiv.org/abs/2301.10079","arxiv_id":"2301.10079","published":"2025-12-17"},{"title":"Trustworthy, responsible, ethical AI in manufacturing and supply chains: synthesis and emerging research questions","abstract":"While the increased use of AI in the manufacturing sector has been widely noted, there is little understanding on the risks that it may raise in a manufacturing organisation. Although various high level frameworks and definitions have been proposed to consolidate potential risks, practitioners struggle with understanding and implementing them. This lack of understanding exposes manufacturing to a multitude of risks, ","authors":["Brintrup, Alexandra","Baryannis, George","Tiwari, Ashutosh","Ratchev, Svetan","Martinez-Arellano, Giovanna","Singh, Jatinder"],"url":"https://arxiv.org/abs/2305.11581","arxiv_id":"2305.11581","published":"2025-12-17"},{"title":"Decoding Emotional Trajectories: A Temporal-Semantic Network Approach for Latent Depression Assessment in Social Media","abstract":"The early identification and intervention of latent depression are of significant societal importance for mental health governance. While current automated detection methods based on social media have shown progress, their decision-making processes often lack a clinically interpretable framework, particularly in capturing the duration and dynamic evolution of depressive symptoms. To address this, this study introduce","authors":["Kuang, Junwei","Xie, Jiaheng","Yan, Zhijun"],"url":"https://arxiv.org/abs/2305.13127","arxiv_id":"2305.13127","published":"2025-12-17"},{"title":"Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting","abstract":"Ensembling is among the most popular tools in machine learning (ML) due to its effectiveness in minimizing variance and thus improving generalization. Most ensembling methods for black-box base learners fall under the umbrella of "stacked generalization," namely training an ML algorithm that takes the inferences from the base learners as input. While stacking has been widely applied in practice, its theoretic","authors":["Hasson, Hilaf","Maddix, Danielle C.","Wang, Yuyang","Gupta, Gaurav","Park, Youngsuk"],"url":"https://arxiv.org/abs/2305.15786","arxiv_id":"2305.15786","published":"2025-12-17"},{"title":"General Formulation and PCL-Analysis for Restless Bandits with Limited Observability","abstract":"In this paper, we consider a general observation model for restless multi-armed bandit problems. The operation of the player is based on the past observation history that is limited (partial) and error-prone due to resource constraints or environmental or intrinsic noises. By establishing a general probabilistic model for dynamics of the observation process, we formulate the problem as a restless bandit with an infin","authors":["Liu, Keqin","Jia, Qizhen"],"url":"https://arxiv.org/abs/2307.03034","arxiv_id":"2307.03034","published":"2025-12-17"},{"title":"Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability","abstract":"Adversarial examples (AEs) for DNNs have been shown to be transferable: AEs that successfully fool white-box surrogate models can also deceive other black-box models with different architectures. Although a bunch of empirical studies have provided guidance on generating highly transferable AEs, many of these findings lack explanations and even lead to inconsistent advice. In this paper, we take a further step towards","authors":["Zhang, Yechao","Hu, Shengshan","Zhang, Leo Yu","Shi, Junyu","Li, Minghui","Liu, Xiaogeng"],"url":"https://arxiv.org/abs/2307.07873","arxiv_id":"2307.07873","published":"2025-12-17"},{"title":"Global Deep Forecasting with Patient-Specific Pharmacokinetics","abstract":"Forecasting healthcare time series data is vital for early detection of adverse outcomes and patient monitoring. However, it can be challenging in practice due to variable medication administration and unique pharmacokinetic (PK) properties of each patient. To address these challenges, we propose a novel hybrid global-local architecture and a PK encoder that informs deep learning models of patient-specific treatment ","authors":["Potosnak, Willa","Challu, Cristian","Olivares, Kin G.","Dufendach, Keith A.","Dubrawski, Artur"],"url":"https://arxiv.org/abs/2309.13135","arxiv_id":"2309.13135","published":"2025-12-17"},{"title":"MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness","abstract":"Vision Transformers (ViTs) have emerged as a fundamental architecture and serve as the backbone of modern vision-language models. Despite their impressive performance, ViTs exhibit notable vulnerability to evasion attacks, necessitating the development of specialized Adversarial Training (AT) strategies tailored to their unique architecture. While a direct solution might involve applying existing AT methods to ViTs, ","authors":["Xu, Xiaoyun","Yu, Shujian","Liu, Zhuoran","Picek, Stjepan"],"url":"https://arxiv.org/abs/2312.04960","arxiv_id":"2312.04960","published":"2025-12-17"},{"title":"Question Answering Over Spatio-Temporal Knowledge Graph","abstract":"Spatio-temporal knowledge graphs (STKGs) enhance traditional KGs by integrating temporal and spatial annotations, enabling precise reasoning over questions with spatio-temporal dependencies. Despite their potential, research on spatio-temporal knowledge graph question answering (STKGQA) remains limited. This is primarily due to the lack of datasets that simultaneously contain spatio-temporal information, as well as m","authors":["Dai, Xinbang","Li, Huiying","Hu, Nan","Chen, Yongrui","Jin, Rihui","Hu, Huikang"],"url":"https://arxiv.org/abs/2402.11542","arxiv_id":"2402.11542","published":"2025-12-17"},{"title":"Differentially Private Knowledge Distillation via Synthetic Text Generation","abstract":"Large Language models (LLMs) are achieving state-of-the-art performance in many different downstream tasks. However, the increasing urgency of data privacy puts pressure on practitioners to train LLMs with Differential Privacy (DP) on private data. Concurrently, the exponential growth in parameter size of LLMs necessitates model compression before deployment of LLMs on resource-constrained devices or latency-sensitiv","authors":["Flemings, James","Annavaram, Murali"],"url":"https://arxiv.org/abs/2403.00932","arxiv_id":"2403.00932","published":"2025-12-17"},{"title":"I-Diff: Structural Regularization for High-Fidelity Diffusion Models","abstract":"Denoising Diffusion Probabilistic Models (DDPMs) have significantly advanced generative AI, achieving impressive results in high-quality image and data generation. However, enhancing fidelity without compromising semantic content remains a key challenge in the field. Recent diffusion research in multiple disciplines has introduced objectives and architectural refinements that tighten the match between generated and r","authors":["Perera, Shakthi","Fernando, Dilum","Malshan, H. L. P.","Madushan, H. M. P. S.","Godaliyadda, Roshan","Ekanayake, M. P. B."],"url":"https://arxiv.org/abs/2403.16790","arxiv_id":"2403.16790","published":"2025-12-17"},{"title":"Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem","abstract":"Diversity optimization is the class of optimization problems in which we aim to find a diverse set of good solutions. One of the frequently-used approaches to solve such problems is to use evolutionary algorithms that evolve a desired diverse population. This approach is called evolutionary diversity optimization (EDO). In this paper, we analyze EDO on a three-objective function LOTZ$_k$, which is a modification of t","authors":["Antipov, Denis","Neumann, Aneta","Neumann, Frank","Sutton, Andrew M."],"url":"https://arxiv.org/abs/2404.11496","arxiv_id":"2404.11496","published":"2025-12-17"},{"title":"Automated Model Selection for Generalized Linear Models","abstract":"In this paper, we show how mixed-integer conic optimization can be used to combine feature subset selection with holistic generalized linear models to fully automate the model selection process. Concretely, we directly optimize for the Akaike and Bayesian information criteria while imposing constraints designed to deal with multicollinearity in the feature selection task. Specifically, we propose a novel pairwise cor","authors":["Schwendinger, Benjamin","Schwendinger, Florian","Vana-Gür, Laura"],"url":"https://arxiv.org/abs/2404.16560","arxiv_id":"2404.16560","published":"2025-12-17"},{"title":"Coupling Light with Matter for Identifying Dominant Subnetworks","abstract":"We introduce DOMINO, a light-matter computing platform that exploits the full complex amplitude of coupled condensate networks to solve maximum-weight clique problems and reveal hidden indirect correlations in large graphs. By embedding network structure directly into a gain-controlled polaritonic (or photonic) oscillator array, DOMINO performs analog optimization, directly solving the maximum-weight clique problem v","authors":["Kamaletdinov, Airat","Berloff, Natalia G."],"url":"https://arxiv.org/abs/2405.17296","arxiv_id":"2405.17296","published":"2025-12-17"},{"title":"REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning","abstract":"Recent rehearsal-free continual learning (CL) methods guided by prompts achieve strong performance on vision tasks with non-stationary data but remain resource-intensive, hindering real-world edge deployment. We introduce resource-efficient prompting (REP), which improves the computational and memory efficiency of prompt-based rehearsal-free continual learning methods while minimizing accuracy trade-offs. Our approac","authors":["Jeon, Sungho","Ma, Xinyue","Kim, Kwang In","Jeon, Myeongjae"],"url":"https://arxiv.org/abs/2406.04772","arxiv_id":"2406.04772","published":"2025-12-17"},{"title":"CrossPT-EEG: A Benchmark for Cross-Participant and Cross-Time Generalization of EEG-based Visual Decoding","abstract":"Exploring brain activity in relation to visual perception provides insights into the biological representation of the world. While functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) have enabled effective image classification and reconstruction, their high cost and bulk limit practical use. Electroencephalography (EEG), by contrast, offers low cost and excellent temporal resolution, but its","authors":["Zhu, Shuqi","Ye, Ziyi","Ai, Qingyao","Liu, Yiqun"],"url":"https://arxiv.org/abs/2406.07151","arxiv_id":"2406.07151","published":"2025-12-17"},{"title":"LSM: A Comprehensive Metric for Assessing the Safety of Lane Detection Systems in Autonomous Driving","abstract":"Comprehensive perception of the vehicle's environment and correct interpretation of the environment are crucial for the safe operation of autonomous vehicles. The perception of surrounding objects is the main component for further tasks such as trajectory planning. However, safe trajectory planning requires not only object detection, but also the detection of drivable areas and lane corridors. While first approac","authors":["Gamerdinger, Jörg","Teufel, Sven","Amann, Stephan","Volk, Georg","Bringmann, Oliver"],"url":"https://arxiv.org/abs/2407.07740","arxiv_id":"2407.07740","published":"2025-12-17"},{"title":"FedGlu: A personalized federated learning-based glucose forecasting algorithm for improved performance in glycemic excursion regions","abstract":"Continuous glucose monitoring (CGM) devices provide real-time glucose monitoring and timely alerts for glycemic excursions, improving glycemic control among patients with diabetes. However, identifying rare events like hypoglycemia and hyperglycemia remain challenging due to their infrequency. Moreover, limited access to sensitive patient data hampers the development of robust machine learning models. Our objective i","authors":["Dave, Darpit","Vyas, Kathan","Jayagopal, Jagadish Kumaran","Garcia, Alfredo","Erraguntla, Madhav","Lawley, Mark"],"url":"https://arxiv.org/abs/2408.13926","arxiv_id":"2408.13926","published":"2025-12-17"},{"title":"Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models","abstract":"Language models (LMs) rely on their parametric knowledge augmented with relevant contextual knowledge for certain tasks, such as question answering. However, the contextual knowledge can contain private information that may be leaked when answering queries, and estimating this privacy leakage is not well understood. A straightforward approach of directly comparing an LM's output to the contexts can overestimate t","authors":["Flemings, James","Jiang, Bo","Zhang, Wanrong","Takhirov, Zafar","Annavaram, Murali"],"url":"https://arxiv.org/abs/2410.03026","arxiv_id":"2410.03026","published":"2025-12-17"},{"title":"COMMA: A Communicative Multimodal Multi-Agent Benchmark","abstract":"The rapid advances of multimodal agents built on large foundation models have largely overlooked their potential for language-based communication between agents in collaborative tasks. This oversight presents a critical gap in understanding their effectiveness in real-world deployments, particularly when communicating with humans. Existing agentic benchmarks fail to address key aspects of inter-agent communication an","authors":["Ossowski, Timothy","Maqbool, Danyal","Chen, Jixuan","Cai, Zefan","Bradshaw, Tyler","Hu, Junjie"],"url":"https://arxiv.org/abs/2410.07553","arxiv_id":"2410.07553","published":"2025-12-17"},{"title":"QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design","abstract":"Quantum computing is an emerging field recognized for the significant speedup it offers over classical computing through quantum algorithms. However, designing and implementing quantum algorithms pose challenges due to the complex nature of quantum mechanics and the necessity for precise control over quantum states. Despite the significant advancements in AI, there has been a lack of datasets specifically tailored fo","authors":["Yang, Rui","Wang, Ziruo","Gu, Yuntian","Chen, Tianyi","Liang, Yitao","Li, Tongyang"],"url":"https://arxiv.org/abs/2410.07961","arxiv_id":"2410.07961","published":"2025-12-17"}],"history":{"events":[{"year":2016,"text":"The first victims of a mass methanol poisoning which eventually killed over 70 inhabitants of Irkutsk, Russia, began arriving at hospitals.","url":"https://en.wikipedia.org/wiki/2016_Irkutsk_mass_methanol_poisoning"},{"year":2010,"text":"Arab Spring: Mohamed Bouazizi, a street vendor in Sidi Bouzid, set himself on fire in protest against police harassment, triggering the Tunisian revolution.","url":"https://en.wikipedia.org/wiki/Arab_Spring"},{"year":1990,"text":"American gay rights activist William E. Woods brought three same-sex couples to fill out marriage licenses in Honolulu.","url":"https://en.wikipedia.org/wiki/LGBTQ_movements"},{"year":1983,"text":"The Troubles: The Provisional Irish Republican Army detonated a car bomb outside Harrods in London, killing six people and injuring about 90 others.","url":"https://en.wikipedia.org/wiki/The_Troubles"},{"year":1970,"text":"Polish soldiers fired at workers (memorial pictured) emerging from trains in Gdynia, beginning the government's crackdown on mass anti-communist protests across the country.","url":"https://en.wikipedia.org/wiki/December_1970_protests_in_Poland"},{"year":1967,"text":"Harold Holt, the prime minister of Australia, disappeared while swimming near Portsea, Victoria; his body was never recovered.","url":"https://en.wikipedia.org/wiki/Harold_Holt"},{"year":1951,"text":"The Civil Rights Congress presented a document to the United Nations Genocide Convention charging the United States government with genocide against African Americans.","url":"https://en.wikipedia.org/wiki/Civil_Rights_Congress"},{"year":1948,"text":"The Finnish Security Police was established to remove communist leadership from its predecessor, the State Police.","url":"https://en.wikipedia.org/wiki/Finnish_Security_and_Intelligence_Service"},{"year":1945,"text":"The modern flag of Kurdistan was raised for the first time in Mahabad, Iran.","url":"https://en.wikipedia.org/wiki/Flag_of_Kurdistan"},{"year":1944,"text":"Nazi troops under Joachim Peiper killed unarmed prisoners of war, captured during the Battle of the Bulge, with machine guns near Malmedy, Belgium.","url":"https://en.wikipedia.org/wiki/Joachim_Peiper"},{"year":1939,"text":"World War II: After sustaining moderate damage in the Battle of the River Plate two days earlier, the German cruiser Graf Spee was scuttled by its commander, Hans Langsdorff, to avoid its internment by Uruguay.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1926,"text":"A coup d'état by the Lithuanian military replaced the democratically elected President Kazys Grinius with Antanas Smetona.","url":"https://en.wikipedia.org/wiki/1926_Lithuanian_coup_d'%C3%A9tat"},{"year":1918,"text":"About 1,000 demonstrators marched (pictured) on Government House in Darwin, Australia, where they burned an effigy of Administrator John Gilruth and demanded his resignation.","url":"https://en.wikipedia.org/wiki/Darwin_rebellion"},{"year":1862,"text":"American Civil War: Union General Ulysses S. Grant issued General Order No. 11, expelling Jews from Tennessee, Mississippi, and Kentucky.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1790,"text":"The Aztec sun stone (pictured), now a modern symbol of Mexican culture, was excavated in the Zócalo, the main square of Mexico City.","url":"https://en.wikipedia.org/wiki/Aztec_sun_stone"},{"year":1583,"text":"Cologne War: Forces under Ernest of Bavaria defeated Gebhard Truchsess von Waldburg's troops at the siege of Godesberg.","url":"https://en.wikipedia.org/wiki/Cologne_War"},{"year":942,"text":"William Longsword of Normandy was ambushed and assassinated by supporters of Arnulf I, Count of Flanders, while both were at a peace conference to settle their differences.","url":"https://en.wikipedia.org/wiki/William_Longsword"},{"year":546,"text":"Rome was sacked by the Ostrogoths led by Totila after a year-long siege.","url":"https://en.wikipedia.org/wiki/Sack_of_Rome_(546)"}],"births":[{"year":2002,"text":"Castello Lukeba, French footballer","url":"https://en.wikipedia.org/wiki/Castello_Lukeba"},{"year":2000,"text":"Wesley Fofana, French footballer","url":"https://en.wikipedia.org/wiki/Wesley_Fofana_(footballer)"},{"year":1999,"text":"Holly Humberstone, English singer-songwriter","url":"https://en.wikipedia.org/wiki/Holly_Humberstone"},{"year":1999,"text":"Mirei Sasaki, Japanese singer, model, and actress","url":"https://en.wikipedia.org/wiki/Mirei_Sasaki"},{"year":1998,"text":"Jasmine Armfield, English actress","url":"https://en.wikipedia.org/wiki/Jasmine_Armfield"},{"year":1998,"text":"Martin Ødegaard, Norwegian footballer","url":"https://en.wikipedia.org/wiki/Martin_%C3%98degaard"},{"year":1997,"text":"Naiktha Bains, British-Australian tennis player","url":"https://en.wikipedia.org/wiki/Naiktha_Bains"},{"year":1997,"text":"Shoma Uno, Japanese figure skater","url":"https://en.wikipedia.org/wiki/Shoma_Uno"}],"deaths":[{"year":2025,"text":"William Rush, English actor (born 1994)","url":"https://en.wikipedia.org/wiki/William_Rush_(actor)"},{"year":2024,"text":"Igor Kirillov, Russian general (born 1970)","url":"https://en.wikipedia.org/wiki/Igor_Kirillov_(general)"},{"year":2024,"text":"Marisa Paredes, Spanish film actress (born 1946)","url":"https://en.wikipedia.org/wiki/Marisa_Paredes"},{"year":2023,"text":"Ronaldo Valdez, Filipino actor (born 1947)","url":"https://en.wikipedia.org/wiki/Ronaldo_Valdez"},{"year":2023,"text":"James McCaffrey, American actor (born 1958)","url":"https://en.wikipedia.org/wiki/James_McCaffrey_(actor)"},{"year":2020,"text":"Jeremy Bulloch, English actor (born 1945)","url":"https://en.wikipedia.org/wiki/Jeremy_Bulloch"},{"year":2020,"text":"Allen Dines, American politician (born 1921)","url":"https://en.wikipedia.org/wiki/Allen_Dines"},{"year":2016,"text":"Benjamin A. Gilman, American soldier and politician (born 1922)","url":"https://en.wikipedia.org/wiki/Benjamin_Gilman"}]},"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."}