{"date":"2026-07-23","schema_version":1,"captured_at":"2026-08-25T23:17:09.813Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"The Odyssey (2026 film)","views":664906,"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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In this paper we present a two-component system to automate the task of resonance equalization. The first component is a dynamic equalizer that automatically detects resonances and offers to attenuate them by a user-specified factor. The second component is a deep neural network that predicts t","authors":["Grachten, Maarten","Deruty, Emmanuel","Tanguy, Alexandre"],"url":"https://arxiv.org/abs/1807.08636","arxiv_id":"1807.08636","published":"2026-07-23"},{"title":"Deep Learning in Mining Biological Data","abstract":"Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Broadly categorized in three types (i.e., sequences, images, and signals), these data are huge in amount and complex in nature. Mining such an enormous amount of data for pattern recognition is a big challenge and requires sophisticated data-intensive machine le","authors":["Mahmud, Mufti","Kaiser, M Shamim","Hussain, Amir"],"url":"https://arxiv.org/abs/2003.00108","arxiv_id":"2003.00108","published":"2026-07-23"},{"title":"Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation","abstract":"This article investigates the origin of numerical issues in maximum likelihood parameter estimation for Gaussian process (GP) interpolation and investigates simple but effective strategies for improving commonly used open-source software implementations. This work targets a basic problem but a host of studies, particularly in the literature of Bayesian optimization, rely on off-the-shelf GP implementations. For the c","authors":["Basak, Subhasish","Petit, Sébastien","Bect, Julien","Vazquez, Emmanuel"],"url":"https://arxiv.org/abs/2101.09747","arxiv_id":"2101.09747","published":"2026-07-23"},{"title":"Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals","abstract":"Many canonical models in causal inference and structural econometrics have recursive identification formulas. In causal inference, recursion arises when identification requires both pre- and post-treatment covariates. For example, short-term surrogate outcomes are measured after the treatment, and serve as necessary covariates when identifying long-term effects. Post-treatment covariates are also required for identif","authors":["Chernozhukov, Victor","Newey, Whitney","Singh, Rahul","Syrgkanis, Vasilis"],"url":"https://arxiv.org/abs/2203.13887","arxiv_id":"2203.13887","published":"2026-07-23"},{"title":"Is Smaller Always Faster? Tradeoffs in Compressing Self-Supervised Speech Transformers","abstract":"Transformer-based self-supervised models have achieved remarkable success in speech processing, but their large size and high inference cost present significant challenges for real-world deployment. While numerous compression techniques have been proposed, inconsistent evaluation metrics make it difficult to compare their practical effectiveness. In this work, we conduct a comprehensive study of four common compressi","authors":["Lin, Tzu-Quan","Yang, Tsung-Huan","Chang, Chun-Yao","Chen, Kuang-Ming","Feng, Tzu-hsun","Lee, Hung-yi"],"url":"https://arxiv.org/abs/2211.09949","arxiv_id":"2211.09949","published":"2026-07-23"},{"title":"Kernel Ridge Regression Inference","abstract":"We provide uniform confidence bands for kernel ridge regression (KRR), a widely used nonparametric regression estimator for nonstandard data such as preferences, sequences, and graphs. Despite the prevalence of these data--e.g., student preferences in school matching mechanisms--the inferential theory of KRR is not fully known. We construct valid and sharp confidence sets that shrink at nearly the minimax rate, allow","authors":["Singh, Rahul","Vijaykumar, Suhas"],"url":"https://arxiv.org/abs/2302.06578","arxiv_id":"2302.06578","published":"2026-07-23"},{"title":"Rational kernel-based interpolation for complex-valued frequency response functions","abstract":"This work is concerned with the kernel-based approximation of a complex-valued function from data, where the frequency response function of a partial differential equation in the frequency domain is of particular interest. In this setting, kernel methods are employed more and more frequently, however, standard kernels do not perform well. Moreover, the role and mathematical implications of the underlying pair of kern","authors":["Bect, Julien","Georg, Niklas","Römer, Ulrich","Schöps, Sebastian"],"url":"https://arxiv.org/abs/2307.13484","arxiv_id":"2307.13484","published":"2026-07-23"},{"title":"A convergence result of a continuous model of deep learning via a Łojasiewicz--Simon inequality","abstract":"We study an idealized training process for deep neural networks in a continuous-depth, mean-field model in which each layer is parameterized by a probability measure on a Euclidean parameter space. The training dynamics are formulated as a Wasserstein-type gradient flow of an objective with a fixed $L^2$-regularization. Under suitable analyticity and growth assumptions, together with a coercivity assumption and suffi","authors":["Isobe, Noboru"],"url":"https://arxiv.org/abs/2311.15365","arxiv_id":"2311.15365","published":"2026-07-23"},{"title":"Advancing bioinformatics with large language models: components, applications and perspectives","abstract":"Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of artificial neural networks with numerous parameters, trained on large amounts of unlabeled input using self-supervised or semi-supervised learning. However, their potential for solvi","authors":["Liu, Jiajia","Yang, Mengyuan","Yu, Yankai","Xu, Haixia","Wang, Tiangang","Li, Kang"],"url":"https://arxiv.org/abs/2401.04155","arxiv_id":"2401.04155","published":"2026-07-23"},{"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":"2026-07-23"},{"title":"Local search for valued constraint satisfaction parameterized by treedepth","abstract":"Sometimes local search algorithms cannot efficiently find even local peaks. To understand why, I look at the structure of ascents in fitness landscapes from valued constraint satisfaction problems (VCSPs) parameterized by the treedepth of their constraint graphs. There are existing constructions of VCSPs with logarithm treedepth that represent fitness landscapes where all ascents are exponential from some initial ass","authors":["Kaznatcheev, Artem"],"url":"https://arxiv.org/abs/2405.12410","arxiv_id":"2405.12410","published":"2026-07-23"},{"title":"Any-Time Regret-Guaranteed Algorithm for Control of Linear Quadratic Systems","abstract":"We propose a computationally efficient algorithm that achieves anytime regret of order $\\mathcal{O}(\\sqrt{t})$, with explicit dependence on the system dimensions and on the solution of the Discrete Algebraic Riccati Equation (DARE). Our approach builds on the SDP-based framework of \\cite{cohen2019learning}, using an appropriately tuned regularization and a sufficiently accurate initial estimate to construct confidenc","authors":["Chekan, Jafar Abbaszadeh","Langbort, Cedric"],"url":"https://arxiv.org/abs/2406.07746","arxiv_id":"2406.07746","published":"2026-07-23"},{"title":"LaSEr-Edit: Localized Span-level Error Editing with Energy-based Localization","abstract":"As large language models (LLMs) are widely adopted in real-world applications, it has become critical to ensure LLMs satisfy safety constraints, such as non-toxicity and logical consistency, as well as task- and situation-specific constraints. Controlling the output through instructions is a simple and tempting approach; however, it remains brittle, is opaque in how it influences model behavior, and thus cannot relia","authors":["Son, Hye Ryung","Eom, Saehee","Song, Mooho","Lee, Jay-Yoon"],"url":"https://arxiv.org/abs/2407.00740","arxiv_id":"2407.00740","published":"2026-07-23"},{"title":"Footprints of Data in a Classifier: Understanding the Privacy Risks and Solution Strategies","abstract":"The widespread deployment of Artificial Intelligence (AI) across government and private industries brings both advancements and heightened privacy and security concerns. Article 17 of the General Data Protection Regulation (GDPR) mandates the Right to Erasure, requiring data to be permanently removed from a system to prevent potential compromise. While existing research primarily focuses on erasing sensitive data att","authors":["Sadhukhan, Payel","Chakraborty, Tanujit"],"url":"https://arxiv.org/abs/2407.02268","arxiv_id":"2407.02268","published":"2026-07-23"},{"title":"Differentially Private Neural Network Training Under the Hidden State Assumption","abstract":"Current differentially private learning paradigms face a severe utility bottleneck: DP-SGD degrades performance through noise accumulation over training steps, while aggregation-based approaches such as PATE suffer from data inefficiency due to disjoint data partitioning. We propose \\textbf{Differentially Private Decoupled Training (DP-DT)}, a framework that decouples representation learning from privacy enforcement.","authors":["Chen, Ding","Luo, Haochen","Wang, Xiaofei","Liu, Chen"],"url":"https://arxiv.org/abs/2407.08233","arxiv_id":"2407.08233","published":"2026-07-23"},{"title":"A Confidence Interval for the $\\ell_2$ Expected Calibration Error","abstract":"Recent advances in machine learning have significantly improved prediction accuracy in various applications. However, ensuring the calibration of probabilistic predictions remains a significant challenge. Despite efforts to enhance model calibration, the rigorous statistical evaluation of model calibration remains less explored. In this work, we develop confidence intervals the $\\ell_2$ Expected Calibration Error (EC","authors":["Sun, Yan","Chaudhari, Pratik","Barnett, Ian J.","Dobriban, Edgar"],"url":"https://arxiv.org/abs/2408.08998","arxiv_id":"2408.08998","published":"2026-07-23"},{"title":"Distributed Optimization via Energy Conservation Laws in Dilated Coordinates","abstract":"Continuous-time models can reveal accelerated structures in distributed optimization, but their rates need not survive direct discretization. We introduce a second-order primal--dual flow for smooth convex distributed optimization and construct an exactly conserved energy that yields an $\\mathcal O(t^{-2})$ rate for both the aggregate objective gap and the squared consensus error. We then prove a horizon-wise $Ω(k^{-","authors":["Chakrabarti, Kushal","Baranwal, Mayank"],"url":"https://arxiv.org/abs/2409.19279","arxiv_id":"2409.19279","published":"2026-07-23"},{"title":"The Hive Mind is a Single Reinforcement Learning Agent","abstract":"Decision-making is an essential attribute of any intelligent agent or group. Natural systems are known to converge to effective strategies through at least two distinct mechanisms: collective decision-making via imitation of others, and trial-and-error by a single agent. This paper establishes an equivalence between these two paradigms. We show that the emergent distributed cognition (sometimes referred to as the \\te","authors":["Soma, Karthik","Bouteiller, Yann","Hamann, Heiko","Beltrame, Giovanni"],"url":"https://arxiv.org/abs/2410.17517","arxiv_id":"2410.17517","published":"2026-07-23"},{"title":"Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models","abstract":"Continuous monitoring and real-time control of high-dimensional distributed systems are often crucial in applications to ensure a desired physical behavior, without degrading stability and system performances. Traditional feedback control design that relies on full-order models, such as high-dimensional state-space representations or partial differential equations, fails to meet these requirements due to the delay in","authors":["Tomasetto, Matteo","Braghin, Francesco","Manzoni, Andrea"],"url":"https://arxiv.org/abs/2412.09942","arxiv_id":"2412.09942","published":"2026-07-23"},{"title":"Tokens, the oft-overlooked appetizer: Large language models, the distributional hypothesis, and meaning","abstract":"Tokenization is a necessary component within the current architecture of many language mod-els, including the transformer-based large language models (LLMs) of Generative AI, yet its impact on the model's cognition is often overlooked. We argue that LLMs demonstrate that the Distributional Hypothesis (DH) is sufficient for reasonably human-like language performance (particularly with respect to inferential lexica","authors":["Zimmerman, Julia Witte","Hudon, Denis","Cramer, Kathryn","Ruiz, Alejandro J.","Beauregard, Calla","Fehr, Ashley"],"url":"https://arxiv.org/abs/2412.10924","arxiv_id":"2412.10924","published":"2026-07-23"},{"title":"Reduced Order Modeling with Shallow Recurrent Decoder Networks","abstract":"Reduced Order Modeling is of paramount importance for efficiently inferring high-dimensional spatio-temporal fields in parametric contexts, enabling computationally tractable parametric analyses, uncertainty quantification and control. However, conventional dimensionality reduction techniques are typically limited to known and constant parameters, inefficient for nonlinear and chaotic dynamics, and uninformed to the ","authors":["Tomasetto, Matteo","Williams, Jan P.","Braghin, Francesco","Manzoni, Andrea","Kutz, J. Nathan"],"url":"https://arxiv.org/abs/2502.10930","arxiv_id":"2502.10930","published":"2026-07-23"},{"title":"Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation: A Comparative Study","abstract":"OpenNotes gives patients access to their EHR notes, but dense medical jargon limits comprehension. We evaluate closed-source and open-source LLMs for extracting and prioritizing the jargon terms most relevant to individual patients, using 90 expert-annotated EHR notes. We test combinations of general vs. structured prompts, zero-shot vs. few-shot prompting, fine-tuning, and GPT-4o-based data augmentation, the last pa","authors":["Jang, Won Seok","Sultana, Sharmin","Yao, Zonghai","Tran, Hieu","Yang, Zhichao","Kwon, Sunjae"],"url":"https://arxiv.org/abs/2502.16022","arxiv_id":"2502.16022","published":"2026-07-23"},{"title":"SemICP: Semantic Non-Rigid Point Cloud Registration with Elastic Energy Regularization","abstract":"Purpose: Accurate point cloud registration is essential in computer-aided interventions (CAI) to align multi-modal medical images for intraoperative guidance. Classical methods, such as Iterative Closest Point (ICP), remain attractive for their explainability and minimal training requirements, but typically ignore anatomical semantics and biomechanical properties during regularization. Methods: We present Semantic IC","authors":["Chen, Wanwen","Zeng, Qi","Studders, Carson","Li, Zongze","Kwon, Jamie J. Y.","Kemper, Tara"],"url":"https://arxiv.org/abs/2503.00972","arxiv_id":"2503.00972","published":"2026-07-23"},{"title":"SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding","abstract":"We present SEED (Semantic Evaluation for Visual Brain Decoding), a novel metric for evaluating the semantic decoding performance of visual brain decoding models. It integrates three complementary metrics, each capturing a different aspect of semantic similarity between images inspired by neuroscientific findings. Using carefully crowd-sourced human evaluation data, we demonstrate that SEED achieves the highest alignm","authors":["Park, Juhyeon","Kim, Peter Yongho","Cha, Jiook","Yoo, Shinjae","Moon, Taesup"],"url":"https://arxiv.org/abs/2503.06437","arxiv_id":"2503.06437","published":"2026-07-23"},{"title":"Theory-to-Practice Gap for Neural Networks and Neural Operators","abstract":"This work studies the sampling complexity of learning with ReLU neural networks and neural operators. For mappings belonging to relevant approximation spaces, we derive upper bounds on the best-possible convergence rate of any learning algorithm, with respect to the number of samples. In the finite-dimensional case, these bounds imply a gap between the parametric and sampling complexities of learning, known as the \\e","authors":["Grohs, Philipp","Lanthaler, Samuel","Trautner, Margaret"],"url":"https://arxiv.org/abs/2503.18219","arxiv_id":"2503.18219","published":"2026-07-23"}],"history":{"events":[{"year":2010,"text":"The English-Irish boy band One Direction (pictured) were formed while auditioning for the 2010 series of the British singing competition The X Factor.","url":"https://en.wikipedia.org/wiki/One_Direction"},{"year":2001,"text":"Megawati Sukarnoputri was sworn in (pictured) as the first female president of Indonesia following her predecessor's impeachment.","url":"https://en.wikipedia.org/wiki/Megawati_Sukarnoputri"},{"year":1999,"text":"Forty-seven people were arrested in Tulia, Texas, for dealing cocaine; 35 of them were pardoned by the governor of Texas years later.","url":"https://en.wikipedia.org/wiki/1999_Tulia_drug_arrests"},{"year":1995,"text":"Hale–Bopp, one of the most widely observed comets of the 20th century, was independently discovered by astronomers Alan Hale and Thomas Bopp.","url":"https://en.wikipedia.org/wiki/Comet_Hale%E2%80%93Bopp"},{"year":1984,"text":"Vanessa Williams, the first African-American Miss America, was forced to resign after the magazine Penthouse published nude photos of her without consent.","url":"https://en.wikipedia.org/wiki/Vanessa_Williams"},{"year":1982,"text":"A helicopter crashed during the filming of Twilight Zone: The Movie in Valencia, California, killing actor Vic Morrow and two child actors.","url":"https://en.wikipedia.org/wiki/Twilight_Zone_accident"},{"year":1968,"text":"A shootout between police and a Black power group began in Cleveland, Ohio, sparking three days of rioting.","url":"https://en.wikipedia.org/wiki/Glenville_shootout"},{"year":1942,"text":"The Holocaust: The gas chambers at Treblinka extermination camp began operation, killing 6,500 Jews who had been transported from the Warsaw Ghetto the day before.","url":"https://en.wikipedia.org/wiki/The_Holocaust"},{"year":1942,"text":"Bulgarian poet and communist activist Nikola Vaptsarov was executed by firing squad.","url":"https://en.wikipedia.org/wiki/Nikola_Vaptsarov"},{"year":1940,"text":"Sumner Welles, U.S. Under Secretary of State, issued a declaration that the U.S. government would not recognize the Soviet Union's annexation of the Baltic states.","url":"https://en.wikipedia.org/wiki/Sumner_Welles"},{"year":1927,"text":"Wilfred Rhodes of England and Yorkshire became the only person to play in 1,000 first-class cricket matches.","url":"https://en.wikipedia.org/wiki/Wilfred_Rhodes"},{"year":1921,"text":"The first National Congress of the Chinese Communist Party opened in a house in Shanghai.","url":"https://en.wikipedia.org/wiki/1st_National_Congress_of_the_Chinese_Communist_Party"},{"year":1891,"text":"During a visit of the French Navy to Kronstadt in Russia, the two nations reached a secret agreement on a joint response to any future war in Europe.","url":"https://en.wikipedia.org/wiki/Kronstadt%E2%80%93Toulon_naval_visits"},{"year":1860,"text":"The trial of the Eastbourne manslaughter, which later became an important legal precedent in the United Kingdom for discussions of corporal punishment in schools, began in Lewes.","url":"https://en.wikipedia.org/wiki/Eastbourne_manslaughter"},{"year":1319,"text":"A fleet led by the Knights Hospitaller sank 22 of 28 ships of the Turkish Aydinid emirate.","url":"https://en.wikipedia.org/wiki/Knights_Hospitaller"}],"births":[{"year":2003,"text":"Alex Consani, Model and Influencer","url":"https://en.wikipedia.org/wiki/Alex_Consani"},{"year":2002,"text":"Séléna Janicijevic, French tennis player","url":"https://en.wikipedia.org/wiki/S%C3%A9l%C3%A9na_Janicijevic"},{"year":2001,"text":"Lily Phillips, British pornographic actress","url":"https://en.wikipedia.org/wiki/Lily_Phillips"},{"year":1998,"text":"Deandre Ayton, Bahamian basketball player","url":"https://en.wikipedia.org/wiki/Deandre_Ayton"},{"year":1996,"text":"Alexandra Andresen, Norwegian heiress and equestrian","url":"https://en.wikipedia.org/wiki/Alexandra_Andresen"},{"year":1996,"text":"David Dobrik, Slovak YouTube personality","url":"https://en.wikipedia.org/wiki/David_Dobrik"},{"year":1996,"text":"Kasperi Kapanen, Finnish ice hockey player","url":"https://en.wikipedia.org/wiki/Kasperi_Kapanen"},{"year":1996,"text":"Danielle Bradbery, American singer","url":"https://en.wikipedia.org/wiki/Danielle_Bradbery"}],"deaths":[{"year":2024,"text":"Robin Warren, Australian pathologist and academic, Nobel Prize laureate (born 1937)","url":"https://en.wikipedia.org/wiki/Robin_Warren"},{"year":2022,"text":"Zayar Thaw, Burmese politician and rapper (born 1981)","url":"https://en.wikipedia.org/wiki/Phyo_Zeya_Thaw"},{"year":2022,"text":"Kyaw Min Yu, Burmese political activist (born 1969)","url":"https://en.wikipedia.org/wiki/Kyaw_Min_Yu"},{"year":2017,"text":"John Kundla, American basketball coach (born 1916)","url":"https://en.wikipedia.org/wiki/John_Kundla"},{"year":2015,"text":"Shigeko Kubota, Japanese-American sculptor and director (born 1937)","url":"https://en.wikipedia.org/wiki/Shigeko_Kubota"},{"year":2015,"text":"Don Oberdorfer, American journalist, author, and academic (born 1931)","url":"https://en.wikipedia.org/wiki/Don_Oberdorfer"},{"year":2015,"text":"William Wakefield Baum, American cardinal (born 1926)","url":"https://en.wikipedia.org/wiki/William_Wakefield_Baum"},{"year":2014,"text":"Dora Bryan, English actress and restaurateur (born 1923)","url":"https://en.wikipedia.org/wiki/Dora_Bryan"}]},"sources":[{"id":"attention","name":"Wikipedia 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Every item links to its source."}