{"date":"2026-02-03","schema_version":1,"captured_at":"2026-08-25T23:26:40.285Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Jeffrey Epstein","views":875619,"rank":3,"extract":"Jeffrey Edward Epstein was an American financier and child sex offender. He began his career as a math teacher at the Dalton School in New York City, before entering the banking and finance sector. 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In this way, the structure of ANN can be represented by a simple function, and it is possible to find the mathematical solutions of ANN. Thus, it can be recognized that the current ANN can be placed in a more reasonable framework. Perhaps all questions","authors":["Ma, Zhongkui"],"url":"https://arxiv.org/abs/1908.10493","arxiv_id":"1908.10493","published":"2026-02-03"},{"title":"Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)","abstract":"Machine learning (ML) can help fight pandemics like COVID-19 by enabling rapid screening of large volumes of images. To perform data analysis while maintaining patient privacy, we create ML models that satisfy Differential Privacy (DP). Previous works exploring private COVID-19 models are in part based on small datasets, provide weaker or unclear privacy guarantees, and do not investigate practical privacy. We sugges","authors":["Lange, Lucas","Schneider, Maja","Christen, Peter","Rahm, Erhard"],"url":"https://arxiv.org/abs/2211.11434","arxiv_id":"2211.11434","published":"2026-02-03"},{"title":"Safe Control and Learning Using Generalized Action Governor","abstract":"This paper introduces the Generalized Action Governor (AG), a supervisory scheme that augments a nominal closed-loop system with the capability to enforce state and input constraints through online action adjustment. We develop a generalized AG theory for discrete-time systems under bounded uncertainties, and relax the usual requirement of positive invariance to returnability of a safe set. Based on the theory, we pr","authors":["Fang, Peiyuan","Zhang, Weiqi","Xiong, Lu","Li, Nan","Huang, Yanjun","Li, Yutong"],"url":"https://arxiv.org/abs/2211.12628","arxiv_id":"2211.12628","published":"2026-02-03"},{"title":"Revolutionizing Genomics with Reinforcement Learning Techniques","abstract":"In recent years, Reinforcement Learning (RL) has emerged as a powerful tool for solving a wide range of problems, including decision-making and genomics. The exponential growth of raw genomic data over the past two decades has exceeded the capacity of manual analysis, leading to a growing interest in automatic data analysis and processing. RL algorithms are capable of learning from experience with minimal human super","authors":["Karami, Mohsen","Khadijeh","Jahanian","Alizadehsani, Roohallah","Dehzangi, Iman","Gorriz, Juan M"],"url":"https://arxiv.org/abs/2302.13268","arxiv_id":"2302.13268","published":"2026-02-03"},{"title":"The Principle of Uncertain Maximum Entropy","abstract":"The Principle of Maximum Entropy is a rigorous technique for estimating an unknown distribution given partial information while simultaneously minimizing bias. However, an important requirement for applying the principle is that the available information be provided error-free (Jaynes, 1982). We relax this requirement using a memoryless communication channel as a framework to derive a new, more general principle. We ","authors":["Bogert, Kenneth","Kothe, Matthew"],"url":"https://arxiv.org/abs/2305.09868","arxiv_id":"2305.09868","published":"2026-02-03"},{"title":"MiniLLM: On-Policy Distillation of Large Language Models","abstract":"Knowledge Distillation (KD) is a promising technique for reducing the high computational demand of large language models (LLMs). However, previous KD methods are primarily applied to white-box classification models or training small models to imitate black-box model APIs like ChatGPT. How to effectively distill the knowledge of white-box LLMs into small models is still under-explored, which becomes more important wit","authors":["Gu, Yuxian","Dong, Li","Wei, Furu","Huang, Minlie"],"url":"https://arxiv.org/abs/2306.08543","arxiv_id":"2306.08543","published":"2026-02-03"},{"title":"Wikibio: a Semantic Resource for the Intersectional Analysis of Biographical Events","abstract":"Biographical event detection is a relevant task for the exploration and comparison of the ways in which people's lives are told and represented. In this sense, it may support several applications in digital humanities and in works aimed at exploring bias about minoritized groups. Despite that, there are no corpora and models specifically designed for this task. In this paper we fill this gap by presenting a new c","authors":["Stranisci, Marco Antonio","Damiano, Rossana","Mensa, Enrico","Patti, Viviana","Radicioni, Daniele","Caselli, Tommaso"],"url":"https://arxiv.org/abs/2306.09505","arxiv_id":"2306.09505","published":"2026-02-03"},{"title":"T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems","abstract":"To address the interpretability challenge in machine learning (ML) systems, counterfactual explanations (CEs) have emerged as a promising solution. CEs are unique as they provide workable suggestions to users, instead of explaining why a certain outcome was predicted. The application of CEs encounters two main challenges: general user preferences and variable ML systems. On one hand, user preferences for specific val","authors":["Wang, Ming","Wang, Daling","Wu, Wenfang","Feng, Shi","Zhang, Yifei"],"url":"https://arxiv.org/abs/2309.16146","arxiv_id":"2309.16146","published":"2026-02-03"},{"title":"Parameter-efficient Multi-Task and Multi-Domain Learning using Factorized Tensor Networks","abstract":"Multi-task and multi-domain learning methods seek to learn multiple tasks/domains, jointly or one after another, using a single unified network. The primary challenge and opportunity lie in leveraging shared information across these tasks and domains to enhance the efficiency of the unified network. The efficiency can be in terms of accuracy, storage cost, computation, or sample complexity. In this paper, we introduc","authors":["Garg, Yash","Yismaw, Nebiyou","Hyder, Rakib","Prater-Bennette, Ashley","Asif, M. Salman"],"url":"https://arxiv.org/abs/2310.06124","arxiv_id":"2310.06124","published":"2026-02-03"},{"title":"From Lengthy to Lucid: A Systematic Literature Review on NLP Techniques for Taming Long Sentences","abstract":"Long sentences have been a persistent issue in written communication for many years since they make it challenging for readers to grasp the main points or follow the initial intention of the writer. This survey, conducted using the PRISMA guidelines, systematically reviews two main strategies for addressing the issue of long sentences: a) sentence compression and b) sentence splitting. An increased trend of interest ","authors":["Passali, Tatiana","Chatzikyriakidis, Efstathios","Andreadis, Stelios","Stavropoulos, Thanos G.","Matonaki, Anastasia","Fachantidis, Anestis"],"url":"https://arxiv.org/abs/2312.05172","arxiv_id":"2312.05172","published":"2026-02-03"},{"title":"Brain-inspired Computing Based on Deep Learning for Human-computer Interaction: A Review","abstract":"The continuous development of artificial intelligence has a profound impact on biomedicine and other fields, providing new research ideas and technical methods. Brain-inspired computing is an important intersection between multimodal technology and biomedical field. Focusing on the application scenarios of decoding text and speech from brain signals in human-computer interaction, this paper presents a comprehensive r","authors":["Yu, Bihui","Zhang, Sibo","Zhou, Lili","Wei, Jingxuan","Sun, Linzhuang","Bu, Liping"],"url":"https://arxiv.org/abs/2312.07213","arxiv_id":"2312.07213","published":"2026-02-03"},{"title":"Operator learning for hyperbolic partial differential equations","abstract":"We construct the first rigorously justified probabilistic algorithm for recovering the solution operator of a hyperbolic partial differential equation (PDE) in two variables from input-output training pairs. The primary challenge of recovering the solution operator of hyperbolic PDEs is the presence of characteristics, along which the associated Green's function is discontinuous. Therefore, a central component of","authors":["Wang, Christopher","Townsend, Alex"],"url":"https://arxiv.org/abs/2312.17489","arxiv_id":"2312.17489","published":"2026-02-03"},{"title":"Unified Task and Motion Planning using Object-centric Abstractions of Motion Constraints","abstract":"In task and motion planning (TAMP), the ambiguity and underdetermination of abstract descriptions used by task planning methods make it difficult to characterize physical constraints needed to successfully execute a task. The usual approach is to overlook such constraints at task planning level and to implement expensive sub-symbolic geometric reasoning techniques that perform multiple calls on unfeasible actions, pl","authors":["Agostini, Alejandro","Piater, Justus"],"url":"https://arxiv.org/abs/2312.17605","arxiv_id":"2312.17605","published":"2026-02-03"},{"title":"Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection","abstract":"Smartwatch health sensor data are increasingly utilized in smart health applications and patient monitoring, including stress detection. However, such medical data often comprise sensitive personal information and are resource-intensive to acquire for research purposes. In response to this challenge, we introduce the privacy-aware synthetization of multi-sensor smartwatch health readings related to moments of stress,","authors":["Lange, Lucas","Wenzlitschke, Nils","Rahm, Erhard"],"url":"https://arxiv.org/abs/2401.13327","arxiv_id":"2401.13327","published":"2026-02-03"},{"title":"Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning","abstract":"Membership inference attacks (MIAs) are used to test practical privacy of machine learning models. MIAs complement formal guarantees from differential privacy (DP) under a more realistic adversary model. We analyse MIA vulnerability of fine-tuned neural networks both empirically and theoretically, the latter using a simplified model of fine-tuning. We show that the vulnerability of non-DP models when measured as the ","authors":["Tobaben, Marlon","Ito, Hibiki","Jälkö, Joonas","He, Yuan","Honkela, Antti"],"url":"https://arxiv.org/abs/2402.06674","arxiv_id":"2402.06674","published":"2026-02-03"},{"title":"Towards Artwork Explanation in Large-scale Vision Language Models","abstract":"Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clarified to what extent LVLMs possess the ability to understand the knowledge necessary for explaining images, the complex relationships between various pieces of knowledge, and how they integrate these understandings into their explanations. T","authors":["Hayashi, Kazuki","Sakai, Yusuke","Kamigaito, Hidetaka","Hayashi, Katsuhiko","Watanabe, Taro"],"url":"https://arxiv.org/abs/2403.00068","arxiv_id":"2403.00068","published":"2026-02-03"},{"title":"Trajectory Data Management and Mining: A Survey from Deep Learning to the LLM Era","abstract":"Trajectory computing is a pivotal domain encompassing trajectory data management and mining, garnering widespread attention due to its crucial role in various practical applications such as location services, urban traffic, and public safety. Traditional methods, focusing on simplistic spatio-temporal features, face challenges of complex calculations, limited scalability, and inadequate adaptability to real-world com","authors":["Chen, Wei","Zhu, Yuanshao","Chang, Yanchuan","Luo, Kang","Wen, Haomin","Li, Lei"],"url":"https://arxiv.org/abs/2403.14151","arxiv_id":"2403.14151","published":"2026-02-03"},{"title":"LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models","abstract":"Large Multimodal Models (LMMs) have shown significant visual reasoning capabilities by connecting a visual encoder and a large language model. LMMs typically take in a fixed and large amount of visual tokens, such as the penultimate layer features in the CLIP visual encoder, as the prefix content. Recent LMMs incorporate more complex visual inputs, such as high-resolution images and videos, which further increases th","authors":["Shang, Yuzhang","Cai, Mu","Xu, Bingxin","Lee, Yong Jae","Yan, Yan"],"url":"https://arxiv.org/abs/2403.15388","arxiv_id":"2403.15388","published":"2026-02-03"},{"title":"ModeTv2: GPU-accelerated Motion Decomposition Transformer for Pairwise Optimization in Medical Image Registration","abstract":"Deformable image registration plays a crucial role in medical imaging, aiding in disease diagnosis and image-guided interventions. Traditional iterative methods are slow, while deep learning (DL) accelerates solutions but faces usability and precision challenges. This study introduces a pyramid network with the enhanced motion decomposition Transformer (ModeTv2) operator, showcasing superior pairwise optimization (PO","authors":["Wang, Haiqiao","Wang, Zhuoyuan","Ni, Dong","Wang, Yi"],"url":"https://arxiv.org/abs/2403.16526","arxiv_id":"2403.16526","published":"2026-02-03"},{"title":"InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction","abstract":"Text-conditioned human motion generation has experienced significant advancements with diffusion models trained on extensive motion capture data and corresponding textual annotations. However, extending such success to 3D dynamic human-object interaction (HOI) generation faces notable challenges, primarily due to the lack of large-scale interaction data and comprehensive descriptions that align with these interaction","authors":["Xu, Sirui","Wang, Ziyin","Wang, Yu-Xiong","Gui, Liang-Yan"],"url":"https://arxiv.org/abs/2403.19652","arxiv_id":"2403.19652","published":"2026-02-03"},{"title":"VC Theory for Inventory Policies","abstract":"There has been growing interest in applying reinforcement learning (RL) to inventory management, either by optimizing over temporal transitions or by learning directly from full historical demand trajectories. This contrasts sharply with classical data-driven approaches, which first estimate demand distributions from past data and then compute well-structured optimal policies via dynamic programming. This paper consi","authors":["Xie, Yaqi","Ma, Will","Xin, Linwei"],"url":"https://arxiv.org/abs/2404.11509","arxiv_id":"2404.11509","published":"2026-02-03"},{"title":"Deep Transformer Network for Monocular Pose Estimation of Shipborne Unmanned Aerial Vehicle","abstract":"This paper introduces a deep transformer network for estimating the relative 6D pose of a Unmanned Aerial Vehicle (UAV) with respect to a ship using monocular images. A synthetic dataset of ship images is created and annotated with 2D keypoints of multiple ship parts. A Transformer Neural Network model is trained to detect these keypoints and estimate the 6D pose of each part. The estimates are integrated using Bayes","authors":["Wickramasuriya, Maneesha","Lee, Taeyoung","Snyder, Murray"],"url":"https://arxiv.org/abs/2406.09260","arxiv_id":"2406.09260","published":"2026-02-03"},{"title":"Dual-Phase Continual Learning: Supervised Adaptation Meets Unsupervised Retention","abstract":"Foundational Vision-Language Models (VLMs) excel across diverse tasks, but adapting them to new domains without forgetting prior knowledge remains a critical challenge. Continual Learning (CL) addresses this challenge by enabling models to learn sequentially from new data while mitigating the forgetting of prior information, typically under supervised settings involving label shift. Nonetheless, abrupt distribution s","authors":["Singh, Vaibhav","Aljundi, Rahaf","Belilovsky, Eugene"],"url":"https://arxiv.org/abs/2406.13653","arxiv_id":"2406.13653","published":"2026-02-03"},{"title":"Retrospective Feature Estimation for Continual Learning","abstract":"The intrinsic capability to continuously learn a changing data stream is a desideratum of deep neural networks (DNNs). However, current DNNs suffer from catastrophic forgetting, which interferes with remembering past knowledge. To mitigate this issue, existing Continual Learning (CL) approaches often retain exemplars for replay, regularize learning, or allocate dedicated capacity for new tasks. This paper investigate","authors":["Nguyen, Nghia D.","Nguyen, Hieu Trung","Li, Ang","Pham, Hoang","Nguyen, Viet Anh","Doan, Khoa D."],"url":"https://arxiv.org/abs/2406.17381","arxiv_id":"2406.17381","published":"2026-02-03"},{"title":"Instance Temperature Knowledge Distillation","abstract":"Knowledge distillation (KD) enhances the performance of a student network by allowing it to learn the knowledge transferred from a teacher network incrementally. Existing methods dynamically adjust the temperature to enable the student network to adapt to the varying learning difficulties at different learning stages of KD. KD is a continuous process, but when adjusting the temperature, these methods consider only th","authors":["Zhang, Zhengbo","Zhou, Yuxi","Gong, Jia","Liu, Jun","Tu, Zhigang"],"url":"https://arxiv.org/abs/2407.00115","arxiv_id":"2407.00115","published":"2026-02-03"}],"history":{"events":[{"year":2023,"text":"A freight train derailed in East Palestine, Ohio, releasing hazardous materials into the surrounding area.","url":"https://en.wikipedia.org/wiki/East_Palestine%2C_Ohio%2C_train_derailment"},{"year":2014,"text":"Russia's first school shooting took place when a student opened fire at School No. 263 in Moscow, resulting in the deaths of a teacher and a police officer.","url":"https://en.wikipedia.org/wiki/School_shooting"},{"year":2010,"text":"An edition of L'Homme qui marche I, a bronze sculpture by Swiss sculptor Alberto Giacometti, was sold for £65 million, setting the record for the most expensive sculpture sold at auction.","url":"https://en.wikipedia.org/wiki/L'Homme_qui_marche_I"},{"year":2006,"text":"Al-Qaeda insurgency in Yemen: 23 convicts, including several militants associated with al-Qaeda, escaped from a prison administered by the Political Security Organization in Sanaa, Yemen.","url":"https://en.wikipedia.org/wiki/Al-Qaeda_insurgency_in_Yemen"},{"year":1998,"text":"Despite a large international movement advocating the commutation of her sentence to life imprisonment, Karla Faye Tucker became the first woman to be executed in the United States since 1984.","url":"https://en.wikipedia.org/wiki/Commutation_(law)"},{"year":1995,"text":"In mission STS-63, astronaut Eileen Collins (pictured) became the first woman to pilot the Space Shuttle.","url":"https://en.wikipedia.org/wiki/STS-63"},{"year":1986,"text":"Steve Jobs purchased Pixar from Lucasfilm and launched it as an independent computer-animation studio.","url":"https://en.wikipedia.org/wiki/Steve_Jobs"},{"year":1972,"text":"The deadliest blizzard in history began in Iran and continued for a week leaving more than 4,000 people dead.","url":"https://en.wikipedia.org/wiki/1972_Iran_blizzard"},{"year":1959,"text":"American rock and roll musicians Buddy Holly, Ritchie Valens, and J. P. \"The Big Bopper\" Richardson died in a plane crash (wreckage pictured) shortly after takeoff from Mason City Municipal Airport in Iowa.","url":"https://en.wikipedia.org/wiki/Rock_and_roll"},{"year":1953,"text":"Hundreds of native creoles known as Forros were massacred on São Tomé Island by the colonial administration and Portuguese landowners.","url":"https://en.wikipedia.org/wiki/Creole_peoples"},{"year":1941,"text":"World War II: Free French and British forces began the Battle of Keren to capture the strategic town of Keren in Italian East Africa.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1933,"text":"Adolf Hitler announced that the conquest of Lebensraum in Eastern Europe, and its \"ruthless Germanisation\", were the geopolitical objectives of Reich foreign policy.","url":"https://en.wikipedia.org/wiki/Adolf_Hitler"},{"year":1930,"text":"The Communist Party of Indochina, the Communist Party of Annam and the Communist League of Indochina merged to form the Communist Party of Vietnam.","url":"https://en.wikipedia.org/wiki/Communist_Party_of_Indochina"},{"year":1870,"text":"Reconstruction era: The Fifteenth Amendment to the United States Constitution was ratified, formally prohibiting race-based disenfranchisement in the United States.","url":"https://en.wikipedia.org/wiki/Reconstruction_era"},{"year":1862,"text":"Moldavia and Wallachia formally united, creating the Romanian United Principalities.","url":"https://en.wikipedia.org/wiki/Moldavia"},{"year":1852,"text":"The Argentine Confederation was defeated in the Platine War by an alliance consisting of Brazil, Uruguay and the Argentine provinces of Entre Ríos and Corrientes.","url":"https://en.wikipedia.org/wiki/Argentine_Confederation"},{"year":1813,"text":"Argentine War of Independence: José de San Martín and the Mounted Grenadiers Regiment defeated Spanish royalist forces in the Battle of San Lorenzo (depicted).","url":"https://en.wikipedia.org/wiki/Argentine_War_of_Independence"},{"year":1266,"text":"Mudéjar revolt: King James I of Aragon entered the formerly Muslim-held city of Murcia following its surrender three days earlier.","url":"https://en.wikipedia.org/wiki/Mud%C3%A9jar_revolt_of_1264%E2%80%931266"}],"births":[{"year":2004,"text":"Rei, Japanese rapper and singer","url":"https://en.wikipedia.org/wiki/Rei_(singer)"},{"year":2004,"text":"Scoot Henderson, American basketball player","url":"https://en.wikipedia.org/wiki/Scoot_Henderson"},{"year":2001,"text":"Tre Mann, American basketball player","url":"https://en.wikipedia.org/wiki/Tre_Mann"},{"year":2001,"text":"Rhys Williams, English footballer","url":"https://en.wikipedia.org/wiki/Rhys_Williams_(footballer%2C_born_2001)"},{"year":1999,"text":"Kanna Hashimoto, Japanese actress","url":"https://en.wikipedia.org/wiki/Kanna_Hashimoto"},{"year":1998,"text":"Tyler Huntley, American football player","url":"https://en.wikipedia.org/wiki/Tyler_Huntley"},{"year":1998,"text":"Isaiah Roby, American basketball player","url":"https://en.wikipedia.org/wiki/Isaiah_Roby"},{"year":1998,"text":"Aurélien Giraud, French skateboarder","url":"https://en.wikipedia.org/wiki/Aur%C3%A9lien_Giraud"}],"deaths":[{"year":2025,"text":"Harry Jayawardena, Sri Lankan industrialist (born 1942)","url":"https://en.wikipedia.org/wiki/Harry_Jayawardena"},{"year":2025,"text":"Kandiah Balendra, Sri Lankan corporate leader and executive (born 1940)","url":"https://en.wikipedia.org/wiki/Kandiah_Balendra"},{"year":2020,"text":"George Steiner, French-American philosopher, author, and critic (born 1929)","url":"https://en.wikipedia.org/wiki/George_Steiner"},{"year":2019,"text":"Julie Adams, American actress (born 1926)","url":"https://en.wikipedia.org/wiki/Julie_Adams"},{"year":2019,"text":"Kristoff St. John, American actor (born 1966)","url":"https://en.wikipedia.org/wiki/Kristoff_St._John"},{"year":2017,"text":"Dritëro Agolli, Albanian poet, writer and politician (born 1931)","url":"https://en.wikipedia.org/wiki/Drit%C3%ABro_Agolli"},{"year":2016,"text":"Joe Alaskey, American actor (born 1952)","url":"https://en.wikipedia.org/wiki/Joe_Alaskey"},{"year":2016,"text":"Balram Jakhar, Indian lawyer and politician, 23rd Governor of Madhya Pradesh (born 1923)","url":"https://en.wikipedia.org/wiki/Balram_Jakhar"}]},"census":null,"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."}