{"date":"2025-12-11","schema_version":1,"captured_at":"2026-08-25T23:04:34.667Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"Dhurandhar","views":562210,"rank":3,"extract":"Dhurandhar is a 2025 Indian Hindi-language spy action thriller film written and directed by Aditya Dhar. It is produced by Aditya Dhar, Lokesh Dhar and Jyoti Deshpande under Jio Studios and B62 Studios. The film features an ensemble cast consisting of Ranveer ","url":"https://en.wikipedia.org/wiki/Dhurandhar","thumb":"https://upload.wikimedia.org/wikipedia/en/c/ce/Dhurandhar_poster.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail_unscaled"},{"title":"E-Government in Saudi Arabia","views":389259,"rank":4,"extract":"The e-Government in Saudi Arabia was established as per Royal Decree No. 7/B/33181 dated 7 September 2003. 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Recent state-of-the-art solutions addressing this challenge include deep learning techniques as they provide end-to-end solution to predict steering angles directly from the raw input images with higher accuracy. Most of these works ignore the temporal dependencies between the image frames. In this paper, we t","authors":["Valiente, Rodolfo","Zaman, Mahdi","Ozer, Sedat","Fallah, Yaser P."],"url":"https://arxiv.org/abs/1904.04375","arxiv_id":"1904.04375","published":"2025-12-11"},{"title":"Two Causal Principles for Improving Visual Dialog","abstract":"This paper unravels the design tricks adopted by us, the champion team MReaL-BDAI, for Visual Dialog Challenge 2019: two causal principles for improving Visual Dialog (VisDial). By "improving", we mean that they can promote almost every existing VisDial model to the state-of-the-art performance on the leader-board. Such a major improvement is only due to our careful inspection on the causality behind the mode","authors":["Qi, Jiaxin","Niu, Yulei","Huang, Jianqiang","Zhang, Hanwang"],"url":"https://arxiv.org/abs/1911.10496","arxiv_id":"1911.10496","published":"2025-12-11"},{"title":"TCNN: Triple Convolutional Neural Network Models for Retrieval-based Question Answering System in E-commerce","abstract":"Automatic question-answering (QA) systems have boomed during last few years, and commonly used techniques can be roughly categorized into Information Retrieval (IR)-based and generation-based. A key solution to the IR based models is to retrieve the most similar knowledge entries of a given query from a QA knowledge base, and then rerank those knowledge entries with semantic matching models. In this paper, we aim to ","authors":["Song, Shuangyong","Wang, Chao"],"url":"https://arxiv.org/abs/2004.10919","arxiv_id":"2004.10919","published":"2025-12-11"},{"title":"Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses","abstract":"How related are the representations learned by neural language models, translation models, and language tagging tasks? We answer this question by adapting an encoder-decoder transfer learning method from computer vision to investigate the structure among 100 different feature spaces extracted from hidden representations of various networks trained on language tasks. This method reveals a low-dimensional structure whe","authors":["Antonello, Richard","Turek, Javier","Vo, Vy","Huth, Alexander"],"url":"https://arxiv.org/abs/2106.05426","arxiv_id":"2106.05426","published":"2025-12-11"},{"title":"Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic","abstract":"With the adoption of autonomous vehicles on our roads, we will witness a mixed-autonomy environment where autonomous and human-driven vehicles must learn to co-exist by sharing the same road infrastructure. To attain socially-desirable behaviors, autonomous vehicles must be instructed to consider the utility of other vehicles around them in their decision-making process. Particularly, we study the maneuver planning p","authors":["Toghi, Behrad","Valiente, Rodolfo","Sadigh, Dorsa","Pedarsani, Ramtin","Fallah, Yaser P."],"url":"https://arxiv.org/abs/2107.05664","arxiv_id":"2107.05664","published":"2025-12-11"},{"title":"Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic","abstract":"Building autonomous vehicles (AVs) is a complex problem, but enabling them to operate in the real world where they will be surrounded by human-driven vehicles (HVs) is extremely challenging. Prior works have shown the possibilities of creating inter-agent cooperation between a group of AVs that follow a social utility. Such altruistic AVs can form alliances and affect the behavior of HVs to achieve socially desirable","authors":["Valiente, Rodolfo","Toghi, Behrad","Pedarsani, Ramtin","Fallah, Yaser P."],"url":"https://arxiv.org/abs/2202.00881","arxiv_id":"2202.00881","published":"2025-12-11"},{"title":"Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving","abstract":"Autonomous vehicle (AV) navigation in the presence of Human-driven vehicles (HVs) is challenging, as HVs continuously update their policies in response to AVs. In order to navigate safely in the presence of complex AV-HV social interactions, the AVs must learn to predict these changes. Humans are capable of navigating such challenging social interaction settings because of their intrinsic knowledge about other agents","authors":["Valiente, Rodolfo","Razzaghpour, Mahdi","Toghi, Behrad","Shah, Ghayoor","Fallah, Yaser P."],"url":"https://arxiv.org/abs/2211.10585","arxiv_id":"2211.10585","published":"2025-12-11"},{"title":"Learning-based social coordination to improve safety and robustness of cooperative autonomous vehicles in mixed traffic","abstract":"It is expected that autonomous vehicles(AVs) and heterogeneous human-driven vehicles(HVs) will coexist on the same road. The safety and reliability of AVs will depend on their social awareness and their ability to engage in complex social interactions in a socially accepted manner. However, AVs are still inefficient in terms of cooperating with HVs and struggle to understand and adapt to human behavior, which is part","authors":["Valiente, Rodolfo","Toghi, Behrad","Razzaghpour, Mahdi","Pedarsani, Ramtin","Fallah, Yaser P."],"url":"https://arxiv.org/abs/2211.11963","arxiv_id":"2211.11963","published":"2025-12-11"},{"title":"Preoperative Prognosis Assessment of Lumbar Spinal Surgery for Low Back Pain and Sciatica Patients based on Multimodalities and Multimodal Learning","abstract":"Low back pain (LBP) and sciatica may require surgical therapy when they are symptomatic of severe pain. However, there is no effective measures to evaluate the surgical outcomes in advance. This work combined elements of Eastern medicine and machine learning, and developed a preoperative assessment tool to predict the prognosis of lumbar spinal surgery in LBP and sciatica patients. Standard operative assessments, tra","authors":["Chen, Li-Chin","Lai, Jung-Nien","Lin, Hung-En","Chen, Hsien-Te","Hung, Kuo-Hsuan","Tsao, Yu"],"url":"https://arxiv.org/abs/2303.09085","arxiv_id":"2303.09085","published":"2025-12-11"},{"title":"The Vector Grounding Problem","abstract":"Large language models (LLMs) produce seemingly meaningful outputs, yet they are trained on text alone without direct interaction with the world. This leads to a modern variant of the classical symbol grounding problem in AI: can LLMs' internal states and outputs be about extra-linguistic reality, independently of the meaning human interpreters project onto them? We argue that they can. We first distinguish refere","authors":["Mollo, Dimitri Coelho","Millière, Raphaël"],"url":"https://arxiv.org/abs/2304.01481","arxiv_id":"2304.01481","published":"2025-12-11"},{"title":"Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning","abstract":"Federated Learning (FL) is a machine learning paradigm that enables clients to jointly train a global model by aggregating the locally trained models without sharing any local training data. In practice, there can often be substantial heterogeneity (e.g., class imbalance) across the local data distributions observed by each of these clients. Under such non-iid label distributions across clients, FL suffers from the &","authors":["Yashwanth, M","Nayak, Gaurav Kumar","Singh, Arya","Simmhan, Yogesh","Chakraborty, Anirban"],"url":"https://arxiv.org/abs/2305.19600","arxiv_id":"2305.19600","published":"2025-12-11"},{"title":"Information-Theoretic Active Correlation Clustering","abstract":"Correlation clustering is a flexible framework for partitioning data based solely on pairwise similarity or dissimilarity information, without requiring the number of clusters as input. However, in many practical scenarios, these pairwise similarities are not available a priori and must be obtained through costly measurements or human feedback. This motivates the use of active learning to query only the most informat","authors":["Aronsson, Linus","Chehreghani, Morteza Haghir"],"url":"https://arxiv.org/abs/2402.03587","arxiv_id":"2402.03587","published":"2025-12-11"},{"title":"Improving Topic Relevance Model by Mix-structured Summarization and LLM-based Data Augmentation","abstract":"Topic relevance between query and document is a very important part of social search, which can evaluate the degree of matching between document and user's requirement. In most social search scenarios such as Dianping, modeling search relevance always faces two challenges. One is that many documents in social search are very long and have much redundant information. The other is that the training data for search ","authors":["Liu, Yizhu","Tao, Ran","Guo, Shengyu","Yang, Yifan"],"url":"https://arxiv.org/abs/2404.02616","arxiv_id":"2404.02616","published":"2025-12-11"},{"title":"Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data","abstract":"Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some cases privacy concerns, among others. This paper presents an overview of the 2nd edition of the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized ","authors":["DeAndres-Tame, Ivan","Tolosana, Ruben","Melzi, Pietro","Vera-Rodriguez, Ruben","Kim, Minchul","Rathgeb, Christian"],"url":"https://arxiv.org/abs/2404.10378","arxiv_id":"2404.10378","published":"2025-12-11"},{"title":"Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search","abstract":"We study the robustness of data-centric methods to find neural network architectures, known as neural architecture search (NAS), against data poisoning. To audit this robustness, we design a poisoning framework that enables the systematic evaluation of the ability of NAS to produce architectures under data corruption. Our framework examines four off-the-shelf NAS algorithms, representing different approaches to archi","authors":["Coalson, Zachary","Wang, Huazheng","Wu, Qingyun","Hong, Sanghyun"],"url":"https://arxiv.org/abs/2405.06073","arxiv_id":"2405.06073","published":"2025-12-11"},{"title":"Breast Cancer Diagnosis: A Comprehensive Exploration of Explainable Artificial Intelligence (XAI) Techniques","abstract":"Breast cancer (BC) stands as one of the most common malignancies affecting women worldwide, necessitating advancements in diagnostic methodologies for better clinical outcomes. This article provides a comprehensive exploration of the application of Explainable Artificial Intelligence (XAI) techniques in the detection and diagnosis of breast cancer. As Artificial Intelligence (AI) technologies continue to permeate the","authors":["Bai, Samita","Nasir, Sidra","Khan, Rizwan Ahmed","Meyer, Alexandre","Konik, Hubert"],"url":"https://arxiv.org/abs/2406.00532","arxiv_id":"2406.00532","published":"2025-12-11"},{"title":"Multi-Scale Direction-Aware Network for Infrared Small Target Detection","abstract":"Infrared small target detection faces the problem that it is difficult to effectively separate the background and the target. Existing deep learning-based methods focus on edge and shape features, but ignore the richer structural differences and detailed information embedded in high-frequency components from different directions, thereby failing to fully exploit the value of high-frequency directional features in tar","authors":["Zhao, Jinmiao","Shi, Zelin","Yu, Chuang","Liu, Yunpeng","Ying, Xinyi","Dai, Yimian"],"url":"https://arxiv.org/abs/2406.02037","arxiv_id":"2406.02037","published":"2025-12-11"},{"title":"A survey on the impacts of recommender systems on users, items, and human-AI ecosystems","abstract":"Recommendation systems and assistants (in short, recommenders) influence through online platforms most actions of our daily lives, suggesting items or providing solutions based on users' preferences or requests. This survey systematically reviews, categories, and discusses the impact of recommenders in four human-AI ecosystems -- social media, online retail, urban mapping and generative AI ecosystems. Its scope i","authors":["Pappalardo, Luca","Citraro, Salvatore","Cornacchia, Giuliano","Nanni, Mirco","Pansanella, Valentina","Rossetti, Giulio"],"url":"https://arxiv.org/abs/2407.01630","arxiv_id":"2407.01630","published":"2025-12-11"},{"title":"Leveraging Machine Learning to Identify Gendered Stereotypes and Body Image Concerns on Diet and Fitness Online Forums","abstract":"The pervasive expectations about ideal body types in Western society can lead to body image concerns, dissatisfaction, and in extreme cases, eating disorders and other psychopathologies related to body image. While previous research has focused on online pro-anorexia communities glorifying the "thin ideal," less attention has been given to the broader spectrum of body image concerns or how emerging disorders ","authors":["Chu, Minh Duc","Sánchez, Cinthia","He, Zihao","Dorn, Rebecca","Murray, Stuart","Lerman, Kristina"],"url":"https://arxiv.org/abs/2407.03551","arxiv_id":"2407.03551","published":"2025-12-11"},{"title":"Entropy-Informed Weighting Channel Normalizing Flow for Deep Generative Models","abstract":"Normalizing Flows (NFs) are widely used in deep generative models for their exact likelihood estimation and efficient sampling. However, they require substantial memory since the latent space matches the input dimension. Multi-scale architectures address this by progressively reducing latent dimensions while preserving reversibility. Existing multi-scale architectures use simple, static channel-wise splitting, limiti","authors":["Chen, Wei","Du, Shian","Li, Shigui","Zeng, Delu","Paisley, John"],"url":"https://arxiv.org/abs/2407.04958","arxiv_id":"2407.04958","published":"2025-12-11"},{"title":"Generative AI Augmented Induction-based Formal Verification","abstract":"Generative Artificial Intelligence (GenAI) has demonstrated its capabilities in the present world that reduce human effort significantly. It utilizes deep learning techniques to create original and realistic content in terms of text, images, code, music, and video. Researchers have also shown the capabilities of modern Large Language Models (LLMs) used by GenAI models that can be used to aid hardware development. For","authors":["Kumar, Aman","Gadde, Deepak Narayan"],"url":"https://arxiv.org/abs/2407.18965","arxiv_id":"2407.18965","published":"2025-12-11"},{"title":"Towards Robust Infrared Small Target Detection: A Feature-Enhanced and Sensitivity-Tunable Framework","abstract":"Recently, single-frame infrared small target (SIRST) detection technology has attracted widespread attention. Different from most existing deep learning-based methods that focus on improving network architectures, we propose a feature-enhanced and sensitivity-tunable (FEST) framework, which is compatible with existing SIRST detection networks and further enhances their detection performance. The FEST framework improv","authors":["Zhao, Jinmiao","Shi, Zelin","Yu, Chuang","Liu, Yunpeng","Dai, Yimian"],"url":"https://arxiv.org/abs/2407.20090","arxiv_id":"2407.20090","published":"2025-12-11"},{"title":"Effects of a Prompt Engineering Intervention on Undergraduate Students' AI Self-Efficacy, AI Knowledge and Prompt Engineering Ability: A Mixed Methods Study","abstract":"Prompt engineering is critical for effective interaction with large language models (LLMs) such as ChatGPT. However, efforts to teach this skill to students have been limited. This study designed and implemented a prompt engineering intervention, examining its influence on undergraduate students' AI self-efficacy, AI knowledge, and proficiency in creating effective prompts. The intervention involved 27 students w","authors":["Woo, David James","Wang, Deliang","Yung, Tim","Guo, Kai"],"url":"https://arxiv.org/abs/2408.07302","arxiv_id":"2408.07302","published":"2025-12-11"},{"title":"LLM-Barber: Block-Aware Rebuilder for Sparsity Mask in One-Shot for Large Language Models","abstract":"Large language models (LLMs) have seen substantial growth, necessitating efficient model pruning techniques. Existing post-training pruning methods primarily measure weight importance in converged dense models, often overlooking changes in weight significance during the pruning process, leading to performance degradation. To address this issue, we present LLM-Barber (Block-Aware Rebuilder for Sparsity Mask in One-Sho","authors":["Su, Yupeng","Guan, Ziyi","Liu, Xiaoqun","Jin, Tianlai","Wu, Dongkuan","Chen, Zhengfei"],"url":"https://arxiv.org/abs/2408.10631","arxiv_id":"2408.10631","published":"2025-12-11"},{"title":"Point Neuron Learning: A New Physics-Informed Neural Network Architecture","abstract":"Machine learning and neural networks have advanced numerous research domains, but challenges such as large training data requirements and inconsistent model performance hinder their application in certain scientific problems. To overcome these challenges, researchers have investigated integrating physics principles into machine learning models, mainly through: (i) physics-guided loss functions, generally termed as ph","authors":["Bi, Hanwen","Abhayapala, Thushara D."],"url":"https://arxiv.org/abs/2408.16969","arxiv_id":"2408.16969","published":"2025-12-11"}],"history":{"events":[{"year":2024,"text":"Urfan Sharif and Beinash Batool were found guilty of the murder of Sara Sharif, and were sentenced to life imprisonment.","url":"https://en.wikipedia.org/wiki/Murder_of_Sara_Sharif"},{"year":2008,"text":"American stockbroker Bernie Madoff was arrested and charged with securities fraud in a $64.8 billion Ponzi scheme, the largest in history.","url":"https://en.wikipedia.org/wiki/Bernie_Madoff"},{"year":2008,"text":"American stockbroker Bernie Madoff was arrested and charged with securities fraud in a $64.8 billion Ponzi scheme, the largest in history.","url":"https://en.wikipedia.org/wiki/Bernie_Madoff"},{"year":2006,"text":"The first action in the Mexican drug war began as President Felipe Calderón ordered Mexican soldiers and Federal Police units into the state of Michoacán.","url":"https://en.wikipedia.org/wiki/Mexican_drug_war"},{"year":2006,"text":"Criticized worldwide as a \"meeting of Holocaust deniers\", the International Conference to Review the Global Vision of the Holocaust opened in Tehran.","url":"https://en.wikipedia.org/wiki/Holocaust_denial"},{"year":2005,"text":"Demonstrations in Cronulla, a suburb of Sydney, against recent violence towards locals turned into a series of race riots.","url":"https://en.wikipedia.org/wiki/Cronulla"},{"year":1972,"text":"Apollo 17 (Lunar Roving Vehicle pictured), the last Apollo mission, landed on the Moon.","url":"https://en.wikipedia.org/wiki/Apollo_17"},{"year":1925,"text":"Pope Pius XI promulgated the encyclical Quas primas, establishing the Feast of Christ the King.","url":"https://en.wikipedia.org/wiki/Pope_Pius_XI"},{"year":1920,"text":"Irish War of Independence: Following an Irish Republican Army ambush of an Auxiliary patrol, British forces burned and looted numerous buildings in Cork.","url":"https://en.wikipedia.org/wiki/Irish_War_of_Independence"},{"year":1907,"text":"The original Parliament House in Wellington, New Zealand, was destroyed by fire (pictured).","url":"https://en.wikipedia.org/wiki/Parliament_House%2C_Wellington"},{"year":1899,"text":"Second Boer War: In the Battle of Magersfontein, Boers defeated British forces trying to relieve the Siege of Kimberley.","url":"https://en.wikipedia.org/wiki/Second_Boer_War"},{"year":1886,"text":"The London-based football club Arsenal, then known as Dial Square, played their first match on the Isle of Dogs.","url":"https://en.wikipedia.org/wiki/Association_football"},{"year":1789,"text":"The University of North Carolina at Chapel Hill (structure pictured), one of the oldest public universities in the United States and the only one to award degrees in the 18th century, was chartered.","url":"https://en.wikipedia.org/wiki/University_of_North_Carolina_at_Chapel_Hill"},{"year":1640,"text":"A crowd of 1,500 people presented the Root and Branch petition to the Long Parliament, calling for abolishing the episcopacy of the Church of England.","url":"https://en.wikipedia.org/wiki/Root_and_Branch_petition"},{"year":861,"text":"The Abbasid caliph al-Mutawakkil was assassinated by his guards, beginning the Anarchy at Samarra.","url":"https://en.wikipedia.org/wiki/Abbasid_Caliphate"}],"births":[{"year":2000,"text":"Onyeka Okongwu, American basketball player","url":"https://en.wikipedia.org/wiki/Onyeka_Okongwu"},{"year":1997,"text":"Matthew Tkachuk, American ice hockey player","url":"https://en.wikipedia.org/wiki/Matthew_Tkachuk"},{"year":1996,"text":"Hailee Steinfeld, American actress, singer and songwriter","url":"https://en.wikipedia.org/wiki/Hailee_Steinfeld"},{"year":1995,"text":"Abbi Grant, Scottish footballer","url":"https://en.wikipedia.org/wiki/Abbi_Grant"},{"year":1993,"text":"Yalitza Aparicio, Mexican actress","url":"https://en.wikipedia.org/wiki/Yalitza_Aparicio"},{"year":1992,"text":"Tiffany Alvord, American singer-songwriter","url":"https://en.wikipedia.org/wiki/Tiffany_Alvord"},{"year":1992,"text":"Malcolm Brogdon, American basketball player","url":"https://en.wikipedia.org/wiki/Malcolm_Brogdon"},{"year":1990,"text":"Alexa Demie, American actress and singer","url":"https://en.wikipedia.org/wiki/Alexa_Demie"}],"deaths":[{"year":2024,"text":"David Bonderman, American billionaire businessman (born 1942)","url":"https://en.wikipedia.org/wiki/David_Bonderman"},{"year":2024,"text":"Khalil Haqqani, Afghan politician and warlord (born 1966)","url":"https://en.wikipedia.org/wiki/Khalil_Haqqani"},{"year":2024,"text":"Purushottam Upadhyay, Indian musician, singer and composer (born 1934)","url":"https://en.wikipedia.org/wiki/Purushottam_Upadhyay"},{"year":2023,"text":"Andre Braugher, American actor (born 1962)","url":"https://en.wikipedia.org/wiki/Andre_Braugher"},{"year":2021,"text":"Anne Rice, American author (born 1941)","url":"https://en.wikipedia.org/wiki/Anne_Rice"},{"year":2020,"text":"James Flynn, New Zealand intelligence researcher. (born 1934)","url":"https://en.wikipedia.org/wiki/James_Flynn_(academic)"},{"year":2017,"text":"Keith Chegwin, British TV presenter (born 1957)","url":"https://en.wikipedia.org/wiki/Keith_Chegwin"},{"year":2015,"text":"Abish Kekilbayev, Kazakh academic and politician (born 1939)","url":"https://en.wikipedia.org/wiki/Abish_Kekilbayev"}]},"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."}