{"date":"2025-12-10","schema_version":1,"captured_at":"2026-08-25T23:04:22.513Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":18},"attention":[{"title":"Dhurandhar","views":539066,"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. 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situations and stimuli. Advances in machine learning and artificial intelligence have begun to approximate and even surpass human performance, but machine systems reliably struggle to generalize information to untrained situations. We describe a neural network model that is trained to play one video game (Breakout) and demonstrates one-shot generalization t","authors":["Doumas, Leonidas A. A.","Puebla, Guillermo","Martin, Andrea E."],"url":"https://arxiv.org/abs/1806.01709","arxiv_id":"1806.01709","published":"2025-12-10"},{"title":"Discovering Influential Factors in Variational Autoencoders","abstract":"In the field of machine learning, it is still a critical issue to identify and supervise the learned representation without manually intervening or intuition assistance to extract useful knowledge or serve for the downstream tasks. In this work, we focus on supervising the influential factors extracted by the variational autoencoder(VAE). The VAE is proposed to learn independent low dimension representation while fac","authors":["Liu, Shiqi","Liu, Jingxin","Zhao, Qian","Cao, Xiangyong","Li, Huibin","Meng, Deyu"],"url":"https://arxiv.org/abs/1809.01804","arxiv_id":"1809.01804","published":"2025-12-10"},{"title":"A Theory of Relation Learning and Cross-domain Generalization","abstract":"People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in humans is a case of analogical inference over structured (i.e., symbolic) relational representations. The model is an extension of the LISA and DORA models of relational inference and learning. The resulting model learns both the content an","authors":["Doumas, Leonidas A. A.","Puebla, Guillermo","Martin, Andrea E.","Hummel, John E."],"url":"https://arxiv.org/abs/1910.05065","arxiv_id":"1910.05065","published":"2025-12-10"},{"title":"Generative Learning of Heterogeneous Tail Dependence","abstract":"We propose a multivariate generative model to capture the complex dependence structure often encountered in business and financial data. Our model features heterogeneous and asymmetric tail dependence between all pairs of individual dimensions while also allowing heterogeneity and asymmetry in the tails of the marginals. A significant merit of our model structure is that it is not prone to error propagation in the pa","authors":["Sun, Xiangqian","Yan, Xing","Wu, Qi"],"url":"https://arxiv.org/abs/2011.13132","arxiv_id":"2011.13132","published":"2025-12-10"},{"title":"Astral Space: Convex Analysis at Infinity","abstract":"Not all convex functions on $\\mathbb{R}^n$ have finite minimizers; some can only be minimized by a sequence as it heads to infinity. In this work, we aim to develop a theory for understanding such minimizers at infinity. We study astral space, a compact extension of $\\mathbb{R}^n$ to which such points at infinity have been added. Astral space is constructed to be as small as possible while still ensuring that all lin","authors":["Dudík, Miroslav","Schapire, Robert E.","Telgarsky, Matus"],"url":"https://arxiv.org/abs/2205.03260","arxiv_id":"2205.03260","published":"2025-12-10"},{"title":"Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise","abstract":"The existence of spurious correlations such as image backgrounds in the training environment can make empirical risk minimization (ERM) perform badly in the test environment. To address this problem, Kirichenko et al. (2022) empirically found that the core features that are related to the outcome can still be learned well even with the presence of spurious correlations. This opens a promising strategy to first train ","authors":["Ye, Haotian","Zou, James","Zhang, Linjun"],"url":"https://arxiv.org/abs/2210.11075","arxiv_id":"2210.11075","published":"2025-12-10"},{"title":"Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment","abstract":"Counterfactuals are central in causal human reasoning and the scientific discovery process. The uplift, also called conditional average treatment effect, measures the causal effect of some action, or treatment, on the outcome of an individual. This paper discusses how it is possible to derive bounds on the probability of counterfactual statements based on uplift terms. First, we derive some original bounds on the pro","authors":["Verhelst, Théo","Mercier, Denis","Shrestha, Jeevan","Bontempi, Gianluca"],"url":"https://arxiv.org/abs/2211.07264","arxiv_id":"2211.07264","published":"2025-12-10"},{"title":"BeeTLe: An Imbalance-Aware Deep Sequence Model for Linear B-Cell Epitope Prediction and Classification with Logit-Adjusted Losses","abstract":"The process of identifying and characterizing B-cell epitopes, which are the portions of antigens recognized by antibodies, is important for our understanding of the immune system, and for many applications including vaccine development, therapeutics, and diagnostics. Computational epitope prediction is challenging yet rewarding as it significantly reduces the time and cost of laboratory work. Most of the existing to","authors":["Yuan, Xiao"],"url":"https://arxiv.org/abs/2309.02071","arxiv_id":"2309.02071","published":"2025-12-10"},{"title":"Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling","abstract":"The performance of Hamiltonian Monte Carlo simulations crucially depends on both the integration timestep and the number of integration steps. We present an adaptive general-purpose framework to automatically tune such parameters, based on a local loss function which promotes the fast exploration of phase-space. We show that a good correspondence between loss and autocorrelation time can be established, allowing for ","authors":["Christiansen, Henrik","Errica, Federico","Alesiani, Francesco"],"url":"https://arxiv.org/abs/2309.13593","arxiv_id":"2309.13593","published":"2025-12-10"},{"title":"RL-I2IT: Image-to-Image Translation with Deep Reinforcement Learning","abstract":"Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of a deep learning (DL) model. However, designing such a single-step model is always challenging, requiring a huge number of parameters and easily falling into bad global minimums and overfitting. In this work, we reformulate I2IT as a step-wise decision-making problem via deep reinforcement learning (DRL) and propose a novel fram","authors":["Hu, Jing","Luo, Ziwei","Feng, Chengming","Hu, Shu","Zhu, Bin","Wu, Xi"],"url":"https://arxiv.org/abs/2309.13672","arxiv_id":"2309.13672","published":"2025-12-10"},{"title":"MiniGPT-5: Interleaved Vision-and-Language Generation via Generative Vokens","abstract":"The effectiveness of Multimodal Large Language Models (MLLMs) demonstrates a profound capability in multimodal understanding. However, the simultaneous generation of images with coherent texts is still underdeveloped. Addressing this, we introduce a novel interleaved vision-and-language generation method, centered around the concept of ``generative vokens&#34;. These vokens serve as pivotal elements contributing to c","authors":["Zheng, Kaizhi","He, Xuehai","Wang, Xin Eric"],"url":"https://arxiv.org/abs/2310.02239","arxiv_id":"2310.02239","published":"2025-12-10"},{"title":"Diffusion Models for Wireless Communications","abstract":"A comprehensive study on the applications of denoising diffusion models for wireless systems is provided. The article highlights the capabilities of diffusion models in learning complicated signal distributions, modeling wireless channels, and denoising and reconstructing distorted signals. First, fundamental working mechanism of diffusion models is introduced. Then the recent advances in applying diffusion models to","authors":["Letafati, Mehdi","Ali, Samad","Latva-aho, Matti"],"url":"https://arxiv.org/abs/2310.07312","arxiv_id":"2310.07312","published":"2025-12-10"},{"title":"Leveraging heterogeneous spillover in maximizing contextual bandit rewards","abstract":"Recommender systems relying on contextual multi-armed bandits continuously improve relevant item recommendations by taking into account the contextual information. The objective of bandit algorithms is to learn the best arm (e.g., best item to recommend) for each user and thus maximize the cumulative rewards from user engagement with the recommendations. The context that these algorithms typically consider are the us","authors":["Faruk, Ahmed Sayeed","Zheleva, Elena"],"url":"https://arxiv.org/abs/2310.10259","arxiv_id":"2310.10259","published":"2025-12-10"},{"title":"Detecting value-expressive text posts in Russian social media","abstract":"Basic values are concepts or beliefs which pertain to desirable end-states and transcend specific situations. Studying personal values in social media can illuminate how and why societal values evolve especially when the stimuli-based methods, such as surveys, are inefficient, for instance, in hard-to-reach populations. On the other hand, user-generated content is driven by the massive use of stereotyped, culturally ","authors":["Milkova, Maria","Rudnev, Maksim","Okolskaya, Lidia"],"url":"https://arxiv.org/abs/2312.08968","arxiv_id":"2312.08968","published":"2025-12-10"},{"title":"Sampling and estimation on manifolds using the Langevin diffusion","abstract":"Error bounds are derived for sampling and estimation using a discretization of an intrinsically defined Langevin diffusion with invariant measure $\\text{d}μ_ϕ\\propto e^{-ϕ} \\mathrm{dvol}_g $ on a compact Riemannian manifold. Two estimators of linear functionals of $μ_ϕ$ based on the discretized Markov process are considered: a time-averaging estimator based on a single trajectory and an ensemble-averaging estimator b","authors":["Bharath, Karthik","Lewis, Alexander","Sharma, Akash","Tretyakov, Michael V"],"url":"https://arxiv.org/abs/2312.14882","arxiv_id":"2312.14882","published":"2025-12-10"},{"title":"Improving LLM Reliability with RAG in Religious Question-Answering: MufassirQAS","abstract":"Religious teachings can sometimes be complex and challenging to grasp, but chatbots can serve as effective assistants in this domain. Large Language Model (LLM) based chatbots, powered by Natural Language Processing (NLP), can connect related topics and provide well-supported responses to intricate questions, making them valuable tools for religious education. However, LLMs are prone to hallucinations as they can gen","authors":["Alan, Ahmet Yusuf","Karaarslan, Enis","Aydin, Omer"],"url":"https://arxiv.org/abs/2401.15378","arxiv_id":"2401.15378","published":"2025-12-10"},{"title":"Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark","abstract":"Pre-trained vision models (PVMs) have demonstrated remarkable adaptability across a wide range of downstream vision tasks, showcasing exceptional performance. However, as these models scale to billions or even trillions of parameters, conventional full fine-tuning has become increasingly impractical due to its high computational and storage demands. To address these challenges, parameter-efficient fine-tuning (PEFT) ","authors":["Xin, Yi","Yang, Jianjiang","Luo, Siqi","Du, Yuntao","Qin, Qi","Cen, Kangrui"],"url":"https://arxiv.org/abs/2402.02242","arxiv_id":"2402.02242","published":"2025-12-10"},{"title":"Spike-EVPR: Deep Spiking Residual Networks with SNN-Tailored Representations for Event-Based Visual Place Recognition","abstract":"Event cameras are ideal for visual place recognition (VPR) in challenging environments due to their high temporal resolution and high dynamic range. However, existing methods convert sparse events into dense frame-like representations for Artificial Neural Networks (ANNs), ignoring event sparsity and incurring high computational cost. Spiking Neural Networks (SNNs) complement event data through discrete spike signals","authors":["Liu, Zuntao","Li, Yaohui","Hu, Chenming","Kong, Delei","Jiang, Junjie","Fang, Zheng"],"url":"https://arxiv.org/abs/2402.10476","arxiv_id":"2402.10476","published":"2025-12-10"},{"title":"Automated Classification of Phonetic Segments in Child Speech Using Raw Ultrasound Imaging","abstract":"Speech sound disorder (SSD) is defined as a persistent impairment in speech sound production leading to reduced speech intelligibility and hindered verbal communication. Early recognition and intervention of children with SSD and timely referral to speech and language therapists (SLTs) for treatment are crucial. Automated detection of speech impairment is regarded as an efficient method for examining and screening la","authors":["Ani, Saja Al","Cleland, Joanne","Zoha, Ahmed"],"url":"https://arxiv.org/abs/2402.17482","arxiv_id":"2402.17482","published":"2025-12-10"},{"title":"BG-HGNN: Toward Efficient Learning for Complex Heterogeneous Graphs","abstract":"Heterogeneous graphs, comprising diverse node and edge types connected through varied relations, are ubiquitous in real-world applications. Message-passing heterogeneous graph neural networks (HGNNs) have emerged as a powerful model class for such data. However, existing HGNNs typically allocate a separate set of learnable weights for each relation type to model relational heterogeneity. Despite their promise, these ","authors":["Su, Junwei","Mao, Lingjun","Da, Zheng","Wu, Chuan"],"url":"https://arxiv.org/abs/2403.08207","arxiv_id":"2403.08207","published":"2025-12-10"},{"title":"Machine learning augmented diagnostic testing to identify sources of variability in test performance","abstract":"Diagnostic tests that can detect pre-clinical or sub-clinical infection, are one of the most powerful tools in our armoury of weapons to control infectious diseases. Considerable effort has been paid to improving diagnostic testing for human, plant and animal diseases, including strategies for targeting the use of diagnostic tests towards individuals who are more likely to be infected. We use machine learning to asse","authors":["Banks, Christopher J.","Sanchez, Aeron","Stewart, Vicki","Bowen, Kate","Doherty, Thomas","Tearne, Oliver"],"url":"https://arxiv.org/abs/2404.03678","arxiv_id":"2404.03678","published":"2025-12-10"},{"title":"Deep generative modelling of canonical ensemble with differentiable thermal properties","abstract":"It is a long-standing challenge to accurately and efficiently compute thermodynamic quantities of many-body systems at thermal equilibrium. The conventional methods, e.g., Markov chain Monte Carlo, require many steps to equilibrate. The recently developed deep learning methods can perform direct sampling, but only work at a single trained temperature point and risk biased sampling. Here, we propose a variational meth","authors":["Li, Shuo-Hui","Zhang, Yao-Wen","Pan, Ding"],"url":"https://arxiv.org/abs/2404.18404","arxiv_id":"2404.18404","published":"2025-12-10"},{"title":"CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale","abstract":"Measuring biodiversity is crucial for understanding ecosystem health. While prior works have developed machine learning models for taxonomic classification of photographic images and DNA separately, in this work, we introduce a multimodal approach combining both, using CLIP-style contrastive learning to align images, barcode DNA, and text-based representations of taxonomic labels in a unified embedding space. This al","authors":["Gong, ZeMing","Wang, Austin T.","Huo, Xiaoliang","Haurum, Joakim Bruslund","Lowe, Scott C.","Taylor, Graham W."],"url":"https://arxiv.org/abs/2405.17537","arxiv_id":"2405.17537","published":"2025-12-10"},{"title":"The Energy Cost of Artificial Intelligence Lifecycle in Communication Networks","abstract":"Artificial Intelligence (AI) is being incorporated in several optimization, scheduling, orchestration as well as in native communication network functions. This paradigm shift results in increased energy consumption, however, quantifying the end-to-end energy consumption of adding intelligence to communication systems remains an open challenge since conventional energy consumption metrics focus on either communicatio","authors":["Chou, Shih-Kai","Hribar, Jernej","Hanžel, Vid","Mohorčič, Mihael","Fortuna, Carolina"],"url":"https://arxiv.org/abs/2408.00540","arxiv_id":"2408.00540","published":"2025-12-10"},{"title":"Explosive neural networks via higher-order interactions in curved statistical manifolds","abstract":"Higher-order interactions underlie complex phenomena in systems such as biological and artificial neural networks, but their study is challenging due to the scarcity of tractable models. By leveraging a generalisation of the maximum entropy principle, we introduce curved neural networks as a class of models with a limited number of parameters that are particularly well-suited for studying higher-order phenomena. Thro","authors":["Aguilera, Miguel","Morales, Pablo A.","Rosas, Fernando E.","Shimazaki, Hideaki"],"url":"https://arxiv.org/abs/2408.02326","arxiv_id":"2408.02326","published":"2025-12-10"}],"history":{"events":[{"year":2021,"text":"A tornado strikes an Amazon warehouse during increased holiday demand, killing six sheltering workers.","url":"https://en.wikipedia.org/wiki/Edwardsville_Amazon_warehouse_collapse"},{"year":1993,"text":"The video game Doom, later considered the \"father\" of the first-person shooter genre, is released.","url":"https://en.wikipedia.org/wiki/Doom_(1993_video_game)"},{"year":1992,"text":"Sheikh Zayed bin Sultan Al Nahyan establishes the Marriage Fund in the United Arab Emirates in response to rising wedding prices.","url":"https://en.wikipedia.org/wiki/Zayed_bin_Sultan_Al_Nahyan"},{"year":1989,"text":"At the first open pro-democracy demonstration in Mongolia, journalist Tsakhiagiin Elbegdorj announced the formation of the Mongolian Democratic Union, which would be instrumental in ending communist rule four months later.","url":"https://en.wikipedia.org/wiki/Tsakhiagiin_Elbegdorj"},{"year":1983,"text":"Raúl Alfonsín (pictured) became the first democratically elected president of Argentina to take office after more than seven years of military dictatorship.","url":"https://en.wikipedia.org/wiki/Ra%C3%BAl_Alfons%C3%ADn"},{"year":1970,"text":"Around the northern Thai village of Mae Salong, remnants of Chinese anti-communist forces now fighting on behalf of the Thai government launched a five-year campaign against local communist insurgents.","url":"https://en.wikipedia.org/wiki/Mae_Salong"},{"year":1967,"text":"Soul and blues singer, Otis Redding, along with members of his back-up group, The Bar-Kays, are killed when their helicopter crashes in Lake Monona in Madison, Wisconsin.","url":"https://en.wikipedia.org/wiki/Otis_Redding"},{"year":1942,"text":"Edward Raczyński of the Polish government-in-exile issued a note that was the first official report on the Holocaust.","url":"https://en.wikipedia.org/wiki/Edward_Bernard_Raczy%C5%84ski"},{"year":1941,"text":"Second World War: The Royal Navy capital ships HMS Prince of Wales and HMS Repulse were sunk by Imperial Japanese Navy torpedo bombers east of Malaya.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1936,"text":"Edward VIII, desiring to marry the American socialite Wallis Simpson against widespread British opposition, signed the instrument of abdication to renounce the throne in favour of his brother George VI.","url":"https://en.wikipedia.org/wiki/Edward_VIII"},{"year":1932,"text":"The conclusion of the Emu War, after the Australian Government ordered the withdrawal of all Australian forces from the conflict.","url":"https://en.wikipedia.org/wiki/Emu_War"},{"year":1911,"text":"Calbraith Perry Rodgers completed the first transcontinental flight across the United States.","url":"https://en.wikipedia.org/wiki/Calbraith_Perry_Rodgers"},{"year":1907,"text":"During the Brown Dog affair, protesters marched through London and clashed with police officers in Trafalgar Square over the existence of a memorial for animals that had been vivisected.","url":"https://en.wikipedia.org/wiki/Brown_Dog_affair"},{"year":1901,"text":"On the fifth anniversary of the death of their founder, Swedish chemist and industrialist Alfred Nobel, the first Nobel Prizes were awarded in Stockholm.","url":"https://en.wikipedia.org/wiki/Alfred_Nobel"},{"year":1890,"text":"The New York World Building, the then-tallest building in the United States at a height of 110 meters, was completed in New York City.","url":"https://en.wikipedia.org/wiki/New_York_World_Building"},{"year":1884,"text":"Adventures of Huckleberry Finn (Finn depicted) by American author Mark Twain was first published in the United Kingdom and Canada, two months earlier than in the US.","url":"https://en.wikipedia.org/wiki/Adventures_of_Huckleberry_Finn"},{"year":1861,"text":"Militia forces led by Nguyễn Trung Trực, an anti-colonial leader in southern Vietnam, sank the French lorcha L'Esperance.","url":"https://en.wikipedia.org/wiki/Nguy%E1%BB%85n_Trung_Tr%E1%BB%B1c"},{"year":1848,"text":"Louis-Napoleon Bonaparte won France's first presidential election, and was elected as the first and only president of the French Second Republic.","url":"https://en.wikipedia.org/wiki/Napoleon_III"}],"births":[{"year":2005,"text":"Ivan Demidov, Russian ice hockey player","url":"https://en.wikipedia.org/wiki/Ivan_Demidov"},{"year":2001,"text":"Coby Mayo, American professional baseball player","url":"https://en.wikipedia.org/wiki/Coby_Mayo"},{"year":2000,"text":"Jeremie Frimpong, Dutch footballer","url":"https://en.wikipedia.org/wiki/Jeremie_Frimpong"},{"year":1999,"text":"Reiss Nelson, English footballer","url":"https://en.wikipedia.org/wiki/Reiss_Nelson"},{"year":1998,"text":"Lucia Bronzetti, Italian tennis player","url":"https://en.wikipedia.org/wiki/Lucia_Bronzetti"},{"year":1997,"text":"Viktoriia Savtsova, Ukrainian Paralympic swimmer","url":"https://en.wikipedia.org/wiki/Viktoriia_Savtsova"},{"year":1996,"text":"Joe Burrow, American football player","url":"https://en.wikipedia.org/wiki/Joe_Burrow"},{"year":1996,"text":"Kang Daniel, South Korean singer and entrepreneur","url":"https://en.wikipedia.org/wiki/Kang_Daniel"}],"deaths":[{"year":2025,"text":"Jeffery Garcia, American stand-up comedian and voice actor (born 1975)","url":"https://en.wikipedia.org/wiki/Jeff_Garcia_(comedian)"},{"year":2024,"text":"Rocky Colavito, American baseball player and sportscaster (born 1933)","url":"https://en.wikipedia.org/wiki/Rocky_Colavito"},{"year":2024,"text":"Michael Cole, American actor (born 1940)","url":"https://en.wikipedia.org/wiki/Michael_Cole_(actor)"},{"year":2024,"text":"Kreskin, American mentalist (born 1935)","url":"https://en.wikipedia.org/wiki/The_Amazing_Kreskin"},{"year":2024,"text":"S. M. Krishna, Indian politician and statesman, Minister of External Affairs, 10th Chief Minister of Karnataka, 19th Governor of Maharashtra (born 1932)","url":"https://en.wikipedia.org/wiki/S._M._Krishna"},{"year":2023,"text":"Julian Carroll, American politician, 54th Governor of Kentucky (born 1931)","url":"https://en.wikipedia.org/wiki/Julian_Carroll"},{"year":2021,"text":"Michael Nesmith, American musician (The Monkees), songwriter, actor, producer, and novelist (born 1942)","url":"https://en.wikipedia.org/wiki/Michael_Nesmith"},{"year":2020,"text":"Tommy \"Tiny\" Lister Jr., American actor and wrestler (born 1958)","url":"https://en.wikipedia.org/wiki/Tommy_Lister_Jr."}]},"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."}