{"date":"2026-07-24","schema_version":1,"captured_at":"2026-08-25T23:17:17.344Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":15},"attention":[{"title":"The Odyssey (2026 film)","views":582054,"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. An adaptation of Homer's ancient Greek epic poem the Odyssey, it stars an ensemble cast including Matt Damon, Tom Holland, Anne","url":"https://en.wikipedia.org/wiki/The_Odyssey_(2026_film)","thumb":"https://upload.wikimedia.org/wikipedia/en/9/90/The_Odyssey_%282026_film%29_poster.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail_unscaled"},{"title":"Odyssey","views":200887,"rank":5,"extract":"The Odyssey is one of two major epics of ancient Greek literature attributed to Homer. 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In the past study, the algorithm only controls the forward direction about quadcopter. In this letter, we use two functions to control quadcopter. One is quadcopter navigating function. It is based on calculating coordination point and find the straight path to the goal. The other function is colli","authors":["Wu, Tung-Cheng","Tseng, Shau-Yin","Lai, Chin-Feng","Ho, Chia-Yu","Lai, Ying-Hsun"],"url":"https://arxiv.org/abs/1811.04584","arxiv_id":"1811.04584","published":"2026-07-24"},{"title":"BoXHED2.0: Scalable boosting of dynamic survival analysis","abstract":"Modern applications of survival analysis increasingly involve time-dependent covariates. The Python package BoXHED2.0 is a tree-boosted hazard estimator that is fully nonparametric, and is applicable to survival settings far more general than right-censoring, including recurring events and competing risks. BoXHED2.0 is also scalable to the point of being on the same order of speed as parametric boosted survival model","authors":["Pakbin, Arash","Wang, Xiaochen","Mortazavi, Bobak J.","Lee, Donald K. K."],"url":"https://arxiv.org/abs/2103.12591","arxiv_id":"2103.12591","published":"2026-07-24"},{"title":"The optimality of word lengths. Theoretical foundations and an empirical study","abstract":"Zipf's law of abbreviation, namely the tendency of more frequent words to be shorter, has been viewed as a manifestation of compression, i.e. the minimization of the length of forms -- a universal principle of natural communication. Although the claim that languages are optimized has become trendy, attempts to measure the degree of optimization of languages have been rather scarce. Here we present two optimality ","authors":["Petrini, Sonia","Casas-i-Muñoz, Antoni","Cluet-i-Martinell, Jordi","Wang, Mengxue","Bentz, Christian","Ferrer-i-Cancho, Ramon"],"url":"https://arxiv.org/abs/2208.10384","arxiv_id":"2208.10384","published":"2026-07-24"},{"title":"Understanding Addition and Subtraction in Transformers","abstract":"We use integer addition and subtraction as a controlled, exactly-solvable testbed for what can be said with confidence about the algorithm a low-loss transformer implements - logically and mechanically. We train small transformers (2-3 layers) from scratch, find the edge cases they fail (long carry and borrow cascades), and enrich the training data with them; most resulting models reach >$99.999% accuracy on 5-15 ","authors":["Quirke, Philip","Neo, Clement","Barez, Fazl"],"url":"https://arxiv.org/abs/2402.02619","arxiv_id":"2402.02619","published":"2026-07-24"},{"title":"Training Fast Robot Policies with Slow Foundation Models","abstract":"Continuous robotic control requires policies that execute with low latency and modest computational cost during deployment. Foundation models provide strong semantic and visual reasoning, but repeatedly querying a large model throughout deployment incurs substantial inference latency and compute requirements. Language-to-Reward (L2R) methods avoid this deployment-time cost by using large language models (LLMs) to syn","authors":["Singh, Utsav","Bhattacharyya, Pramit","Namboodiri, Vinay P.","Bedi, Amrit Singh"],"url":"https://arxiv.org/abs/2406.05881","arxiv_id":"2406.05881","published":"2026-07-24"},{"title":"Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning","abstract":"We study a structured class of Markov Decision Processes, known as Exo-MDPs, in which the state space is partitioned into exogenous and endogenous components. Exogenous states evolve stochastically, independent of the agent's actions, while endogenous states evolve deterministically based on both state components and actions. Exo-MDPs capture many operations research settings, including inventory control, resourc","authors":["Wan, Jia","Sinclair, Sean R.","Shah, Devavrat","Wainwright, Martin J."],"url":"https://arxiv.org/abs/2409.14557","arxiv_id":"2409.14557","published":"2026-07-24"},{"title":"Evaluation and Prognostic Validation of Deep Regression Models for WSI-Based Gene-Expression Prediction","abstract":"Gene-expression profiling is widely used in research and central to many areas of precision oncology, but remains costly and not universally accessible. Recent advances in computational pathology enable prediction of transcriptomic profiles directly from hematoxylin and eosin (H&E)-stained whole-slide images (WSIs), although optimal modeling strategies and clinical relevance remain unclear. In this study, we syst","authors":["Gustafsson, Fredrik K.","Boissin, Constance","Vallon-Christersson, Johan","Rantalainen, Mattias"],"url":"https://arxiv.org/abs/2410.00945","arxiv_id":"2410.00945","published":"2026-07-24"},{"title":"Exactly Minimax-Optimal Locally Differentially Private Sampling","abstract":"The sampling problem under local differential privacy has recently been studied with potential applications to generative models, but a fundamental analysis of its privacy-utility trade-off (PUT) remains incomplete. In this work, we define the fundamental PUT of private sampling in the minimax sense, using the f-divergence between original and sampling distributions as the utility measure. We characterize the exact P","authors":["Park, Hyun-Young","Asoodeh, Shahab","Lee, Si-Hyeon"],"url":"https://arxiv.org/abs/2410.22699","arxiv_id":"2410.22699","published":"2026-07-24"},{"title":"Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis","abstract":"This scoping review examines the relationship between Generative AI (GenAI) and agency in education, analyzing the literature available through the lens of Critical Digital Pedagogy. Following PRISMA-ScR guidelines, we collected 10 studies from academic databases focusing on both learner and teacher agency in GenAI-enabled environments. We conducted an AI-supported hybrid thematic analysis that revealed three key the","authors":["Roe, Jasper","Perkins, Mike"],"url":"https://arxiv.org/abs/2411.00631","arxiv_id":"2411.00631","published":"2026-07-24"},{"title":"Classifier-pruned Bayesian optimization for particle accelerator tuning: Exploring temporally structured manifold of 6D beam phase space","abstract":"Complex dynamical systems, such as particle accelerators, often require intricate and time-consuming tuning procedures to achieve optimal performance. In many cases, these procedures must also estimate the optimal system parameters governing the dynamics of a spatiotemporal beam, making the task a high-dimensional optimization problem. To address this, we propose a Classifier-pruned Bayesian Optimization-based Latent","authors":["Rautela, Mahindra","Williams, Alan","Scheinker, Alexander"],"url":"https://arxiv.org/abs/2412.01748","arxiv_id":"2412.01748","published":"2026-07-24"},{"title":"How Robust Is Homogeneity Bias in LLMs? Evidence Across Models, Decoding Settings, and Identity Signals","abstract":"Large language models (LLMs) reproduce homogeneity bias -- the tendency to portray marginalized groups as more internally similar than dominant groups -- but whether this bias generalizes across models, is stable under different inference settings, or depends on how group identity is signaled remains unstudied. We map homogeneity bias across seven open-weight instruction-tuned LLMs (7-20B parameters), a 5x5 temperatu","authors":["Lee, Messi H. J."],"url":"https://arxiv.org/abs/2501.02211","arxiv_id":"2501.02211","published":"2026-07-24"},{"title":"A Counterfactual Cause in Situation Calculus","abstract":"Perhaps the most popular modern formulation of actual causality is the HP account by Halpern and Pearl. Recent advancement has focused on extension of HP account to lift its limited expressiveness, in particular, Batusov and Soutchanski proposed a notion of actual achievement cause in the situation calculus, a rich first-order formalism of actions and changes. Among other things, the first-order nature allows for det","authors":["Liu, Daxin","Belle, Vaishak"],"url":"https://arxiv.org/abs/2501.06857","arxiv_id":"2501.06857","published":"2026-07-24"},{"title":"Statistical Inference for Generative Model Comparison","abstract":"Generative models have achieved remarkable success across a range of applications, yet their evaluation still lacks principled uncertainty quantification. In this paper, we develop a method for comparing how close different generative models are to the underlying distribution of test samples. Particularly, our approach employs the Kullback-Leibler (KL) divergence to measure the distance between a generative model and","authors":["Gao, Zijun","Sun, Yan","Su, Han"],"url":"https://arxiv.org/abs/2501.18897","arxiv_id":"2501.18897","published":"2026-07-24"},{"title":"Token-Level Entropy Reveals Demographic Disparities in Large Language Models","abstract":"A name alone measurably reshapes a language model's next-token distribution before a single token is sampled. We measure full-vocabulary Shannon entropy of the next-token distribution across six open-weight model families on 5,760 sentence-completion prompts in which race and gender are signaled only by a first name. Black-associated names co-occur with higher first-token entropy and more diverse continuations th","authors":["Lee, Messi H. J."],"url":"https://arxiv.org/abs/2501.19337","arxiv_id":"2501.19337","published":"2026-07-24"},{"title":"Decentralized Planning Using Probabilistic Hyperproperties","abstract":"Multi-agent planning under stochastic dynamics is usually formalised using decentralized (partially observable) Markov decision processes ( MDPs) and reachability or expected reward specifications. In this paper, we propose a different approach: we use an MDP describing how a single agent operates in an environment and probabilistic hyperproperties to capture desired temporal objectives for a set of decentralized age","authors":["Pontiggia, Francesco","Macák, Filip","Andriushchenko, Roman","Chiari, Michele","Češka, Milan"],"url":"https://arxiv.org/abs/2502.13621","arxiv_id":"2502.13621","published":"2026-07-24"},{"title":"SoccerSynth Field: enhancing field detection with synthetic data from virtual soccer simulator","abstract":"Field detection in team sports is an essential task in sports video analysis. However, collecting large-scale and diverse real-world datasets for training detection models is often cost and time-consuming. Synthetic datasets, which allow controlled variability in lighting, textures, and camera angles, will be a promising alternative for addressing these problems. This study addresses the challenges of high costs and ","authors":["Qin, HaoBin","Fang, Jiale","Fujii, Keisuke"],"url":"https://arxiv.org/abs/2503.13969","arxiv_id":"2503.13969","published":"2026-07-24"},{"title":"Dominated Actions in Imperfect-Information Games","abstract":"Dominance is a fundamental concept in game theory. In normal-form games dominated strategies can be identified in polynomial time. As a consequence, iterative removal of dominated strategies can be performed efficiently as a preprocessing step for reducing the size of a game before computing a Nash equilibrium. For imperfect-information games in extensive form, we could convert the game to normal form and then iterat","authors":["Ganzfried, Sam"],"url":"https://arxiv.org/abs/2504.09716","arxiv_id":"2504.09716","published":"2026-07-24"},{"title":"Semantics at an Angle: When Cosine Similarity Works Until It Doesn't","abstract":"Cosine similarity is a standard comparison rule for learned representations in information retrieval, natural language processing, computer vision, and multimodal learning. Its popularity is well founded: it removes positive radial scale, is computationally convenient, and often matches objectives that train normalized embeddings. These same properties also delimit what cosine can express. Normalization discards radi","authors":["You, Kisung"],"url":"https://arxiv.org/abs/2504.16318","arxiv_id":"2504.16318","published":"2026-07-24"},{"title":"Do Large Language Models know who did what to whom?","abstract":"Large Language Models (LLMs) are commonly criticized for not understanding language. However, many critiques focus on cognitive abilities that, in humans, are distinct from language processing. Here, we instead study a kind of understanding tightly linked to language: inferring who did what to whom (thematic roles) in a sentence. Does the central training objective of LLMs-word prediction-result in sentence represent","authors":["Denning, Joseph M.","Guo, Xiaohan Hannah","Snefjella, Bryor","Blank, Idan A."],"url":"https://arxiv.org/abs/2504.16884","arxiv_id":"2504.16884","published":"2026-07-24"},{"title":"PreMoE: Proactive Inference for Efficient Mixture-of-Experts","abstract":"Mixture-of-Experts (MoE) models offer dynamic computation, but are typically deployed as static full-capacity models, missing opportunities for deployment-specific specialization. We introduce PreMoE, a training-free framework that proactively compiles sparse MoE variants for targeted deployment scenarios. At its core is Predicted Expert Utility (PEU), a robust metric for estimating expert importance from router logi","authors":["Pei, Zehua","Zhang, Ying","Zhen, Hui-Ling","Yuan, Tao","Yu, Xianzhi","Dong, Zhenhua"],"url":"https://arxiv.org/abs/2505.17639","arxiv_id":"2505.17639","published":"2026-07-24"},{"title":"Concept Concentration for Faithful Representation Intervention","abstract":"Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to elicit the aligned and expected behaviors. Despite the empirical success, it has never been examined whether one could localize the faithful concepts for intervention. In this work, we explore the question in safety alignment. If the interventions are faithful, the interve","authors":["Yang, Hongzheng","Chen, Yongqiang","Qin, Zeyu","Liu, Tongliang","Xiao, Chaowei","Zhang, Kun"],"url":"https://arxiv.org/abs/2505.18672","arxiv_id":"2505.18672","published":"2026-07-24"},{"title":"SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows","abstract":"Deep generative models have recently garnered significant attention across various fields, from physics to chemistry, where sampling from unnormalized Boltzmann-like distributions represents a fundamental challenge. In particular, autoregressive models and normalizing flows have become prominent due to their appealing ability to yield closed-form probability densities. Moreover, it is well-established that incorporat","authors":["Kreit, Janik","Schuh, Dominic","Nicoli, Kim A.","Funcke, Lena"],"url":"https://arxiv.org/abs/2505.19619","arxiv_id":"2505.19619","published":"2026-07-24"},{"title":"Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective","abstract":"Diffusion models have achieved tremendous success in image generation, but they also raise significant concerns regarding privacy and copyright issues. Membership Inference Attacks (MIAs) are designed to ascertain whether specific data was utilized during a model's training phase. As current MIAs for diffusion models typically exploit the model's image prediction ability, we formalize them into a unified gene","authors":["Lian, Puwei","Cai, Yujun","Li, Songze","Bao, Bingkun"],"url":"https://arxiv.org/abs/2505.20955","arxiv_id":"2505.20955","published":"2026-07-24"},{"title":"Gibbs randomness-compression proposition","abstract":"A proposition that connects randomness and compression is put forward via Gibbs entropy over set of measurement vectors associated with a lossy compression process. In building this connection, we use a performance of a learning task as a probe of compression in iterative compress-train cycles. This can be thought as iterative coarse-graining from statistical mechanics perspective using thermodynamic efficiency as a ","authors":["Süzen, M"],"url":"https://arxiv.org/abs/2505.23869","arxiv_id":"2505.23869","published":"2026-07-24"},{"title":"Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions","abstract":"Federated Learning (FL) enables privacy-preserving collaborative model training, but its effectiveness is often limited by client data heterogeneity. We introduce a client-selection algorithm that (i) dynamically forms nonoverlapping coalitions of clients based on asymptotic agreement and (ii) selects one representative from each coalition to minimize the variance of model updates. Our approach is inspired by social-","authors":["Licciardi, Alessandro","Raineri, Roberta","Proskurnikov, Anton","Rondoni, Lamberto","Zino, Lorenzo"],"url":"https://arxiv.org/abs/2506.02897","arxiv_id":"2506.02897","published":"2026-07-24"}],"history":{"events":[{"year":2019,"text":"Boris Johnson became Prime Minister of the United Kingdom after winning the Conservative Party leadership election.","url":"https://en.wikipedia.org/wiki/Boris_Johnson"},{"year":2014,"text":"Air Algérie Flight 5017 disappeared from radar shortly after take-off from Ouagadougou, Burkina Faso; its wreckage was found the following day in Mali with no survivors.","url":"https://en.wikipedia.org/wiki/Air_Alg%C3%A9rie_Flight_5017"},{"year":1998,"text":"A gunman entered the United States Capitol and opened fire, killing two police officers.","url":"https://en.wikipedia.org/wiki/United_States_Capitol"},{"year":1987,"text":"Iran–Iraq War: In opposition to the American plan to protect Kuwaiti tankers, Iran laid mines and damaged the SS Bridgeton, resulting in a propaganda victory for Iran.","url":"https://en.wikipedia.org/wiki/Iran%E2%80%93Iraq_War"},{"year":1980,"text":"The Australian swimming team, nicknamed the Quietly Confident Quartet, won the men's 4 × 100 metre medley relay at the Moscow Olympics, the only time that the United States, which boycotted the games, has not won the event at the Olympics.","url":"https://en.wikipedia.org/wiki/Quietly_Confident_Quartet"},{"year":1974,"text":"The Metapolitefsi period began with Konstantinos Karamanlis (pictured) taking office as Prime Minister of Greece after the collapse of the military junta.","url":"https://en.wikipedia.org/wiki/Metapolitefsi"},{"year":1967,"text":"During a speech in Montreal, French president Charles de Gaulle (pictured) declared \"Long live free Quebec!\", a statement that was interpreted as support for Quebec independence from Canada.","url":"https://en.wikipedia.org/wiki/Montreal"},{"year":1959,"text":"Soviet premier Nikita Khrushchev and U.S. vice president Richard Nixon held an impromptu debate (pictured) at the opening of the American National Exhibition at Sokolniki Park in Moscow.","url":"https://en.wikipedia.org/wiki/Nikita_Khrushchev"},{"year":1948,"text":"Australia set a world record for the highest successful run-chase in Test cricket history during the Fourth Test of the Ashes series against England.","url":"https://en.wikipedia.org/wiki/Australia_national_cricket_team"},{"year":1923,"text":"The Treaty of Lausanne was signed to settle part of the partition of the Ottoman Empire, establishing the boundaries of Greece, Bulgaria and Turkey.","url":"https://en.wikipedia.org/wiki/Treaty_of_Lausanne"},{"year":1920,"text":"Franco-Syrian War: At the Battle of Maysalun, forces of the Arab Kingdom of Syria were defeated by a French army moving to occupy the territory allocated to them by the San Remo conference.","url":"https://en.wikipedia.org/wiki/Franco-Syrian_War"},{"year":1910,"text":"Ottoman forces captured the city of Shkodër, ending the Albanian revolt of 1910 (depicted).","url":"https://en.wikipedia.org/wiki/Ottoman_Empire"},{"year":1847,"text":"Brigham Young led the first group of Mormon pioneers into the Salt Lake Valley of Utah, at the time a part of Mexico.","url":"https://en.wikipedia.org/wiki/Brigham_Young"},{"year":1567,"text":"Mary, Queen of Scots, was forced to abdicate in favour of her one-year-old son, who became James VI.","url":"https://en.wikipedia.org/wiki/Mary%2C_Queen_of_Scots"},{"year":1411,"text":"Scottish clansmen led by Donald of Islay, Lord of the Isles, and Alexander Stewart, Earl of Mar, fought the Battle of Harlaw near Inverurie, Scotland.","url":"https://en.wikipedia.org/wiki/Scottish_clan"}],"births":[{"year":2001,"text":"Ryan Johnson, American ice hockey player","url":"https://en.wikipedia.org/wiki/Ryan_Johnson_(ice_hockey%2C_born_2001)"},{"year":2001,"text":"Drake London, American football player","url":"https://en.wikipedia.org/wiki/Drake_London"},{"year":1998,"text":"Bindi Irwin, Australian conservationist, zookeeper, and actress","url":"https://en.wikipedia.org/wiki/Bindi_Irwin"},{"year":1998,"text":"Sophie Wotschke, Austrian politician","url":"https://en.wikipedia.org/wiki/Sophie_Wotschke"},{"year":1998,"text":"Cailee Spaeny, American actress","url":"https://en.wikipedia.org/wiki/Cailee_Spaeny"},{"year":1996,"text":"Joe Mixon, American football player","url":"https://en.wikipedia.org/wiki/Joe_Mixon"},{"year":1995,"text":"Valentine Holmes, Australian rugby league player","url":"https://en.wikipedia.org/wiki/Valentine_Holmes"},{"year":1995,"text":"Kyle Kuzma, American basketball player","url":"https://en.wikipedia.org/wiki/Kyle_Kuzma"}],"deaths":[{"year":2025,"text":"Hulk Hogan, American professional wrestler and actor (born 1953)","url":"https://en.wikipedia.org/wiki/Hulk_Hogan"},{"year":2025,"text":"Cleo Laine, English singer and actress (born 1927)","url":"https://en.wikipedia.org/wiki/Cleo_Laine"},{"year":2024,"text":"Shafin Ahmed, Bangladeshi bassist and singer-songwriter (born 1961)","url":"https://en.wikipedia.org/wiki/Shafin_Ahmed"},{"year":2024,"text":"Hamzah Haz, Indonesian journalist and politician, 9th Vice President of Indonesia (born 1940)","url":"https://en.wikipedia.org/wiki/Hamzah_Haz"},{"year":2024,"text":"Dmytro Kiva, Ukrainian engineer and designer (born 1942)","url":"https://en.wikipedia.org/wiki/Dmytro_Kiva"},{"year":2023,"text":"George Alagiah, BBC News journalist and broadcaster (born 1955)","url":"https://en.wikipedia.org/wiki/George_Alagiah"},{"year":2023,"text":"Trevor Francis, Britain's first \"£1 million football player\" (born 1954)","url":"https://en.wikipedia.org/wiki/Trevor_Francis"},{"year":2022,"text":"David Warner, English actor (born 1941)","url":"https://en.wikipedia.org/wiki/David_Warner_(actor)"}]},"sources":[{"id":"attention","name":"Wikipedia 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Every item links to its source."}