{"date":"2026-08-25","schema_version":1,"captured_at":"2026-08-25T23:15:21.578Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Shelley Fabares","views":465529,"rank":4,"extract":"Michele Ann Marie Fabares was an American actress and singer. 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(2020)","points":148,"comments":231,"url":"https://daily.jstor.org/was-modern-art-really-a-cia-psy-op/","discussion":"https://news.ycombinator.com/item?id=49428080"},{"title":"Credit Card Rewards Became a $9.2B Wealth Transfer","points":145,"comments":280,"url":"https://www.library.hbs.edu/working-knowledge/how-credit-card-rewards-became-multibillion-dollar-wealth-transfer","discussion":"https://news.ycombinator.com/item?id=49432201"},{"title":"AI is hitting entry-level jobs hardest, Stanford study finds","points":133,"comments":153,"url":"https://arstechnica.com/ai/2026/08/ai-is-hitting-entry-level-jobs-hardest-stanford-study-finds/","discussion":"https://news.ycombinator.com/item?id=49435147"},{"title":"Thomson Reuters Launches Its Own Frontier Model","points":132,"comments":54,"url":"https://www.thomsonreuters.com/en/press-releases/2026/august/thomson-reuters-leverages-its-world-class-data-assets-to-launch-its-own-frontier-model","discussion":"https://news.ycombinator.com/item?id=49428318"},{"title":"SiFive's First Server Platform","points":129,"comments":40,"url":"https://chipsandcheese.com/p/sifives-first-server-platform","discussion":"https://news.ycombinator.com/item?id=49428638"},{"title":"Headlong: A microharness for persistent agents","points":118,"comments":53,"url":"https://www.laude.org/updates/headlong-a-microharness-for-persistent-agents","discussion":"https://news.ycombinator.com/item?id=49428882"},{"title":"France's tax agency got hacked (in French)","points":116,"comments":53,"url":"https://www.cybernetica.fr/piratage-des-impots-comment-en-est-on-arrive-la/","discussion":"https://news.ycombinator.com/item?id=49433064"}],"research":[{"title":"A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform","abstract":"Kiva is an online non-profit crowdsouring microfinance platform that raises funds for the poor in the third world. The borrowers on Kiva are small business owners and individuals in urgent need of money. To raise funds as fast as possible, they have the option to form groups and post loan requests in the name of their groups. While it is generally believed that group loans pose less risk for investors than individual","authors":["Pham, Thai T.","Shen, Yuanyuan"],"url":"https://arxiv.org/abs/1706.02795","arxiv_id":"1706.02795","published":"2026-08-25"},{"title":"Measuring the intelligence of an idealized mechanical knowing agent","abstract":"We define a notion of the intelligence level of an idealized mechanical knowing agent. This is motivated by efforts within artificial intelligence research to define real-number intelligence levels of complicated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent t","authors":["Alexander, Samuel Allen"],"url":"https://arxiv.org/abs/1912.09571","arxiv_id":"1912.09571","published":"2026-08-25"},{"title":"Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure","abstract":"In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard's idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second, one specific (somewhat arbitrary) method for measuring said growt","authors":["Alexander, Samuel","Hibbard, Bill"],"url":"https://arxiv.org/abs/2101.12047","arxiv_id":"2101.12047","published":"2026-08-25"},{"title":"Mining Artifacts in Mycelium SEM Micrographs","abstract":"Mycelium is a promising biomaterial based on fungal mycelium, a highly porous, nanofibrous structure. Scanning electron micrographs are used to characterize its network, but the currently available tools for nanofibrous microstructures do not contemplate the particularities of biomaterials. The adoption of a software for artificial nanofibrous in mycelium characterization adds the uncertainty of imaging artifact form","authors":["de Almeida, Thaicia Stona"],"url":"https://arxiv.org/abs/2103.07573","arxiv_id":"2103.07573","published":"2026-08-25"},{"title":"Unique sparse decomposition of low rank matrices","abstract":"The problem of finding the unique low dimensional decomposition of a given matrix has been a fundamental and recurrent problem in many areas. In this paper, we study the problem of seeking a unique decomposition of a low rank matrix $Y\\in \\mathbb{R}^{p\\times n}$ that admits a sparse representation. Specifically, we consider $Y = A X\\in \\mathbb{R}^{p\\times n}$ where the matrix $A\\in \\mathbb{R}^{p\\times r}$ has full co","authors":["Jin, Dian","Bing, Xin","Zhang, Yuqian"],"url":"https://arxiv.org/abs/2106.07736","arxiv_id":"2106.07736","published":"2026-08-25"},{"title":"Arbitrarily Shaped Scene Text Detection: A Decade of Advances and Systematic Analysis","abstract":"Scene text detection has become an important research area in computer vision. However, dynamic changes in scenes and the complex diversity of text appearances make accurate scene text detection highly challenging. Although numerous arbitrary-shaped scene text detection methods have been proposed in recent years, with most claiming state-of-the-art performance, these performance comparisons are often unfair due to va","authors":["Dai, Pengwen","He, Feiyang","Li, Chaolang","Qin, Xugong","Ren, Wenqi","Cao, Xiaochun"],"url":"https://arxiv.org/abs/2107.11800","arxiv_id":"2107.11800","published":"2026-08-25"},{"title":"Machine Learning Classification and Portfolio Construction: Does the Loss Function Matter?","abstract":"Classification outperforms regression across matched machine learning models in portfolio construction. A stacking ensemble of gradient boosted tree, random forest, and neural network yields a value-weighted annualized Sharpe ratio of 1.83 for classification and 1.11 for regression. This outperformance persists in multiclass settings, across subsamples, and after transaction costs. Spanning tests show that classifica","authors":["Bai, Yang","Pukthuanthong, Kuntara"],"url":"https://arxiv.org/abs/2108.02283","arxiv_id":"2108.02283","published":"2026-08-25"},{"title":"Reward-Punishment Symmetric Universal Intelligence","abstract":"Can an agent's intelligence level be negative? We extend the Legg-Hutter agent-environment framework to include punishments and argue for an affirmative answer to that question. We show that if the background encodings and Universal Turing Machine (UTM) admit certain Kolmogorov complexity symmetries, then the resulting Legg-Hutter intelligence measure is symmetric about the origin. In particular, this implies rew","authors":["Alexander, Samuel Allen","Hutter, Marcus"],"url":"https://arxiv.org/abs/2110.02450","arxiv_id":"2110.02450","published":"2026-08-25"},{"title":"Extending Environments To Measure Self-Reflection In Reinforcement Learning","abstract":"We consider an extended notion of reinforcement learning in which the environment can simulate the agent and base its outputs on the agent's hypothetical behavior. Since good performance usually requires paying attention to whatever things the environment's outputs are based on, we argue that for an agent to achieve on-average good performance across many such extended environments, it is necessary for the ag","authors":["Alexander, Samuel Allen","Castaneda, Michael","Compher, Kevin","Martinez, Oscar"],"url":"https://arxiv.org/abs/2110.06890","arxiv_id":"2110.06890","published":"2026-08-25"},{"title":"Universal Agent Mixtures and the Geometry of Intelligence","abstract":"Inspired by recent progress in multi-agent Reinforcement Learning (RL), in this work we examine the collective intelligent behaviour of theoretical universal agents by introducing a weighted mixture operation. Given a weighted set of agents, their weighted mixture is a new agent whose expected total reward in any environment is the corresponding weighted average of the original agents' expected total rewards in t","authors":["Alexander, Samuel Allen","Quarel, David","Du, Len","Hutter, Marcus"],"url":"https://arxiv.org/abs/2302.06083","arxiv_id":"2302.06083","published":"2026-08-25"},{"title":"Neuro-Causal Factor Analysis","abstract":"Factor analysis (FA) is a statistical method for explaining how mutually dependent observed variables can be represented in terms of mutually independent latent factors, and it is widely used in the psychological, biological, and physical sciences. We revisit this classic method from the perspective of recent advances in causal structure learning and deep generative models, introducing a framework for Neuro-Causal Fa","authors":["Markham, Alex","Liu, Mingyu","Aragam, Bryon","Solus, Liam"],"url":"https://arxiv.org/abs/2305.19802","arxiv_id":"2305.19802","published":"2026-08-25"},{"title":"Residual-based attention in physics-informed neural networks","abstract":"Driven by the need for more efficient and seamless integration of physical models and data, physics-informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains a challenge. In this work, we propose an efficient, gradient-less weighting scheme for PINNs that accelerates the convergence of dynamic or static systems. This sim","authors":["Anagnostopoulos, Sokratis J.","Toscano, Juan Diego","Stergiopulos, Nikolaos","Karniadakis, George Em"],"url":"https://arxiv.org/abs/2307.00379","arxiv_id":"2307.00379","published":"2026-08-25"},{"title":"Learning to Select and Rank from Choice-Based Feedback: A Simple Nested Approach","abstract":"We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially displays a set of items to a population of customers and collects their choices as feedback. The only information available about the underlying choice model is that the choice probabilities are consistent with some unknown true strict ranking over the items. The objective ","authors":["Yang, Junwen","Feng, Yifan"],"url":"https://arxiv.org/abs/2307.09295","arxiv_id":"2307.09295","published":"2026-08-25"},{"title":"Evaluating the Efficacy of LLMs to Emulate Realistic Human Personalities","abstract":"To enhance immersion and engagement in video games, the design of Affective Non-Player Characters (ANPCs) is a key focus for researchers and practitioners. Affective Computing frameworks improve Non-player characters (NPC) by providing personalities, emotions, and social relations. Large Language Models (LLMs) bring the promise to dynamically enhance character design when coupled with these frameworks, but further re","authors":["Klinkert, Lawrence J.","Buongiorno, Stephanie","Clark, Corey"],"url":"https://arxiv.org/abs/2402.14879","arxiv_id":"2402.14879","published":"2026-08-25"},{"title":"Approximating invariant functions with the sorting trick is theoretically justified","abstract":"Many machine learning models leverage group invariance which is enjoyed with a wide-range of applications. For exploiting an invariance structure, one common approach is known as \\emph{frame averaging}. One popular example of frame averaging is the \\emph{group averaging}, where the entire group is used to symmetrize a function. Another example is the \\emph{canonicalization}, where a frame at each point consists of a ","authors":["Chaimanowong, Wee","Zhu, Ying"],"url":"https://arxiv.org/abs/2403.01671","arxiv_id":"2403.01671","published":"2026-08-25"},{"title":"A Survey on Human-AI Collaboration with Large Foundation Models","abstract":"As the capabilities of artificial intelligence (AI) continue to expand rapidly, Human-AI (HAI) Collaboration, combining human intellect and AI systems, has become pivotal for advancing problem-solving and decision-making processes. The advent of Large Foundation Models (LFMs) has greatly expanded its potential, offering unprecedented capabilities by leveraging vast amounts of data to understand and predict complex pa","authors":["Vats, Vanshika","Nizam, Marzia Binta","Liu, Minghao","Wang, Ziyuan","Ho, Richard","Prasad, Mohnish Sai"],"url":"https://arxiv.org/abs/2403.04931","arxiv_id":"2403.04931","published":"2026-08-25"},{"title":"Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures","abstract":"Deep clustering partitions complex high-dimensional data using deep neural networks for clustering. It involves projecting data into lower-dimensional embeddings before partitioning, which embarks unique evaluation challenges. Traditional clustering validation measures, designed for low-dimensional spaces, are problematic for deep clustering for two reasons: 1) the curse of dimensionality when applied to the high-dim","authors":["Wang, Zeya","Ye, Chenglong"],"url":"https://arxiv.org/abs/2403.14830","arxiv_id":"2403.14830","published":"2026-08-25"},{"title":"Guessing human intentions to avoid dangerous situations in caregiving robots","abstract":"For robots to interact socially, they must interpret human intentions and anticipate their potential outcomes accurately. This is particularly important for social robots designed for human care, which may face potentially dangerous situations for people, such as unseen obstacles in their way, that should be avoided. This paper explores the Artificial Theory of Mind (ATM) approach to inferring and interpreting human ","authors":["Zapata, Noé","Pérez, Gerardo","Bonilla, Lucas","Núñez, Pedro","Bachiller, Pilar","Bustos, Pablo"],"url":"https://arxiv.org/abs/2403.16291","arxiv_id":"2403.16291","published":"2026-08-25"},{"title":"Learning in PINNs: Phase transition, diffusion equilibrium, and generalization","abstract":"We investigate the learning dynamics of fully-connected neural networks through the lens of the neural gradient signal-to-noise ratio (SNR), examining the behavior of first-order optimizers in non-convex objectives. Interpreting the drift/diffusion phases as proposed in the information bottleneck theory, we identify a third phase termed "diffusion equilibrium" (DE), a stable training phase characterized by hi","authors":["Anagnostopoulos, Sokratis J.","Toscano, Juan Diego","Stergiopulos, Nikolaos","Karniadakis, George Em"],"url":"https://arxiv.org/abs/2403.18494","arxiv_id":"2403.18494","published":"2026-08-25"},{"title":"Soft Label PU Learning","abstract":"PU learning refers to the classification problem in which only part of positive samples are labeled. Existing PU learning methods treat unlabeled samples equally. However, in many real tasks, from common sense or domain knowledge, some unlabeled samples are more likely to be positive than others. In this paper, we propose soft label PU learning, in which unlabeled data are assigned soft labels according to their prob","authors":["Lei, Yong","Zhao, Puning","Deng, Jintao","Cheng, Xu"],"url":"https://arxiv.org/abs/2405.01990","arxiv_id":"2405.01990","published":"2026-08-25"},{"title":"On the Expressive Power of Sparse Geometric MPNNs","abstract":"Motivated by applications in chemistry and other sciences, we study the expressive power of message-passing neural networks for geometric graphs, whose node features correspond to 3-dimensional positions. Recent work has shown that such models can separate generic pairs of non-isomorphic geometric graphs, though they may fail to separate some rare and complicated instances. However, these results assume a fully conne","authors":["Sverdlov, Yonatan","Dym, Nadav"],"url":"https://arxiv.org/abs/2407.02025","arxiv_id":"2407.02025","published":"2026-08-25"},{"title":"Image-Conditional Diffusion Transformer for Underwater Image Enhancement","abstract":"Underwater image enhancement (UIE) has attracted much attention owing to its importance for underwater operation and marine engineering. Motivated by the recent advance in generative models, we propose a novel UIE method based on image-conditional diffusion transformer (ICDT). Our method takes the degraded underwater image as the conditional input and converts it into latent space where ICDT is applied. ICDT replaces","authors":["Nie, Xingyang","Zhang, Caoliang","Zhai, Xiaoyu","Qu, Fengzhong","Wang, Biao","Ge, Huilin"],"url":"https://arxiv.org/abs/2407.05389","arxiv_id":"2407.05389","published":"2026-08-25"},{"title":"Exploring learning environments for label\\-efficient cancer diagnosis","abstract":"Despite significant research efforts and advancements, cancer remains a leading cause of mortality. Early cancer prediction has become a crucial focus in cancer research to streamline patient care and improve treatment outcomes. Manual tumor detection by histopathologists can be time consuming, prompting the need for computerized methods to expedite treatment planning. Traditional approaches to tumor detection rely o","authors":["Rani, Samta","Ahmad, Tanvir","Masood, Sarfaraz","Saxena, Chandni"],"url":"https://arxiv.org/abs/2408.07988","arxiv_id":"2408.07988","published":"2026-08-25"},{"title":"SIG: A Synthetic Identity Generation Pipeline for Generating Evaluation Datasets for Face Recognition","abstract":"As Artificial Intelligence applications expand, the evaluation of models faces heightened scrutiny. Ensuring public readiness requires evaluation datasets, which differ from training data by being disjoint and ethically sourced in compliance with privacy regulations. The performance and fairness of face recognition systems depend significantly on the quality and representativeness of these evaluation datasets. This d","authors":["Nzalasse, Kassi","Raj, Rishav","Laird, Eli","Clark, Corey"],"url":"https://arxiv.org/abs/2409.08345","arxiv_id":"2409.08345","published":"2026-08-25"},{"title":"Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation","abstract":"Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in medicine have shown potential in processing multimodal information, offering a unified solution for various radiology tasks. However, existing studies either pre-trained VL models on natural data or did not fully integrate vision-language architecture and pretraining, often","authors":["Liu, Xiaohong","Yang, Guoxing","Luo, Yulin","Mao, Jiaji","Zhang, Xiang","Wang, Haibo"],"url":"https://arxiv.org/abs/2409.16183","arxiv_id":"2409.16183","published":"2026-08-25"}],"history":{"events":[{"year":2012,"text":"The NASA space probe Voyager 1 became the first man-made object to enter interstellar space.","url":"https://en.wikipedia.org/wiki/NASA"},{"year":2012,"text":"The skeleton of King Richard III of England was discovered under a car park in Leicester.","url":"https://en.wikipedia.org/wiki/Richard_III_of_England"},{"year":2011,"text":"Mexican drug war: Fifty-two people were killed in an arson attack at a casino in Monterrey, Mexico.","url":"https://en.wikipedia.org/wiki/Mexican_drug_war"},{"year":2001,"text":"American singer Aaliyah and several members of her record company were killed when their overloaded 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