{"date":"2026-07-15","schema_version":1,"captured_at":"2026-08-25T23:16:15.879Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":11},"attention":[{"title":"Sam Neill","views":622557,"rank":4,"extract":"Sir Nigel John Dermot \"Sam\" Neill was a New Zealand actor. Known as a leading man in film and television, he received nominations for three Primetime Emmy Awards and two Golden Globe Awards. 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Serverless","points":212,"comments":105,"url":"https://core.telegram.org/bots/serverless","discussion":"https://news.ycombinator.com/item?id=48918534"},{"title":"My midlife crisis Corolla is fast, furious, and modded","points":199,"comments":426,"url":"https://www.zocalopublicsquare.org/my-midlife-crisis-corolla-fast-furious-fully-modded/","discussion":"https://news.ycombinator.com/item?id=48921303"}],"research":[{"title":"Propheticus: Machine Learning Framework for the Development of Predictive Models for Reliable and Secure Software","abstract":"The growing complexity of software calls for innovative solutions that support the deployment of reliable and secure software. Machine Learning (ML) has shown its applicability to various complex problems and is frequently used in the dependability domain, both for supporting systems design and verification activities. However, using ML is complex and highly dependent on the problem in hand, increasing the probabilit","authors":["Campos, João R.","Vieira, Marco","Costa, Ernesto"],"url":"https://arxiv.org/abs/1809.01898","arxiv_id":"1809.01898","published":"2026-07-15"},{"title":"Diversity-Enriched Option-Critic","abstract":"Temporal abstraction allows reinforcement learning agents to represent knowledge and develop strategies over different temporal scales. The option-critic framework has been demonstrated to learn temporally extended actions, represented as options, end-to-end in a model-free setting. However, feasibility of option-critic remains limited due to two major challenges, multiple options adopting very similar behavior, or a","authors":["Kamat, Anand","Precup, Doina"],"url":"https://arxiv.org/abs/2011.02565","arxiv_id":"2011.02565","published":"2026-07-15"},{"title":"Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins","abstract":"Various machine-learning models, including deep neural network models, have already been developed to predict deleteriousness of missense (non-synonymous) mutations. Potential improvements to the current state of the art, however, may still benefit from a fresh look at the biological problem using more sophisticated self-adaptive machine-learning approaches. Recent advances in the natural language processing field sh","authors":["Jiang, Theodore","Fang, Li","Wang, Kai"],"url":"https://arxiv.org/abs/2110.14746","arxiv_id":"2110.14746","published":"2026-07-15"},{"title":"Privacy-Preserving Logistic Regression Training with A Faster Gradient Variant","abstract":"Training logistic regression over encrypted data has emerged as a prominent approach to addressing security concerns in recent years. In this paper, we introduce an efficient gradient variant, termed the \\textit{quadratic gradient}, which is specifically designed for privacy-preserving logistic regression while remaining equally effective in plaintext optimization. By incorporating this quadratic gradient, we enhance","authors":["Chiang, John"],"url":"https://arxiv.org/abs/2201.10838","arxiv_id":"2201.10838","published":"2026-07-15"},{"title":"Spectral Diffusion Processes","abstract":"Diffusion models have proven to be a flexible and effective framework for modelling probability distributions on finite-dimensional spaces. However, many physical modelling problems such as time series are naturally described over function spaces. In this work we apply diffusion models to such stochastic processes. To do so we consider a spectral representation of the data, obtained using a kernel, thereby dissociati","authors":["Phillips, Angus","Seror, Thomas","Hutchinson, Michael","De Bortoli, Valentin","Doucet, Arnaud","Mathieu, Emile"],"url":"https://arxiv.org/abs/2209.14125","arxiv_id":"2209.14125","published":"2026-07-15"},{"title":"Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction","abstract":"A central problem in computational biophysics is protein structure prediction, i.e., finding the optimal folding of a given amino acid sequence. This problem has been studied in a classical abstract model, the HP model, where the protein is modeled as a sequence of H (hydrophobic) and P (polar) amino acids on a lattice. The objective is to find conformations maximizing H-H contacts. It is known that even in this redu","authors":["Yang, Kaiyuan","Huang, Houjing","Vandans, Olafs","Murali, Adithya","Tian, Fujia","Yap, Roland H. C."],"url":"https://arxiv.org/abs/2211.14939","arxiv_id":"2211.14939","published":"2026-07-15"},{"title":"Classification of integers based on residue classes via modern deep learning algorithms","abstract":"Judging whether an integer can be divided by prime numbers such as 2 or 3 may appear trivial to human beings, but can be less straightforward for computers. Here, we tested multiple deep learning architectures and feature engineering approaches on classifying integers based on their residues when divided by small prime numbers. We found that the ability of classification critically depends on the feature space. We al","authors":["Wu, Da","Yang, Jingye","Ahsan, Mian Umair","Wang, Kai"],"url":"https://arxiv.org/abs/2304.01333","arxiv_id":"2304.01333","published":"2026-07-15"},{"title":"Data as Voters: Core Set Selection Using Approval-Based Multi-Winner Voting","abstract":"We present a novel approach to the core set/instance selection problem in machine learning. Our approach is based on recent results on (proportional) representation in approval-based multi-winner elections. In our model, instances play a double role as voters and candidates. The approval set of each instance in the training set (acting as a voter) is defined from the concept of local set, which already exists in the ","authors":["Sánchez-Fernández, Luis","Fisteus, Jesús A.","López-Zaragoza, Rafael"],"url":"https://arxiv.org/abs/2304.09995","arxiv_id":"2304.09995","published":"2026-07-15"},{"title":"Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT","abstract":"We hypothesize that large language models (LLMs) based on the transformer architecture can enable automated detection of clinical phenotype terms, including terms not documented in the HPO. In this study, we developed two types of models: PhenoBCBERT, a BERT-based model, utilizing Bio+Clinical BERT as its pre-trained model, and PhenoGPT, a GPT-based model that can be initialized from diverse GPT models, including ope","authors":["Yang, Jingye","Liu, Cong","Deng, Wendy","Wu, Da","Weng, Chunhua","Zhou, Yunyun"],"url":"https://arxiv.org/abs/2308.06294","arxiv_id":"2308.06294","published":"2026-07-15"},{"title":"Strategic Behavior of Large Language Models: Game Structure vs. Contextual Framing","abstract":"This paper investigates the strategic decision-making capabilities of three Large Language Models (LLMs): GPT-3.5, GPT-4, and LLaMa-2, within the framework of game theory. Utilizing four canonical two-player games -- Prisoner's Dilemma, Stag Hunt, Snowdrift, and Prisoner's Delight -- we explore how these models navigate social dilemmas, situations where players can either cooperate for a collective benefit or","authors":["Lorè, Nunzio","Heydari, Babak"],"url":"https://arxiv.org/abs/2309.05898","arxiv_id":"2309.05898","published":"2026-07-15"},{"title":"Exploring the Reversal Curse and Other Deductive Logical Reasoning in BERT and GPT-Based Large Language Models","abstract":"The term &#34;Reversal Curse&#34; refers to the scenario where auto-regressive decoder large language models (LLMs), such as ChatGPT, trained on &#34;A is B&#34; fail to learn &#34;B is A,&#34; assuming that B and A are distinct and can be uniquely identified from each other, demonstrating a basic failure of logical deduction. This raises a red flag in the use of GPT models for certain general tasks such as construct","authors":["Wu, Da","Yang, Jingye","Wang, Kai"],"url":"https://arxiv.org/abs/2312.03633","arxiv_id":"2312.03633","published":"2026-07-15"},{"title":"The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication","abstract":"Local SGD is a popular optimization method in distributed learning, often outperforming other algorithms in practice, including mini-batch SGD. Despite this success, theoretically proving the dominance of local SGD in settings with reasonable data heterogeneity has been difficult, creating a significant gap between theory and practice. In this paper, we provide new lower bounds for local SGD under existing first-orde","authors":["Patel, Kumar Kshitij","Glasgow, Margalit","Zindari, Ali","Wang, Lingxiao","Stich, Sebastian U.","Cheng, Ziheng"],"url":"https://arxiv.org/abs/2405.11667","arxiv_id":"2405.11667","published":"2026-07-15"},{"title":"Conformal Recursive Feature Elimination","abstract":"Unlike traditional statistical methods, Conformal Prediction (CP) allows for the determination of valid and accurate confidence levels associated with individual predictions based only on exchangeability of the data. We here introduce a new feature selection method that takes advantage of the CP framework. Our proposal, named Conformal Recursive Feature Elimination (CRFE), identifies and recursively removes features ","authors":["López-De-Castro, Marcos","García-Galindo, Alberto","Armañanzas, Rubén"],"url":"https://arxiv.org/abs/2405.19429","arxiv_id":"2405.19429","published":"2026-07-15"},{"title":"Active Exploration via Autoregressive Generation of Missing Data","abstract":"We pose uncertainty quantification and exploration in online decision-making as a problem of training and generation from an autoregressive sequence model, an area experiencing rapid innovation. Our approach rests on viewing uncertainty as arising from missing future outcomes that could be revealed through action choices, rather than from unobservable latent parameters of the environment. This reformulation aligns na","authors":["Cai, Tiffany Tianhui","Namkoong, Hongseok","Russo, Daniel","Zhang, Kelly W"],"url":"https://arxiv.org/abs/2405.19466","arxiv_id":"2405.19466","published":"2026-07-15"},{"title":"VSLLaVA: a pipeline of large multimodal foundation model for industrial vibration signal analysis","abstract":"While Large Multimodal Models (LMMs) excel in general multimodal tasks, they lack the domain-specific knowledge for industrial vibration signal analysis. This paper introduces VSLLaVA, a comprehensive pipeline that utilizes expert knowledge-guided instruction tuning and evaluation to create an end-to-end LMM for signal analysis. To achieve this, we construct a novel Signal-Question-Answer (SQA) dataset using an exper","authors":["Li, Qi","Zhang, Xinran","Huang, Jinfeng","He, Hongliang","Zhang, Feibin","Qin, Zhaoye"],"url":"https://arxiv.org/abs/2409.07482","arxiv_id":"2409.07482","published":"2026-07-15"},{"title":"Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model","abstract":"Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e., In-Distribution (InD), or from an unknown out distribution. Recent researches have leveraged Diffusion Models (DMs) for OoD detection due to their powerful distribution modeling capability. Given an input image, an InD-pretrained DM produces a corresponding InD-aligned","authors":["Fang, Kun","Yang, Zuopeng","Hu, Haibo","Huang, Xiaolin","Yang, Jie","Tao, Qinghua"],"url":"https://arxiv.org/abs/2409.10094","arxiv_id":"2409.10094","published":"2026-07-15"},{"title":"A Comprehensive Evaluation of Deep Learning Object Detection Models on Heterogeneous Edge Devices","abstract":"Modern applications such as autonomous vehicles, intelligent surveillance, and smart city systems increasingly require object detection on resource-constrained edge devices. Yet, there is still limited understanding of how different object detection models behave across heterogeneous edge devices and under varying scene complexity. In this paper, we benchmark YOLOv8 (Nano, Small, Medium), EfficientDet Lite (Lite0, Li","authors":["Alqahtani, Daghash K.","Cheema, Muhammad Aamir","Rodriguez, Maria A.","Toosi, Adel N."],"url":"https://arxiv.org/abs/2409.16808","arxiv_id":"2409.16808","published":"2026-07-15"},{"title":"Stars, Stripes, and Silicon: Unravelling the ChatGPT's All-American, Monochrome, Cis-centric Bias","abstract":"This paper investigates the challenges associated with bias, toxicity, unreliability, and lack of robustness in large language models (LLMs) such as ChatGPT. It emphasizes that these issues primarily stem from the quality and diversity of data on which LLMs are trained, rather than the model architectures themselves. As LLMs are increasingly integrated into various real-world applications, their potential to negative","authors":["Torrielli, Federico"],"url":"https://arxiv.org/abs/2410.13868","arxiv_id":"2410.13868","published":"2026-07-15"},{"title":"Growing a Tail: Increasing Output Diversity in Large Language Models","abstract":"How diverse are the outputs of large language models when diversity is desired? We examine the diversity of responses of several language models to questions with multiple possible answers, comparing them with human responses. Our findings suggest that models' responses are highly concentrated, reflecting narrow, mainstream outputs, in comparison to humans, whose responses exhibit a much longer-tail. We examine t","authors":["Shur-Ofry, Michal","Horowitz-Amsalem, Bar","Rahamim, Adir","Belinkov, Yonatan"],"url":"https://arxiv.org/abs/2411.02989","arxiv_id":"2411.02989","published":"2026-07-15"},{"title":"MolMiner: Toward Controllable, 3D-Aware, Fragment-Based Molecular Design","abstract":"We introduce MolMiner, a fragment-based, geometry-aware, and order-agnostic autoregressive model for molecular design. MolMiner supports high-dimensional conditional control over twelve physicochemical and structural properties from partial specifications, constructs molecules via symmetry-aware fragment attachments, and conditions each generation step on force-field-relaxed three-dimensional geometry of the partial ","authors":["Ortega-Ochoa, Raul","Vegge, Tejs","Frellsen, Jes"],"url":"https://arxiv.org/abs/2411.06608","arxiv_id":"2411.06608","published":"2026-07-15"},{"title":"Image Matching Filtering and Refinement by Planes and Beyond","abstract":"This paper provides a consistent and extensive evaluation of state-of-the-art filtering and refinement methods on common image matching pipelines. Unlike previous comparisons, the designed benchmark also takes into account the more general, real, and practical cases where camera intrinsics are unavailable. Moreover, a novel and effective strategy combining non-deep traditional computer vision approaches based on plan","authors":["Bellavia, Fabio","Zhao, Zhenjun","Morelli, Luca","Remondino, Fabio"],"url":"https://arxiv.org/abs/2411.09484","arxiv_id":"2411.09484","published":"2026-07-15"},{"title":"Enabling Energy-Efficient Simultaneous Multi-Task Reinforcement Learning through Spiking Neural Networks with Active Dendrites for Bio-inspired Generalist Agents","abstract":"Reinforcement learning (RL) has demonstrated remarkable capabilities in training agents to solve complex tasks autonomously, such as mobile robots, UAVs/UGVs, and game-playing agents). However, scaling RL to master multiple tasks simultaneously (i.e., so-called multi-task RL) remains a significant challenge. Such a multi-task RL capability especially is important for agents to adapt to changes in real-world operation","authors":["Putra, Rachmad Vidya Wicaksana","Devkota, Avaneesh","Shafique, Muhammad"],"url":"https://arxiv.org/abs/2412.04847","arxiv_id":"2412.04847","published":"2026-07-15"},{"title":"LVMark: Robust Watermark for Latent Video Diffusion Models","abstract":"Rapid advancements in video diffusion models have enabled the creation of realistic videos, raising concerns about unauthorized use and driving the demand for techniques to protect model ownership. Existing watermarking methods suffer from two key limitations: they overlook temporal consistency due to conventional watermark decoders and degrade the visual quality of the generated videos. To address these issues, we i","authors":["Jang, Youngdong","Jang, MinHyuk","Lee, JaeHyeok","Yang, Feng","Oh, Gyeongrok","Jeong, Jongheon"],"url":"https://arxiv.org/abs/2412.09122","arxiv_id":"2412.09122","published":"2026-07-15"},{"title":"Modeling Story Expectations: A Generative Framework using LLMs","abstract":"Consumers' engagement with stories is shaped by their expectations about what will happen next, yet modeling these forward-looking beliefs over unstructured narrative content has remained challenging. We develop a framework that uses large language models to approximate consumers' story expectations. Our method generates multiple imagined story continuations from a pre-trained LLM and extracts interpretable, ","authors":["Fong, Hortense","Gui, George","Yang, Bo"],"url":"https://arxiv.org/abs/2412.15239","arxiv_id":"2412.15239","published":"2026-07-15"},{"title":"Toward Metaphor-Fluid Conversation Design for Voice User Interfaces","abstract":"Metaphors play a critical role in shaping user experiences with Voice User Interfaces (VUIs), yet existing designs often rely on static, human-centric metaphors that fail to adapt to diverse contexts and user needs. This paper introduces Metaphor-Fluid Design, a novel approach that dynamically adjusts metaphorical representations based on conversational use-contexts. We compare this approach to a Default VUI, which c","authors":["Desai, Smit","Chin, Jessie","Wang, Dakuo","Cowan, Benjamin","Twidale, Michael"],"url":"https://arxiv.org/abs/2502.11554","arxiv_id":"2502.11554","published":"2026-07-15"}],"history":{"events":[{"year":2018,"text":"Croatian Mario Mandžukić scored the first own goal in a FIFA World Cup final in their defeat to France.","url":"https://en.wikipedia.org/wiki/Mario_Mand%C5%BEuki%C4%87"},{"year":2016,"text":"The Peace at Home Council, a faction of the Turkish Armed Forces, staged a coup d'état attempt against the government and President Recep Tayyip Erdoğan.","url":"https://en.wikipedia.org/wiki/Peace_at_Home_Council"},{"year":2012,"text":"South Korean rapper Psy (pictured) released his hit single \"Gangnam Style\".","url":"https://en.wikipedia.org/wiki/Psy"},{"year":2009,"text":"Caspian Airlines Flight 7908 crashed in northwestern Iran, killing all 168 people aboard.","url":"https://en.wikipedia.org/wiki/Caspian_Airlines_Flight_7908"},{"year":2009,"text":"A .mw-parser-output .tooltip-dotted{border-bottom:1px dotted;cursor:help}Mw 7.8 earthquake struck a remote region of Fiordland, New Zealand, the country's largest earthquake magnitude since the 1931 Hawke's Bay earthquake.","url":"https://en.wikipedia.org/wiki/Seismic_magnitude_scales"},{"year":1983,"text":"Sega's first home video game console, the SG-1000 (pictured), was released in Japan.","url":"https://en.wikipedia.org/wiki/Sega"},{"year":1943,"text":"The all-female Emilia Plater Independent Women's Battalion was formed in the Soviet Union's First Polish Army.","url":"https://en.wikipedia.org/wiki/Emilia_Plater_Independent_Women's_Battalion"},{"year":1870,"text":"Following the transfer of Rupert's Land from the Hudson's Bay Company, Manitoba was established as a province of Canada.","url":"https://en.wikipedia.org/wiki/Rupert's_Land"},{"year":1815,"text":"Aboard HMS Bellerophon, French emperor Napoleon surrendered to Royal Navy captain Frederick Lewis Maitland, concluding the Napoleonic Wars.","url":"https://en.wikipedia.org/wiki/HMS_Bellerophon_(1786)"},{"year":1799,"text":"French soldiers at Fort Julien, near the Egyptian port city of Rashid, uncovered the Rosetta Stone, which was essential in the decipherment of ancient Egyptian scripts.","url":"https://en.wikipedia.org/wiki/Fort_Julien"},{"year":1410,"text":"The Kingdom of Poland and the Grand Duchy of Lithuania defeated the Teutonic Knights at the Battle of Grunwald, the decisive engagement of the Polish–Lithuanian–Teutonic War.","url":"https://en.wikipedia.org/wiki/Crown_of_the_Kingdom_of_Poland"}],"births":[{"year":2008,"text":"Iain Armitage, American actor","url":"https://en.wikipedia.org/wiki/Iain_Armitage"},{"year":2005,"text":"JuJu Watkins, American basketball player","url":"https://en.wikipedia.org/wiki/JuJu_Watkins"},{"year":1999,"text":"Mohamed Sobhy, Egyptian footballer","url":"https://en.wikipedia.org/wiki/Mohamed_Sobhy_(footballer%2C_born_1999)"},{"year":1998,"text":"Noah Gragson, American racing driver","url":"https://en.wikipedia.org/wiki/Noah_Gragson"},{"year":1997,"text":"Jil Teichmann, Swiss tennis player","url":"https://en.wikipedia.org/wiki/Jil_Teichmann"},{"year":1997,"text":"Anthony Cirelli, Canadian ice hockey player","url":"https://en.wikipedia.org/wiki/Anthony_Cirelli"},{"year":1996,"text":"Vivianne Miedema, Dutch football player","url":"https://en.wikipedia.org/wiki/Vivianne_Miedema"},{"year":1994,"text":"Mason Dye, American actor","url":"https://en.wikipedia.org/wiki/Mason_Dye"}],"deaths":[{"year":2021,"text":"Peter R. de Vries, Dutch investigative journalist and crime reporter (born 1956)","url":"https://en.wikipedia.org/wiki/Peter_R._de_Vries"},{"year":2017,"text":"Martin Landau, American film and television actor (born 1928)","url":"https://en.wikipedia.org/wiki/Martin_Landau"},{"year":2015,"text":"Masahiko Aoki, Japanese-American economist and academic (born 1938)","url":"https://en.wikipedia.org/wiki/Masahiko_Aoki"},{"year":2015,"text":"Wan Li, Chinese politician, 4th Vice Premier of the People's Republic of China (born 1916)","url":"https://en.wikipedia.org/wiki/Wan_Li"},{"year":2015,"text":"Aubrey Morris, British actor (born 1926)","url":"https://en.wikipedia.org/wiki/Aubrey_Morris"},{"year":2015,"text":"Dave Somerville, Canadian singer (born 1933)","url":"https://en.wikipedia.org/wiki/Dave_Somerville"},{"year":2014,"text":"Óscar Acosta, Honduran author, poet, and diplomat (born 1933)","url":"https://en.wikipedia.org/wiki/%C3%93scar_Acosta"},{"year":2014,"text":"James MacGregor Burns, American historian, political scientist, and author (born 1918)","url":"https://en.wikipedia.org/wiki/James_MacGregor_Burns"}]},"sources":[{"id":"attention","name":"Wikipedia most-read","url":"https://api.wikimedia.org","licence":"CC BY-SA 4.0","attribution":"Wikipedia 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Every item links to its source."}