{"date":"2026-06-23","schema_version":1,"captured_at":"2026-08-25T23:13:51.715Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":17},"attention":[{"title":"Andy Burnham","views":934733,"rank":3,"extract":"Andrew Murray Burnham is a British politician who has served as Prime Minister of the United Kingdom and Leader of the Labour Party since July 2026. 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Tag","points":268,"comments":184,"url":"https://www.anthropic.com/news/introducing-claude-tag","discussion":"https://news.ycombinator.com/item?id=48648039"}],"research":[{"title":"Ratio Utility and Cost Analysis for Privacy Preserving Subspace Projection","abstract":"With a rapidly increasing number of devices connected to the internet, big data has been applied to various domains of human life. Nevertheless, it has also opened new venues for breaching users' privacy. Hence it is highly required to develop techniques that enable data owners to privatize their data while keeping it useful for intended applications. Existing methods, however, do not offer enough flexibility for","authors":["Al, Mert","Wan, Shibiao","Kung, Sun-Yuan"],"url":"https://arxiv.org/abs/1702.07976","arxiv_id":"1702.07976","published":"2026-06-23"},{"title":"Deep Learning Reveals Underlying Physics of Light-matter Interactions in Nanophotonic Devices","abstract":"In this paper, we present a deep learning-based (DL-based) algorithm, as a purely mathematical platform, for providing intuitive understanding of the properties of electromagnetic (EM) wave-matter interaction in nanostructures. This approach is based on using the dimensionality reduction (DR) technique to significantly reduce the dimensionality of a generic EM wave-matter interaction problem without imposing signific","authors":["Kiarashinejad, Yashar","Abdollahramezani, Sajjad","Zandehshahvar, Mohammadreza","Hemmatyar, Omid","Adibi, Ali"],"url":"https://arxiv.org/abs/1905.06889","arxiv_id":"1905.06889","published":"2026-06-23"},{"title":"Manifold Learning for Knowledge Discovery and Intelligent Inverse Design of Photonic Nanostructures: Breaking the Geometric Complexity","abstract":"Here, we present a new approach based on manifold learning for knowledge discovery and inverse design with minimal complexity in photonic nanostructures. Our approach builds on studying sub-manifolds of responses of a class of nanostructures with different design complexities in the latent space to obtain valuable insight about the physics of device operation to guide a more intelligent design. In contrast to the cur","authors":["Zandehshahvar, Mohammadreza","Kiarashi, Yashar","Zhu, Muliang","Maleki, Hossein","Brown, Tyler","Adibi, Ali"],"url":"https://arxiv.org/abs/2102.04454","arxiv_id":"2102.04454","published":"2026-06-23"},{"title":"Incorporating Domain Knowledge into Deep Neural Networks","abstract":"We present a survey of ways in which domain-knowledge has been included when constructing models with neural networks. The inclusion of domain-knowledge is of special interest not just to constructing scientific assistants, but also, many other areas that involve understanding data using human-machine collaboration. In many such instances, machine-based model construction may benefit significantly from being provided","authors":["Dash, Tirtharaj","Chitlangia, Sharad","Ahuja, Aditya","Srinivasan, Ashwin"],"url":"https://arxiv.org/abs/2103.00180","arxiv_id":"2103.00180","published":"2026-06-23"},{"title":"Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain","abstract":"We study the problem of finding approximate first-order stationary points in optimization problems of the form $\\min_{x \\in X} \\max_{y \\in Y} f(x,y)$, where the sets $X,Y$ are convex and $Y$ is compact. The objective function $f$ is smooth, but assumed neither convex in $x$ nor concave in $y$. Our approach relies upon replacing the function $f(x,\\cdot)$ with its $k$th order Taylor approximation (in $y$) and finding a","authors":["Ostrovskii, Dmitrii M.","Barazandeh, Babak","Razaviyayn, Meisam"],"url":"https://arxiv.org/abs/2110.03950","arxiv_id":"2110.03950","published":"2026-06-23"},{"title":"CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment","abstract":"We present Curve Distillation, CuDi, for efficient and controllable exposure adjustment without the requirement of paired or unpaired data during training. Our method inherits the zero-reference learning and curve-based framework from an effective low-light image enhancement method, Zero-DCE, with further speed up in its inference speed, reduction in its model size, and extension to controllable exposure adjustment. ","authors":["Li, Chongyi","Guo, Chunle","Feng, Ruicheng","Zhou, Shangchen","Loy, Chen Change"],"url":"https://arxiv.org/abs/2207.14273","arxiv_id":"2207.14273","published":"2026-06-23"},{"title":"Detection and Evaluation of Clusters within Sequential Data","abstract":"Sequential data is ubiquitous -- it is routinely gathered to gain insights into complex processes such as behavioral, biological, or physical processes. Challengingly, such data not only has dependencies within the observed sequences, but the observations are also often high-dimensional, sparse, and noisy. These are all difficulties that obscure the inner workings of the complex process under study. One solution is t","authors":["Van Werde, Alexander","Senen-Cerda, Albert","Kosmella, Gianluca","Sanders, Jaron"],"url":"https://arxiv.org/abs/2210.01679","arxiv_id":"2210.01679","published":"2026-06-23"},{"title":"MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis","abstract":"Conventional methods for human motion synthesis are either deterministic or struggle with the trade-off between motion diversity and motion quality. In response to these limitations, we introduce MoFusion, i.e., a new denoising-diffusion-based framework for high-quality conditional human motion synthesis that can generate long, temporally plausible, and semantically accurate motions based on a range of conditioning c","authors":["Dabral, Rishabh","Mughal, Muhammad Hamza","Golyanik, Vladislav","Theobalt, Christian"],"url":"https://arxiv.org/abs/2212.04495","arxiv_id":"2212.04495","published":"2026-06-23"},{"title":"Explanations for Automatic Speech Recognition","abstract":"We address quality assessment for neural network based ASR by providing explanations that help increase our understanding of the system and ultimately help build trust in the system. Compared to simple classification labels, explaining transcriptions is more challenging as judging their correctness is not straightforward and transcriptions as a variable-length sequence is not handled by existing interpretable machine","authors":["Wu, Xiaoliang","Bell, Peter","Rajan, Ajitha"],"url":"https://arxiv.org/abs/2302.14062","arxiv_id":"2302.14062","published":"2026-06-23"},{"title":"A criterion for Artificial General Intelligence: hypothetic-deductive reasoning, tested on ChatGPT","abstract":"We argue that a key reasoning skill that any advanced AI, say GPT-4, should master in order to qualify as 'thinking machine', or AGI, is hypothetic-deductive reasoning. Problem-solving or question-answering can quite generally be construed as involving two steps: hypothesizing that a certain set of hypotheses T applies to the problem or question at hand, and deducing the solution or answer from T - hence the ","authors":["Vervoort, Louis","Mizyakov, Vitaliy","Ugleva, Anastasia"],"url":"https://arxiv.org/abs/2308.02950","arxiv_id":"2308.02950","published":"2026-06-23"},{"title":"Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading","abstract":"Machine learning (ML) and deep learning (DL) techniques have gained significant attention as reduced order models (ROMs) to computationally expensive structural analysis methods, such as finite element analysis (FEA). Graph neural network (GNN) is a particular type of neural network which processes data that can be represented as graphs. This allows for efficient representation of complex geometries that can change d","authors":["Cai, Yuecheng","Jelovica, Jasmin"],"url":"https://arxiv.org/abs/2309.13022","arxiv_id":"2309.13022","published":"2026-06-23"},{"title":"Universal Time-Series Representation Learning: A Survey","abstract":"Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bodies. Learning representations by extracting and inferring valuable information from these time series is crucial for understanding the complex dynamics of particular phenomena and enabling informed decisions. With the learned representations, we can perform numerous downstream","authors":["Trirat, Patara","Shin, Yooju","Kang, Junhyeok","Nam, Youngeun","Na, Jihye","Bae, Minyoung"],"url":"https://arxiv.org/abs/2401.03717","arxiv_id":"2401.03717","published":"2026-06-23"},{"title":"Emergent Communication in Continuous Worlds: Self-Organisation of Conceptually Grounded Vocabularies at Scale","abstract":"This paper introduces a general methodology through which a population of autonomous agents can converge on a linguistic convention that enables them to refer to arbitrary entities in their environment. The linguistic convention emerges in a decentralised manner through local communicative interactions between pairs of agents drawn from the population. The emergent convention consists of associations between symbolic","authors":["Ekila, Jérôme Botoko","Verheyen, Lara","Nevens, Jens","Beuls, Katrien","Van Eecke, Paul"],"url":"https://arxiv.org/abs/2401.08461","arxiv_id":"2401.08461","published":"2026-06-23"},{"title":"Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE","abstract":"Understanding the inner workings of neural networks, including transformers, remains one of the most challenging puzzles in machine learning. This study introduces a novel approach by applying the principles of gauge symmetries, a key concept in physics, to neural network architectures. By regarding model functions as physical observables, we find that parametric redundancies of various machine learning models can be","authors":["Hashimoto, Koji","Hirono, Yuji","Sannai, Akiyoshi"],"url":"https://arxiv.org/abs/2402.02362","arxiv_id":"2402.02362","published":"2026-06-23"},{"title":"Are LLMs Effective Negotiators? Systematic Evaluation of the Multifaceted Capabilities of LLMs in Negotiation Dialogues","abstract":"A successful negotiation requires a range of capabilities, including comprehension of the conversation context, Theory-of-Mind (ToM) skills to infer the partner's motives, strategic reasoning, and effective communication, making it challenging for automated systems. Despite the remarkable performance of LLMs in various NLP tasks, there is no systematic evaluation of their capabilities in negotiation. Such an eval","authors":["Kwon, Deuksin","Weiss, Emily","Kulshrestha, Tara","Chawla, Kushal","Lucas, Gale M.","Gratch, Jonathan"],"url":"https://arxiv.org/abs/2402.13550","arxiv_id":"2402.13550","published":"2026-06-23"},{"title":"Wisdom of Committee: Diverse Distillation from Large Foundation Models and Domain Experts","abstract":"Knowledge distillation from foundation models to compact domain models is challenging due to substantial gaps in capacity, architecture, and modality. For example, in our experiments, distilling from a 76M-parameter language model to a 2M-parameter recommender closes less than 40% of the performance gap between the undistilled student and the teacher. We show that introducing domain-specific experts -- which share th","authors":["Liu, Zichang","Liu, Qingyun","Li, Yuening","Liu, Liang","Shrivastava, Anshumali","Bi, Shuchao"],"url":"https://arxiv.org/abs/2402.14035","arxiv_id":"2402.14035","published":"2026-06-23"},{"title":"NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning","abstract":"Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision avoidance. This paper presents NeuPAN: a real-time, highly accurate, map-free, easy-to-deploy, and environment-invariant robot motion planner. Leveraging a tightly coupled perception-to-control framework, NeuPAN has two key innovations compared to existing approaches: 1) ","authors":["Han, Ruihua","Wang, Shuai","Wang, Shuaijun","Zhang, Zeqing","Chen, Jianjun","Lin, Shijie"],"url":"https://arxiv.org/abs/2403.06828","arxiv_id":"2403.06828","published":"2026-06-23"},{"title":"Neural network representation of quantum systems","abstract":"It has been proposed that random wide neural networks near Gaussian process are quantum field theories around Gaussian fixed points. In this paper, we provide a novel map with which a wide class of quantum mechanical systems can be cast into the form of a neural network with a statistical summation over network parameters. Our simple idea is to use the universal approximation theorem of neural networks to generate ar","authors":["Hashimoto, Koji","Hirono, Yuji","Maeda, Jun","Totsuka-Yoshinaka, Jojiro"],"url":"https://arxiv.org/abs/2403.11420","arxiv_id":"2403.11420","published":"2026-06-23"},{"title":"Transcribing Bengali Text with Regional Dialects to IPA using District Guided Tokens","abstract":"Accurate transcription of Bengali text to the International Phonetic Alphabet (IPA) is a challenging task due to the complex phonology of the language and context-dependent sound changes. This challenge is even more for regional Bengali dialects due to unavailability of standardized spelling conventions for these dialects, presence of local and foreign words popular in those regions and phonological diversity across ","authors":["Islam, S M Jishanul","Ahmmed, Sadia","Mustakim, Sahid Hossain"],"url":"https://arxiv.org/abs/2403.17407","arxiv_id":"2403.17407","published":"2026-06-23"},{"title":"Physics-Enhanced Graph Neural Networks For Soft Sensing in Industrial Internet of Things","abstract":"The Industrial Internet of Things (IIoT) is reshaping manufacturing, industrial processes, and infrastructure management. By fostering new levels of automation, efficiency, and predictive maintenance, IIoT is transforming traditional industries into intelligent, seamlessly interconnected ecosystems. However, achieving highly reliable IIoT can be hindered by factors such as the cost of installing large numbers of sens","authors":["Niresi, Keivan Faghih","Bissig, Hugo","Baumann, Henri","Fink, Olga"],"url":"https://arxiv.org/abs/2404.08061","arxiv_id":"2404.08061","published":"2026-06-23"},{"title":"A polarity-aware multi-relational model for the signed interaction prediction in biological networks","abstract":"Predicting signed interactions in biological networks is crucial for understanding drug mechanisms and facilitating drug repurposing. While deep graph models have demonstrated success in modeling complex biological systems, existing approaches often fail to distinguish between positive and negative interactions, limiting their utility for precise pharmacological predictions. In this study, we propose a novel deep gra","authors":["Zhou, Yize","Wang, Meijie","Yu, Lun"],"url":"https://arxiv.org/abs/2407.07357","arxiv_id":"2407.07357","published":"2026-06-23"},{"title":"ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software","abstract":"Achieving reproducibility, quantity, and diversity in vulnerability datasets has long been viewed as an inherent three-way trade-off, where improving one dimension often comes at the cost of the others. In practice, reproducibility has been the dimension most often neglected. This has limited what can be automatically extracted from historical bug datasets, and has reduced their utility for downstream security resear","authors":["Mei, Xiang","Del Castillo, Jordi","Singaria, Pulkit Singh","Xi, Haoran","Benchikh, Abdelouahab","Bao, Tiffany"],"url":"https://arxiv.org/abs/2408.02153","arxiv_id":"2408.02153","published":"2026-06-23"},{"title":"Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model","abstract":"One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have been extensively used in driving-related research to assess cognitive load, only a few studies have specifically focused on high cognitive load scenarios. Most existing studies tend to examine moderate or low levels of cognitive load In this","authors":["Khan, Mehshan Ahmed","Asadi, Houshyar","Qazani, Mohammad Reza Chalak","Arogbonlo, Adetokunbo","Nahavandi, Saeid","Lim, Chee Peng"],"url":"https://arxiv.org/abs/2408.06350","arxiv_id":"2408.06350","published":"2026-06-23"},{"title":"Exploration of LLMs, EEG, and behavioral data to measure and support attention and sleep","abstract":"We explore the application of large language models (LLMs), pre-trained models with massive textual data for detecting and improving attention and sleep. We investigate the use of LLMs to estimate attention states, sleep stages, and sleep quality and generate sleep improvement suggestions and adaptive guided imagery scripts based on electroencephalogram (EEG) and physical activity data (e.g., waveforms, power spectro","authors":["Sano, Akane","Amores, Judith","Czerwinski, Mary"],"url":"https://arxiv.org/abs/2408.07822","arxiv_id":"2408.07822","published":"2026-06-23"},{"title":"Measuring Human Contribution in AI-Assisted Content Generation","abstract":"With the growing prevalence of generative artificial intelligence (AI), an increasing amount of content is no longer exclusively generated by humans but by generative AI models with human guidance. This shift presents notable challenges for the delineation of originality due to the varying degrees of human contribution in AI-assisted works. This study raises the research question of measuring human contribution in AI","authors":["Xie, Yueqi","Qi, Tao","Yi, Jingwei","Yang, Xiyuan","Whalen, Ryan","Huang, Junming"],"url":"https://arxiv.org/abs/2408.14792","arxiv_id":"2408.14792","published":"2026-06-23"}],"history":{"events":[{"year":2016,"text":"Citizens of the United Kingdom voted in favour of leaving the European Union.","url":"https://en.wikipedia.org/wiki/2016_United_Kingdom_European_Union_membership_referendum"},{"year":1992,"text":"Croatian War of Independence: The Battle of the Miljevci Plateau ended after a failed counterattack by forces of the Republic of Serbian Krajina against the Croatian Army who had captured the plateau.","url":"https://en.wikipedia.org/wiki/Croatian_War_of_Independence"},{"year":1991,"text":"The first instalment of the video-game series Sonic the Hedgehog was released in North America.","url":"https://en.wikipedia.org/wiki/Sonic_the_Hedgehog"},{"year":1982,"text":"Chinese American Vincent Chin died after being beaten into a coma in Highland Park, Michigan, U.S., by two automotive workers who were angry about the success of Japanese auto companies.","url":"https://en.wikipedia.org/wiki/Killing_of_Vincent_Chin"},{"year":1973,"text":"The Los Angeles Dodgers started Steve Garvey, Davey Lopes, Ron Cey, and Bill Russell in the infield, beginning a record eight-year run in Major League Baseball for four people designated as starters for those positions.","url":"https://en.wikipedia.org/wiki/Los_Angeles_Dodgers"},{"year":1972,"text":"President Richard Nixon signed Title IX (co-author Patsy Mink pictured) into law as part of the Education Amendments, prohibiting gender discrimination in any educational program receiving U.S. federal funds.","url":"https://en.wikipedia.org/wiki/Richard_Nixon"},{"year":1956,"text":"In a nationwide referendum, Gamal Abdel Nasser (pictured) was elected President of Egypt, a post he held until his death in 1970.","url":"https://en.wikipedia.org/wiki/1956_Egyptian_referendum"},{"year":1946,"text":"Canada's largest recorded onshore earthquake struck Vancouver Island, British Columbia.","url":"https://en.wikipedia.org/wiki/1946_Vancouver_Island_earthquake"},{"year":1944,"text":"The Holocaust: After a closely supervised visit to Theresienstadt Ghetto in German-occupied Czechoslovakia, Red Cross official Maurice Rossel reported that conditions there were \"almost normal\".","url":"https://en.wikipedia.org/wiki/The_Holocaust"},{"year":1926,"text":"The College Board administered the first Scholastic Aptitude Test, a major standardized test for university and college admissions in the United States.","url":"https://en.wikipedia.org/wiki/College_Board"},{"year":1887,"text":"The Parliament of Canada passed the Rocky Mountains Park Act, creating Banff National Park in Alberta as the country's first national park.","url":"https://en.wikipedia.org/wiki/Parliament_of_Canada"},{"year":1865,"text":"Stand Watie became the last Confederate general of the American Civil War to surrender to Union forces.","url":"https://en.wikipedia.org/wiki/Stand_Watie"},{"year":1797,"text":"War of the First Coalition: Napoleon signed the Armistice of Bologna, agreeing a ceasefire between France and the Papal States.","url":"https://en.wikipedia.org/wiki/War_of_the_First_Coalition"},{"year":1726,"text":"On the First Sunday after Trinity, J. S. Bach led the first performance of Brich dem Hungrigen dein Brot, BWV 39 (page pictured), one of a few new cantatas written that year.","url":"https://en.wikipedia.org/wiki/Church_cantata_(Bach)"},{"year":1594,"text":"Anglo-Spanish War: During the Action of Faial, an English attempt to capture a Portuguese carrack, reputedly one of the richest ever to set sail from the Indies, caused it to explode with all the treasure lost.","url":"https://en.wikipedia.org/wiki/Anglo-Spanish_War_(1585%E2%80%931604)"},{"year":1280,"text":"Reconquista: Troops of the Emirate of Granada defeated those of the Kingdom of Castile and the Kingdom of León in the Battle of Moclín.","url":"https://en.wikipedia.org/wiki/Reconquista"},{"year":1266,"text":"War of Saint Sabas: In an action off Trapani, Sicily, a Venetian fleet captured all 27 opposing Genoese vessels.","url":"https://en.wikipedia.org/wiki/War_of_Saint_Sabas"}],"births":[{"year":2008,"text":"Lilliana Ketchman, American dancer and YouTuber","url":"https://en.wikipedia.org/wiki/Lilliana_Ketchman"},{"year":2007,"text":"Elliana Walmsley, American dancer","url":"https://en.wikipedia.org/wiki/Elliana_Walmsley"},{"year":2006,"text":"Eli Junior Kroupi, French footballer","url":"https://en.wikipedia.org/wiki/Eli_Junior_Kroupi"},{"year":2000,"text":"Starford To'a, New Zealand rugby league player","url":"https://en.wikipedia.org/wiki/Starford_To'a"},{"year":1994,"text":"Ben Dwarshuis, Australian cricketer","url":"https://en.wikipedia.org/wiki/Ben_Dwarshuis"},{"year":1994,"text":"Roger Martínez, Colombian footballer","url":"https://en.wikipedia.org/wiki/Roger_Mart%C3%ADnez"},{"year":1993,"text":"Tim Anderson, American baseball player","url":"https://en.wikipedia.org/wiki/Tim_Anderson_(baseball)"},{"year":1993,"text":"Marvin Grumann, German footballer","url":"https://en.wikipedia.org/wiki/Marvin_Grumann"}],"deaths":[{"year":2025,"text":"Rebekah Del Rio, American singer-songwriter (born 1967)","url":"https://en.wikipedia.org/wiki/Rebekah_Del_Rio"},{"year":2025,"text":"John Clark, Scottish Footballer and Lisbon Lion (born 1941)","url":"https://en.wikipedia.org/wiki/John_Clark_(footballer%2C_born_1941)"},{"year":2021,"text":"John McAfee, British-American computer programmer and businessman, founded McAfee (born 1945)","url":"https://en.wikipedia.org/wiki/John_McAfee"},{"year":2016,"text":"Ralph Stanley, American singer and banjo player (born 1927)","url":"https://en.wikipedia.org/wiki/Ralph_Stanley"},{"year":2015,"text":"Miguel Facussé Barjum, Honduran businessman (born 1924)","url":"https://en.wikipedia.org/wiki/Miguel_Facuss%C3%A9_Barjum"},{"year":2015,"text":"Nirmala Joshi, Indian nun, lawyer, and social worker (born 1934)","url":"https://en.wikipedia.org/wiki/Nirmala_Joshi"},{"year":2015,"text":"Dick Van Patten, American actor (born 1928)","url":"https://en.wikipedia.org/wiki/Dick_Van_Patten"},{"year":2014,"text":"Nancy Garden, American author (born 1938)","url":"https://en.wikipedia.org/wiki/Nancy_Garden"}]},"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."}