{"date":"2026-03-19","schema_version":1,"captured_at":"2026-08-25T23:32:53.256Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":17},"attention":[{"title":"Joe Kent","views":323489,"rank":4,"extract":"Joseph Clay Kent is an American politician, former United States Army warrant officer, and former Central Intelligence Agency paramilitary officer who served as the director of the National Counterterrorism Center from 2025 to 2026. 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","url":"https://en.wikipedia.org/wiki/Africa_Cup_of_Nations","thumb":"https://upload.wikimedia.org/wikipedia/en/c/cf/Africa_Cup_of_Nation_official_logo.png?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail_unscaled"},{"title":"Aaron Gagnon","views":76707,"rank":33,"extract":"Aaron Gagnon is a Canadian former professional ice hockey centre who played in the National Hockey League (NHL) with the Dallas Stars and Winnipeg Jets.","url":"https://en.wikipedia.org/wiki/Aaron_Gagnon","thumb":"https://upload.wikimedia.org/wikipedia/commons/thumb/a/a3/Aaron_Gagnon_Iowa.jpg/330px-Aaron_Gagnon_Iowa.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail"},{"title":"P16","views":76631,"rank":34,"extract":"p16, is a protein that slows cell division by slowing the progression of the cell cycle from the G1 phase to the S phase, thereby acting as a tumor suppressor. It is encoded by the CDKN2A gene. 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UIs","points":257,"comments":106,"url":"https://github.com/antithesishq/bombadil","discussion":"https://news.ycombinator.com/item?id=47436592"},{"title":"Electronics for Kids, 2nd Edition","points":252,"comments":60,"url":"https://nostarch.com/electronics-for-kids-2e","discussion":"https://news.ycombinator.com/item?id=47434986"}],"research":[{"title":"HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method","abstract":"Accurately forecasting air quality is critical to protecting general public from lung and heart diseases. This is a challenging task due to the complicated interactions among distinct pollution sources and various other influencing factors. Existing air quality forecasting methods cannot effectively model the diffusion processes of air pollutants between cities and monitoring stations, which may suddenly deteriorate ","authors":["Chen, Ling","Xu, Jiahui","Wu, Binqing","Lv, Mingqi","Zhan, Chaoqun","Chen, Sanjian"],"url":"https://arxiv.org/abs/2101.04264","arxiv_id":"2101.04264","published":"2026-03-19"},{"title":"Theoretical Foundations of δ-margin Majority Voting","abstract":"In high-stakes ML applications such as fraud detection, medical diagnostics, and content moderation, practitioners rely on consensus-based approaches to control prediction quality. A particularly valuable technique -- δδδ-margin majority voting -- collects votes sequentially until one label exceeds alternatives by a threshold δδδ, offering stronger confidence than simple majority voting. Despite widespread adoption, ","authors":["Boyarskaya, Margarita","Ipeirotis, Panos"],"url":"https://arxiv.org/abs/2111.06390","arxiv_id":"2111.06390","published":"2026-03-19"},{"title":"The Moral Foundations Reddit Corpus","abstract":"Moral framing and sentiment can affect a variety of online and offline behaviors, including donation, environmental action, political engagement, and protest. Various computational methods in Natural Language Processing (NLP) have been used to detect moral sentiment from textual data, but achieving strong performance in such subjective tasks requires large, hand-annotated datasets. Previous corpora annotated for mora","authors":["Trager, Jackson","Ziabari, Alireza S.","Rahmati, Elnaz","Davani, Aida Mostafazadeh","Golazizian, Preni","Karimi-Malekabadi, Farzan"],"url":"https://arxiv.org/abs/2208.05545","arxiv_id":"2208.05545","published":"2026-03-19"},{"title":"Aergia: Leveraging Heterogeneity in Federated Learning Systems","abstract":"Federated Learning (FL) is a popular approach for distributed deep learning that prevents the pooling of large amounts of data in a central server. FL relies on clients to update a global model using their local datasets. Classical FL algorithms use a central federator that, for each training round, waits for all clients to send their model updates before aggregating them. In practical deployments, clients might have","authors":["Cox, Bart","Chen, Lydia Y.","Decouchant, Jérémie"],"url":"https://arxiv.org/abs/2210.06154","arxiv_id":"2210.06154","published":"2026-03-19"},{"title":"The MCC approaches the geometric mean of precision and recall as true negatives approach infinity","abstract":"The performance of a binary classifier is described by a confusion matrix with four entries: the number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). The Matthews Correlation Coefficient (MCC), F1, and Fowlkes-Mallows (FM) scores are scalars that summarize a confusion matrix. Both the F1 and FM scores are based on only three of the four entries in a confusion matrix (the","authors":["Crall, Jon"],"url":"https://arxiv.org/abs/2305.00594","arxiv_id":"2305.00594","published":"2026-03-19"},{"title":"Automated stance detection in complex topics and small languages: the challenging case of immigration in polarizing news media","abstract":"Automated stance detection and related machine learning methods can provide useful insights for media monitoring and academic research. Many of these approaches require annotated training datasets, which limits their applicability for languages where these may not be readily available. This paper explores the applicability of large language models for automated stance detection in a challenging scenario, involving a ","authors":["Mets, Mark","Karjus, Andres","Ibrus, Indrek","Schich, Maximilian"],"url":"https://arxiv.org/abs/2305.13047","arxiv_id":"2305.13047","published":"2026-03-19"},{"title":"Bridge Diffusion Model: Bridge Chinese Text-to-Image Diffusion Model with English Communities","abstract":"Text-to-Image generation (TTI) technologies are advancing rapidly, especially in the English language communities. However, apart from the user input language barrier problem, English-native TTI models inherently carry biases from their English world centric training data, which creates a dilemma for development of other language-native TTI models. One common choice is to fine-tune the English-native TTI model with t","authors":["Liu, Shanyuan","Cheng, Bo","Ma, Yuhang","Wu, Liebucha","Ma, Ao","Wu, Xiaoyu"],"url":"https://arxiv.org/abs/2309.00952","arxiv_id":"2309.00952","published":"2026-03-19"},{"title":"QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources","abstract":"Large Language Models (LLMs) have showcased remarkable impacts across a wide spectrum of natural language processing tasks. Fine-tuning these pretrained models on downstream datasets provides further significant performance gains; however, this process typically requires a large number of expensive, high-end GPUs. Although there have been efforts focused on parameter-efficient fine-tuning, they cannot fully unlock th","authors":["Li, Zhikai","Liu, Xiaoxuan","Zhu, Banghua","Dong, Zhen","Gu, Qingyi","Keutzer, Kurt"],"url":"https://arxiv.org/abs/2310.07147","arxiv_id":"2310.07147","published":"2026-03-19"},{"title":"Feature Space Renormalization for Semi-supervised Learning","abstract":"Semi-supervised learning (SSL) has been proven to be a powerful method for leveraging unlabeled data to alleviate models'dependence on large labeled datasets. The common framework among recent approaches is to train the model on a large amount of unlabeled data with consistency regularization to constrain the model predictions to be invariant to input perturbation. This paper proposes a feature space renormalizat","authors":["Sun, Jun","Zhang, Wancheng","Zhou, Chao","Mao, Zhongjie","Li, Chao","Wu, Xiao-Jun"],"url":"https://arxiv.org/abs/2311.04055","arxiv_id":"2311.04055","published":"2026-03-19"},{"title":"MultiMedEval: A Benchmark and a Toolkit for Evaluating Medical Vision-Language Models","abstract":"We introduce MultiMedEval, an open-source toolkit for fair and reproducible evaluation of large, medical vision-language models (VLM). MultiMedEval comprehensively assesses the models' performance on a broad array of six multi-modal tasks, conducted over 23 datasets, and spanning over 11 medical domains. The chosen tasks and performance metrics are based on their widespread adoption in the community and their div","authors":["Royer, Corentin","Menze, Bjoern","Sekuboyina, Anjany"],"url":"https://arxiv.org/abs/2402.09262","arxiv_id":"2402.09262","published":"2026-03-19"},{"title":"CurvFed: Curvature-Aligned Federated Learning for Fairness without Demographics","abstract":"Modern human sensing applications often rely on data distributed across users and devices, where privacy concerns prevent centralized training. Federated Learning (FL) addresses this challenge by enabling collaborative model training without exposing raw data or attributes. However, achieving fairness in such settings remains difficult, as most human sensing datasets lack demographic labels, and FL's privacy guar","authors":["Sharma, Harshit","Roy, Shaily","Salekin, Asif"],"url":"https://arxiv.org/abs/2404.19725","arxiv_id":"2404.19725","published":"2026-03-19"},{"title":"Hi-GMAE: Hierarchical Graph Masked Autoencoders","abstract":"Graph Masked Autoencoders (GMAEs) have emerged as a notable self-supervised learning approach for graph-structured data. Existing GMAE models primarily focus on reconstructing node-level information, categorizing them as single-scale GMAEs. This methodology, while effective in certain contexts, tends to overlook the complex hierarchical structures inherent in many real-world graphs. For instance, molecular graphs exh","authors":["Liu, Chuang","Yao, Zelin","Ma, Xueqi","Chen, Mukun","Wang, Luzhi","Wu, Jia"],"url":"https://arxiv.org/abs/2405.10642","arxiv_id":"2405.10642","published":"2026-03-19"},{"title":"Demystifying amortized causal discovery with transformers","abstract":"Supervised learning for causal discovery from observational data often achieves competitive performance despite seemingly avoiding the explicit assumptions that traditional methods require for identifiability. In this work, we analyze CSIvA (Ke et al., 2023) on bivariate causal models, a transformer architecture for amortized inference promising to train on synthetic data and transfer to real ones. First, we bridge t","authors":["Montagna, Francesco","Cairney-Leeming, Max","Sridhar, Dhanya","Locatello, Francesco"],"url":"https://arxiv.org/abs/2405.16924","arxiv_id":"2405.16924","published":"2026-03-19"},{"title":"UL-VIO: Ultra-lightweight Visual-Inertial Odometry with Noise Robust Test-time Adaptation","abstract":"Data-driven visual-inertial odometry (VIO) has received highlights for its performance since VIOs are a crucial compartment in autonomous robots. However, their deployment on resource-constrained devices is non-trivial since large network parameters should be accommodated in the device memory. Furthermore, these networks may risk failure post-deployment due to environmental distribution shifts at test time. In light ","authors":["Park, Jinho","Chun, Se Young","Seok, Mingoo"],"url":"https://arxiv.org/abs/2409.13106","arxiv_id":"2409.13106","published":"2026-03-19"},{"title":"From Geometric Mimicry to Comprehensive Generation: A Context-Informed Multimodal Diffusion Model for Urban Morphology Synthesis","abstract":"Urban morphology is fundamental to determining urban functionality and vitality. Prevailing simulation methods, however, often oversimplify morphological generation as a geometric problem, lacking a profound understanding of urban semantics and geographical context. To address this limitation, this study proposes ControlCity, a diffusion model that achieves comprehensive urban morphology generation through multimodal","authors":["Zhou, Fangshuo","Li, Huaxia","Xu, Liuchang","Hu, Rui","Wu, Sensen","Xu, Liang"],"url":"https://arxiv.org/abs/2409.17049","arxiv_id":"2409.17049","published":"2026-03-19"},{"title":"Den-TP: A Density-Balanced Data Curation and Evaluation Framework for Trajectory Prediction","abstract":"Trajectory prediction in autonomous driving has traditionally been studied from a model-centric perspective. However, existing datasets exhibit a strong long-tail distribution in scenario density, where common low-density cases dominate and safety-critical high-density cases are severely underrepresented. This imbalance limits model robustness and hides failure modes when standard evaluations average errors across al","authors":["Yang, Ruining","Xu, Yi","Fu, Yun","Su, Lili"],"url":"https://arxiv.org/abs/2409.17385","arxiv_id":"2409.17385","published":"2026-03-19"},{"title":"Efficient Diffusion as Low Light Enhancer","abstract":"The computational burden of the iterative sampling process remains a major challenge in diffusion-based Low-Light Image Enhancement (LLIE). Current acceleration methods, whether training-based or training-free, often lead to significant performance degradation, highlighting the trade-off between performance and efficiency. In this paper, we identify two primary factors contributing to performance degradation: fitting","authors":["Lan, Guanzhou","Ma, Qianli","Yang, Yuqi","Wang, Zhigang","Wang, Dong","Li, Xuelong"],"url":"https://arxiv.org/abs/2410.12346","arxiv_id":"2410.12346","published":"2026-03-19"},{"title":"Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware","abstract":"Quantum computing offers exciting opportunities for simulating complex quantum systems and optimizing large scale combinatorial problems, but its practical use is limited by device noise and constrained connectivity. Designing quantum circuits, which are fundamental to quantum algorithms, is therefore a central challenge in current quantum hardware. Existing reinforcement learning based methods for circuit design los","authors":["Kundu, Akash","Sarra, Leopoldo"],"url":"https://arxiv.org/abs/2411.00230","arxiv_id":"2411.00230","published":"2026-03-19"},{"title":"Fine-Grained Uncertainty Quantification via Collisions","abstract":"We propose a new and intuitive metric for aleatoric uncertainty quantification (UQ), the prevalence of class collisions defined as the same input being observed in different classes. We use the rate of class collisions to define the collision matrix, a novel and uniquely fine-grained measure of uncertainty. For a classification problem involving $K$ classes, the $K\\times K$ collision matrix $S$ measures the inherent ","authors":["Friedbaum, Jesse","Adiga, Sudarshan","Tandon, Ravi"],"url":"https://arxiv.org/abs/2411.12127","arxiv_id":"2411.12127","published":"2026-03-19"},{"title":"Conditional Distribution Learning for Graph Classification","abstract":"Leveraging the diversity and quantity of data provided by various graph-structured data augmentations while preserving intrinsic semantic information is challenging. Additionally, successive layers in graph neural network (GNN) tend to produce more similar node embeddings, while graph contrastive learning aims to increase the dissimilarity between negative pairs of node embeddings. This inevitably results in a confli","authors":["Chen, Jie","Mao, Hua","Liu, Chuanbin","Wang, Zhu","Peng, Xi"],"url":"https://arxiv.org/abs/2411.15206","arxiv_id":"2411.15206","published":"2026-03-19"},{"title":"Towards Clinical Practice in CT-Based Pulmonary Disease Screening: An Efficient and Reliable Framework","abstract":"Deep learning models for pulmonary disease screening from Computed Tomography (CT) scans promise to alleviate the immense workload on radiologists. Still, their high computational cost, stemming from processing entire 3D volumes, remains a major barrier to widespread clinical adoption. Current sub-sampling techniques often compromise diagnostic integrity by introducing artifacts or discarding critical information. To","authors":["Shao, Qian","Du, Bang","Wu, Yixuan","Li, Zepeng","Chen, Qiyuan","Tang, Qianqian"],"url":"https://arxiv.org/abs/2412.01525","arxiv_id":"2412.01525","published":"2026-03-19"},{"title":"Mamba2D: A Natively Multi-Dimensional State-Space Model for Vision Tasks","abstract":"State-Space Models (SSMs) have emerged as an efficient alternative to transformers, yet existing visual SSMs retain deeply ingrained biases from their origins in natural language processing. In this paper, we address these limitations by introducing M2D-SSM, a ground-up re-derivation of selective state-space techniques for multidimensional data. Unlike prior works that apply 1D SSMs directly to images through arbitra","authors":["Baty, Enis","Díaz, Alejandro Hernández","Davidson, Rebecca","Bridges, Chris","Hadfield, Simon"],"url":"https://arxiv.org/abs/2412.16146","arxiv_id":"2412.16146","published":"2026-03-19"},{"title":"Quantum-enhanced causal discovery for a small number of samples","abstract":"The discovery of causal relations from observed data has attracted significant interest from disciplines such as economics, social sciences, and biology. In practical applications, considerable knowledge of the underlying systems is often unavailable, and real data are usually associated with nonlinear causal structures, which makes the direct use of most conventional causality analysis methods difficult. This study ","authors":["Terada, Yu","Arai, Ken","Tanaka, Yu","Maeda, Yota","Ueno, Hiroshi","Tezuka, Hiroyuki"],"url":"https://arxiv.org/abs/2501.05007","arxiv_id":"2501.05007","published":"2026-03-19"},{"title":"Multilingual LLMs Struggle to Link Orthography and Semantics in Bilingual Word Processing","abstract":"Bilingual lexical processing is shaped by the complex interplay of phonological, orthographic, and semantic features of two languages within an integrated mental lexicon. In humans, this is evident in the ease with which cognate words - words similar in both orthographic form and meaning (e.g., blind, meaning "sightless" in both English and German) - are processed, compared to the challenges posed by interlin","authors":["Tanwar, Eshaan","Oke, Gayatri","Chakraborty, Tanmoy"],"url":"https://arxiv.org/abs/2501.09127","arxiv_id":"2501.09127","published":"2026-03-19"},{"title":"Oracular Programming: A Modular Foundation for Building LLM-Enabled Software","abstract":"Large Language Models (LLMs) can solve previously intractable tasks given only natural-language instructions and a few examples, but they remain difficult to steer precisely and lack a key capability for building reliable software at scale: the modular composition of computations under enforceable contracts. As a result, they are often embedded in larger software pipelines that use domain-specific knowledge to decomp","authors":["Laurent, Jonathan","Platzer, André"],"url":"https://arxiv.org/abs/2502.05310","arxiv_id":"2502.05310","published":"2026-03-19"}],"history":{"events":[{"year":2016,"text":"Flydubai Flight 981 crashed during an aborted landing at Rostov-on-Don Airport, Russia, resulting in the deaths of all 62 passengers and crew on board.","url":"https://en.wikipedia.org/wiki/Flydubai_Flight_981"},{"year":2011,"text":"First Libyan Civil War: The French Air Force launched Opération Harmattan, beginning foreign military intervention in Libya.","url":"https://en.wikipedia.org/wiki/Libyan_civil_war_(2011)"},{"year":2008,"text":"The gamma-ray burst GRB 080319B, the farthest object from Earth that was observable by the naked eye, was observed.","url":"https://en.wikipedia.org/wiki/Gamma-ray_burst"},{"year":2008,"text":"The gamma-ray burst GRB 080319B was observed, setting a record for the farthest event from Earth observable with the naked eye.","url":"https://en.wikipedia.org/wiki/Gamma-ray_burst"},{"year":1987,"text":"American televangelist Jim Bakker resigned as the host of The PTL Club in the midst of a sex scandal.","url":"https://en.wikipedia.org/wiki/Televangelism"},{"year":1979,"text":"The American cable television network C-SPAN, covering government proceedings and public-affairs programming, was launched.","url":"https://en.wikipedia.org/wiki/Cable_television"},{"year":1964,"text":"Between 300,000 and 500,000 Brazilians attended the March of the Family with God for Liberty (pictured), in protest against the government of João Goulart and against communism.","url":"https://en.wikipedia.org/wiki/March_of_the_Family_with_God_for_Liberty"},{"year":1962,"text":"Influential American musician Bob Dylan released his eponymous debut album, mainly comprising traditional folk, blues and gospel songs.","url":"https://en.wikipedia.org/wiki/Bob_Dylan"},{"year":1944,"text":"The secular oratorio A Child of Our Time by Michael Tippett premiered at the Adelphi Theatre in London.","url":"https://en.wikipedia.org/wiki/Oratorio"},{"year":1928,"text":"The highly influential American radio comedy show Amos 'n' Andy made its debut.","url":"https://en.wikipedia.org/wiki/Radio_comedy"},{"year":1911,"text":"Established by Clara Zetkin, Käte Duncker, and others, International Women's Day was first observed.","url":"https://en.wikipedia.org/wiki/Clara_Zetkin"},{"year":1865,"text":"American Civil War: The last battle of the Carolinas Campaign, the Battle of Bentonville, began, which contributed to the ultimate Union victory in the war.","url":"https://en.wikipedia.org/wiki/American_Civil_War"},{"year":1824,"text":"American explorer Benjamin Morrell departed Antarctica after a voyage later plagued by claims of fraud.","url":"https://en.wikipedia.org/wiki/Benjamin_Morrell"},{"year":1808,"text":"King Charles IV of Spain was forced to abdicate in favour of his son Ferdinand VII as a result of the Tumult of Aranjuez.","url":"https://en.wikipedia.org/wiki/Charles_IV_of_Spain"},{"year":1563,"text":"The Edict of Amboise was signed, ending the first war in the French Wars of Religion and inaugurating a period of official peace that lasted until 1567.","url":"https://en.wikipedia.org/wiki/Edict_of_Amboise"},{"year":1279,"text":"Mongol conquest of Song China: Zhao Bing (pictured), the last Song emperor, drowned at the end of the Battle of Yamen, bringing the Song dynasty to an end after three centuries.","url":"https://en.wikipedia.org/wiki/Mongol_conquest_of_the_Song_dynasty"},{"year":1277,"text":"The Byzantine Empire and the Republic of Venice signed a treaty that renegotiated and extended by two years a previous treaty between them.","url":"https://en.wikipedia.org/wiki/Byzantine_Empire"}],"births":[{"year":1999,"text":"Nico Collins, American football player","url":"https://en.wikipedia.org/wiki/Nico_Collins"},{"year":1998,"text":"Caylee Cowan, American actress","url":"https://en.wikipedia.org/wiki/Caylee_Cowan"},{"year":1998,"text":"Julian Love, American football player","url":"https://en.wikipedia.org/wiki/Julian_Love"},{"year":1998,"text":"Sakura Miyawaki, Japanese singer","url":"https://en.wikipedia.org/wiki/Sakura_Miyawaki"},{"year":1996,"text":"Yung Gravy, American rapper","url":"https://en.wikipedia.org/wiki/Yung_Gravy"},{"year":1996,"text":"Barbara Haas, Austrian tennis player","url":"https://en.wikipedia.org/wiki/Barbara_Haas"},{"year":1996,"text":"Quenton Nelson, American football player","url":"https://en.wikipedia.org/wiki/Quenton_Nelson"},{"year":1995,"text":"Héctor Bellerín, Spanish footballer","url":"https://en.wikipedia.org/wiki/H%C3%A9ctor_Beller%C3%ADn"}],"deaths":[{"year":2026,"text":"Chuck Norris, American martial artist and actor (born 1940)","url":"https://en.wikipedia.org/wiki/Chuck_Norris"},{"year":2021,"text":"Glynn Lunney, American engineer (born 1936)","url":"https://en.wikipedia.org/wiki/Glynn_Lunney"},{"year":2019,"text":"William Whitfield, British architect (born 1920)","url":"https://en.wikipedia.org/wiki/William_Whitfield_(architect)"},{"year":2016,"text":"Roger Agnelli, Brazilian banker and businessman (born 1959)","url":"https://en.wikipedia.org/wiki/Roger_Agnelli"},{"year":2016,"text":"Jack Mansell, English footballer and manager (born 1927)","url":"https://en.wikipedia.org/wiki/Jack_Mansell"},{"year":2015,"text":"Gus Douglass, American farmer and politician (born 1927)","url":"https://en.wikipedia.org/wiki/Gus_Douglass"},{"year":2015,"text":"Safet Plakalo, Bosnian author and playwright (born 1950)","url":"https://en.wikipedia.org/wiki/Safet_Plakalo"},{"year":2015,"text":"Danny Schechter, American director, producer, and screenwriter (born 1942)","url":"https://en.wikipedia.org/wiki/Danny_Schechter"}]},"census":null,"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."}