{"date":"2026-02-19","schema_version":1,"captured_at":"2026-08-25T23:28:59.271Z","complete":true,"sources_captured":["attention","frontier","research","history"],"counts":{"attention":30,"frontier":25,"research":25,"history":16},"attention":[{"title":"Jesse Jackson","views":370415,"rank":4,"extract":"Jesse Louis Jackson was an American civil rights activist, LGBTQ rights activist, politician, and ordained Baptist minister. 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This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this paper, we propose a novel technique for managing process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. T","authors":["Yeshchenko, Anton","Di Ciccio, Claudio","Mendling, Jan","Polyvyanyy, Artem"],"url":"https://arxiv.org/abs/1907.06386","arxiv_id":"1907.06386","published":"2026-02-19"},{"title":"Identifying Weight-Variant Latent Causal Models","abstract":"The task of causal representation learning aims to uncover latent higher-level causal variables that affect lower-level observations. Identifying the true latent causal variables from observed data, while allowing instantaneous causal relations among latent variables, remains a challenge, however. To this end, we start with the analysis of three intrinsic indeterminacies in identifying latent variables from observati","authors":["Liu, Yuhang","Zhang, Zhen","Gong, Dong","Gong, Mingming","Huang, Biwei","Hengel, Anton van den"],"url":"https://arxiv.org/abs/2208.14153","arxiv_id":"2208.14153","published":"2026-02-19"},{"title":"Measuring Rule-based LTLf Process Specifications: A Probabilistic Data-driven Approach","abstract":"Declarative process specifications define the behavior of processes by means of rules based on Linear Temporal Logic on Finite Traces (LTLf). In a mining context, these specifications are inferred from, and checked on, multi-sets of runs recorded by information systems (namely, event logs). To this end, being able to gauge the degree to which process data comply with a specification is key. However, existing mining a","authors":["Cecconi, Alessio","Barbaro, Luca","Di Ciccio, Claudio","Senderovich, Arik"],"url":"https://arxiv.org/abs/2305.05418","arxiv_id":"2305.05418","published":"2026-02-19"},{"title":"Monaural Multi-Speaker Speech Separation Using Efficient Transformer Model","abstract":"Cocktail party problem is the scenario where it is difficult to separate or distinguish individual speaker from a mixed speech from several speakers. There have been several researches going on in this field but the size and complexity of the model is being traded off with the accuracy and robustness of speech separation. "Monaural multi-speaker speech separation" presents a speech-separation model based on t","authors":["Rijal, S.","Neupane, R.","Mainali, S. P.","Regmi, S. K.","Maharjan, S."],"url":"https://arxiv.org/abs/2308.00010","arxiv_id":"2308.00010","published":"2026-02-19"},{"title":"Graph Isomorphic Networks for Assessing Reliability of the Medium-Voltage Grid","abstract":"Ensuring electricity grid reliability becomes increasingly challenging with the shift towards renewable energy and declining conventional capacities. Distribution System Operators (DSOs) aim to achieve grid reliability by verifying the n-1 principle, ensuring continuous operation in case of component failure. Electricity networks' complex graph-based data holds crucial information for n-1 assessment: graph struct","authors":["van Nooten, Charlotte Cambier","van de Poll, Tom","Füllhase, Sonja","Heres, Jacco","Heskes, Tom","Shapovalova, Yuliya"],"url":"https://arxiv.org/abs/2310.01181","arxiv_id":"2310.01181","published":"2026-02-19"},{"title":"Evaluating Language Model Agency through Negotiations","abstract":"We introduce an approach to evaluate language model (LM) agency using negotiation games. This approach better reflects real-world use cases and addresses some of the shortcomings of alternative LM benchmarks. Negotiation games enable us to study multi-turn, and cross-model interactions, modulate complexity, and side-step accidental evaluation data leakage. We use our approach to test six widely used and publicly acce","authors":["Davidson, Tim R.","Veselovsky, Veniamin","Josifoski, Martin","Peyrard, Maxime","Bosselut, Antoine","Kosinski, Michal"],"url":"https://arxiv.org/abs/2401.04536","arxiv_id":"2401.04536","published":"2026-02-19"},{"title":"RadDQN: a Deep Q Learning-based Architecture for Finding Time-efficient Minimum Radiation Exposure Pathway","abstract":"Recent advancements in deep reinforcement learning (DRL) techniques have sparked its multifaceted applications in the automation sector. Managing complex decision-making problems with DRL encourages its use in the nuclear industry for tasks such as optimizing radiation exposure to the personnel during normal operating conditions and potential accidental scenarios. However, the lack of efficient reward function and ef","authors":["Sadhu, Biswajit","Sadhu, Trijit","Anand, S."],"url":"https://arxiv.org/abs/2402.00468","arxiv_id":"2402.00468","published":"2026-02-19"},{"title":"Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions","abstract":"LLMs have demonstrated impressive performance in answering medical questions, such as achieving passing scores on medical licensing examinations. However, medical board exams or general clinical questions do not capture the complexity of realistic clinical cases. Moreover, the lack of reference explanations means we cannot easily evaluate the reasoning of model decisions, a crucial component of supporting doctors in ","authors":["Chen, Hanjie","Fang, Zhouxiang","Singla, Yash","Dredze, Mark"],"url":"https://arxiv.org/abs/2402.18060","arxiv_id":"2402.18060","published":"2026-02-19"},{"title":"Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm","abstract":"The quantum approximate optimization algorithm (QAOA) is a general-purpose algorithm for combinatorial optimization. In this paper, we analyze the performance of the QAOA on a statistical estimation problem, namely, the spiked tensor model, which exhibits a statistical-computational gap classically. We prove that the weak recovery threshold of $1$-step QAOA matches that of $1$-step tensor power iteration. Additional ","authors":["Zhou, Leo","Basso, Joao","Mei, Song"],"url":"https://arxiv.org/abs/2402.19456","arxiv_id":"2402.19456","published":"2026-02-19"},{"title":"Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scores","abstract":"The diversity across outputs generated by LLMs shapes perception of their quality and utility. High lexical diversity is often desirable, but there is no standard method to measure this property. Templated answer structures and ``canned'' responses across different documents are readily noticeable, but difficult to visualize across large corpora. This work aims to standardize measurement of text diversity. Sp","authors":["Shaib, Chantal","Govindarajan, Venkata S.","Barrow, Joe","Sun, Jiuding","Siu, Alexa F.","Wallace, Byron C."],"url":"https://arxiv.org/abs/2403.00553","arxiv_id":"2403.00553","published":"2026-02-19"},{"title":"LightCode: Light Analytical and Neural Codes for Channels with Feedback","abstract":"The design of reliable and efficient codes for channels with feedback remains a longstanding challenge in communication theory. While significant improvements have been achieved by leveraging deep learning techniques, neural codes often suffer from high computational costs, a lack of interpretability, and limited practicality in resource-constrained settings. We focus on designing low-complexity coding schemes that a","authors":["Ankireddy, Sravan Kumar","Narayanan, Krishna","Kim, Hyeji"],"url":"https://arxiv.org/abs/2403.10751","arxiv_id":"2403.10751","published":"2026-02-19"},{"title":"Prompt When the Animal is: Temporal Animal Behavior Grounding with Positional Recovery Training","abstract":"Temporal grounding is crucial in multimodal learning, but it poses challenges when applied to animal behavior data due to the sparsity and uniform distribution of moments. To address these challenges, we propose a novel Positional Recovery Training framework (Port), which prompts the model with the start and end times of specific animal behaviors during training. Specifically, \\port{} enhances the baseline model with","authors":["Yan, Sheng","Du, Xin","Li, Zongying","Wang, Yi","Jin, Hongcang","Liu, Mengyuan"],"url":"https://arxiv.org/abs/2405.05523","arxiv_id":"2405.05523","published":"2026-02-19"},{"title":"Less is More: Skim Transformer for Light Field Image Super-resolution","abstract":"A light field image captures scenes through its micro-lens array, providing a rich representation that encompasses spatial and angular information. While this richness comes at significant data redundancy, most existing methods tend to indiscriminately utilize all the information from sub-aperture images (SAIs) in an attempt to harness every visual cue regardless of their disparity significance. However, this paradig","authors":["Hu, Zeke Zexi","Chen, Haodong","Ye, Hui","Chen, Xiaoming","Chung, Vera Yuk Ying","Shen, Yiran"],"url":"https://arxiv.org/abs/2407.15329","arxiv_id":"2407.15329","published":"2026-02-19"},{"title":"Amortized Bayesian Workflow","abstract":"Bayesian inference often faces a trade-off between computational speed and sampling accuracy. We propose an adaptive workflow that integrates rapid amortized inference with gold-standard MCMC techniques to achieve a favorable combination of both speed and accuracy when performing inference on many observed datasets. Our approach uses principled diagnostics to guide the choice of inference method for each dataset, mov","authors":["Li, Chengkun","Vehtari, Aki","Bürkner, Paul-Christian","Radev, Stefan T.","Acerbi, Luigi","Schmitt, Marvin"],"url":"https://arxiv.org/abs/2409.04332","arxiv_id":"2409.04332","published":"2026-02-19"},{"title":"Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification","abstract":"In the medical field, the limited availability of large-scale datasets and labor-intensive annotation processes hinder the performance of deep models. Diffusion-based generative augmentation approaches present a promising solution to this issue, having been proven effective in advancing downstream medical recognition tasks. Nevertheless, existing works lack sufficient semantic and sequential steerability for challeng","authors":["Zhou, Xinrui","Huang, Yuhao","Dou, Haoran","Chen, Shijing","Chang, Ao","Liu, Jia"],"url":"https://arxiv.org/abs/2409.17091","arxiv_id":"2409.17091","published":"2026-02-19"},{"title":"When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writing","abstract":"AI-based systems such as language models have been shown to replicate and even amplify social biases reflected in their training data. Among other questionable behaviors, this can lead to AI-generated text--and text suggestions--that contain normatively inappropriate stereotypical associations. Little is known, however, about how this behavior impacts the writing produced by people using these systems. We address thi","authors":["Baumler, Connor","Daumé III, Hal"],"url":"https://arxiv.org/abs/2409.20390","arxiv_id":"2409.20390","published":"2026-02-19"},{"title":"Fused-Planes: Why Train a Thousand Tri-Planes When You Can Share?","abstract":"Tri-Planar NeRFs enable the application of powerful 2D vision models for 3D tasks, by representing 3D objects using 2D planar structures. This has made them the prevailing choice to model large collections of 3D objects. However, training Tri-Planes to model such large collections is computationally intensive and remains largely inefficient. This is because the current approaches independently train one Tri-Plane per","authors":["Kassab, Karim","Schnepf, Antoine","Franceschi, Jean-Yves","Caraffa, Laurent","Vasile, Flavian","Mary, Jeremie"],"url":"https://arxiv.org/abs/2410.23742","arxiv_id":"2410.23742","published":"2026-02-19"},{"title":"Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networks","abstract":"Spiking Neural Networks (SNNs) are biologically-inspired deep neural networks that efficiently extract temporal information while offering promising gains in terms of energy efficiency and latency when deployed on neuromorphic devices. SNN parameters are sensitive to temporal resolution, leading to significant performance drops when the temporal resolution of target data during deployment is not the same as that of t","authors":["Karilanova, Sanja","Fabre, Maxime","Neftci, Emre","Özçelikkale, Ayça"],"url":"https://arxiv.org/abs/2411.04760","arxiv_id":"2411.04760","published":"2026-02-19"},{"title":"A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning","abstract":"Recent regulatory proposals for artificial intelligence emphasize fairness requirements for machine learning models. However, precisely defining the appropriate measure of fairness is challenging due to philosophical, cultural and political contexts. Biases can infiltrate machine learning models in complex ways depending on the model's context, rendering a single common metric of fairness insufficient. This ambig","authors":["Barr, Caleb J. S.","Erdelyi, Olivia","Docherty, Paul D.","Grace, Randolph C."],"url":"https://arxiv.org/abs/2411.06624","arxiv_id":"2411.06624","published":"2026-02-19"},{"title":"VeGaS: Video Gaussian Splatting","abstract":"Implicit Neural Representations (INRs) employ neural networks to approximate discrete data as continuous functions. In the context of video data, such models can be utilized to transform the coordinates of pixel locations along with frame occurrence times (or indices) into RGB color values. Although INRs facilitate effective compression, they are unsuitable for editing purposes. One potential solution is to use a 3D ","authors":["Smolak-Dyżewska, Weronika","Malarz, Dawid","Howil, Kornel","Kaczmarczyk, Jan","Mazur, Marcin","Spurek, Przemysław"],"url":"https://arxiv.org/abs/2411.11024","arxiv_id":"2411.11024","published":"2026-02-19"},{"title":"MC-LLaVA: Multi-Concept Personalized Vision-Language Model","abstract":"Current vision-language models (VLMs) show exceptional abilities across diverse tasks, such as visual question answering. To enhance user experience, recent studies have investigated VLM personalization to understand user-provided concepts. However, they mainly focus on single concepts, neglecting the existence and interplay of multiple concepts, which limits real-world applicability. This paper proposes MC-LLaVA, a ","authors":["An, Ruichuan","Yang, Sihan","Zhang, Renrui","Lu, Ming","Jiang, Tianyi","Zeng, Kai"],"url":"https://arxiv.org/abs/2411.11706","arxiv_id":"2411.11706","published":"2026-02-19"},{"title":"ChatBCI: A P300 Speller BCI Leveraging Large Language Models for Improved Sentence Composition in Realistic Scenarios","abstract":"P300 speller BCIs allow users to compose sentences by selecting target keys on a GUI through the detection of P300 component in their EEG signals following visual stimuli. Most P300 speller BCIs require users to spell words letter by letter, or the first few initial letters, resulting in high keystroke demands that increase time, cognitive load, and fatigue. This highlights the need for more efficient, user-friendly ","authors":["Hong, Jiazhen","Wang, Weinan","Najafizadeh, Laleh"],"url":"https://arxiv.org/abs/2411.15395","arxiv_id":"2411.15395","published":"2026-02-19"},{"title":"A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation","abstract":"Advances in architectural design, data availability, and compute have driven remarkable progress in semantic segmentation. Yet, these models often rely on relaxed Bayesian assumptions, omitting critical uncertainty information needed for robust decision-making. Despite growing interest in probabilistic segmentation to address point-estimate limitations, the research landscape remains fragmented. In response, this rev","authors":["Valiuddin, M. M. A.","van Sloun, R. J. G.","Viviers, C. G. A.","de With, P. H. N.","van der Sommen, F."],"url":"https://arxiv.org/abs/2411.16370","arxiv_id":"2411.16370","published":"2026-02-19"},{"title":"RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics","abstract":"Spatial understanding is a crucial capability that enables robots to perceive their surroundings, reason about their environment, and interact with it meaningfully. In modern robotics, these capabilities are increasingly provided by vision-language models. However, these models face significant challenges in spatial reasoning tasks, as their training data are based on general-purpose image datasets that often lack so","authors":["Song, Chan Hee","Blukis, Valts","Tremblay, Jonathan","Tyree, Stephen","Su, Yu","Birchfield, Stan"],"url":"https://arxiv.org/abs/2411.16537","arxiv_id":"2411.16537","published":"2026-02-19"},{"title":"LMSeg: Unleashing the Power of Large-Scale Models for Open-Vocabulary Semantic Segmentation","abstract":"It is widely agreed that open-vocabulary-based approaches outperform classical closed-set training solutions for recognizing unseen objects in images for semantic segmentation. Existing open-vocabulary approaches leverage vision-language models, such as CLIP, to align visual features with rich semantic features acquired through pre-training on large-scale vision-language datasets. However, the text prompts employed i","authors":["Tang, Huadong","Zhao, Youpeng","Huang, Yan","Xu, Min","Wang, Jun","Wu, Qiang"],"url":"https://arxiv.org/abs/2412.00364","arxiv_id":"2412.00364","published":"2026-02-19"}],"history":{"events":[{"year":2026,"text":"Andrew Mountbatten-Windsor became the first member of the British royal family to be arrested in 379 years.","url":"https://en.wikipedia.org/wiki/Andrew_Mountbatten-Windsor"},{"year":2012,"text":"Mexican drug war: Forty-four inmates died in a prison riot in Apodaca, Mexico, between members of Los Zetas and the Gulf Cartel.","url":"https://en.wikipedia.org/wiki/Mexican_drug_war"},{"year":2011,"text":"Items from the Belitung shipwreck, the largest single collection of Tang-dynasty artefacts found in one location, were first exhibited in Singapore.","url":"https://en.wikipedia.org/wiki/Belitung_shipwreck"},{"year":2006,"text":"A methane explosion in a coal mine in Nueva Rosita, Mexico, trapped and killed 65 miners.","url":"https://en.wikipedia.org/wiki/Methane"},{"year":1965,"text":"Colonel Phạm Ngọc Thảo of the Army of the Republic of Vietnam, along with Generals Lâm Văn Phát and Trần Thiện Khiêm attempted a coup against the military junta of Nguyễn Khánh.","url":"https://en.wikipedia.org/wiki/Ph%E1%BA%A1m_Ng%E1%BB%8Dc_Th%E1%BA%A3o"},{"year":1963,"text":"Betty Friedan's The Feminine Mystique, a non-fiction book credited with sparking the beginning of second-wave feminism in the United States, was first published.","url":"https://en.wikipedia.org/wiki/Betty_Friedan"},{"year":1948,"text":"The Southeast Asian Youth Conference, which is believed to have inspired armed communist rebellions in different Asian countries, opened in Calcutta, India.","url":"https://en.wikipedia.org/wiki/Conference_of_Youth_and_Students_of_Southeast_Asia_Fighting_for_Freedom_and_Independence"},{"year":1942,"text":"World War II: U.S. president Franklin D. Roosevelt signed Executive Order 9066, authorizing the forcible relocation of over 112,000 Japanese Americans to internment camps.","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1942,"text":"Second World War: In the largest attack mounted by a foreign power against Australia, more than 240 Japanese aircraft bombed the city of Darwin (pictured).","url":"https://en.wikipedia.org/wiki/World_War_II"},{"year":1942,"text":"A book-burning was held and politicians were arrested in Winnipeg, Manitoba, Canada, as part of a simulated Nazi invasion.","url":"https://en.wikipedia.org/wiki/Winnipeg"},{"year":1937,"text":"Italian forces began a brutal crackdown on Ethiopians following an attempted assassination of Rodolfo Graziani, the viceroy of Italian East Africa, in Addis Ababa.","url":"https://en.wikipedia.org/wiki/Yekatit_12"},{"year":1931,"text":"The Socialist Soviet Republic of Abkhazia (flag pictured) was dissolved and reformed as the Abkhaz Autonomous Soviet Socialist Republic, an autonomous republic of the Soviet Union within Georgia.","url":"https://en.wikipedia.org/wiki/Socialist_Soviet_Republic_of_Abkhazia"},{"year":1910,"text":"Old Trafford, a football stadium in Greater Manchester, England, hosted its inaugural match, between Manchester United and Liverpool.","url":"https://en.wikipedia.org/wiki/Old_Trafford"},{"year":1903,"text":"A blockade against Venezuela (depicted), caused by President Cipriano Castro's refusal to pay foreign debts, was lifted.","url":"https://en.wikipedia.org/wiki/Venezuelan_crisis_of_1902%E2%80%931903"},{"year":1811,"text":"Peninsular War: Outnumbered French forces under Édouard Mortier routed and nearly destroyed Spanish troops at the Battle of the Gebora near Badajoz, Spain.","url":"https://en.wikipedia.org/wiki/Peninsular_War"},{"year":1600,"text":"Huaynaputina, a stratovolcano in present-day Peru, produced the largest recorded volcanic explosion in South America.","url":"https://en.wikipedia.org/wiki/Huaynaputina"}],"births":[{"year":2004,"text":"Millie Bobby Brown, English actress, model and producer","url":"https://en.wikipedia.org/wiki/Millie_Bobby_Brown"},{"year":2001,"text":"Lee Kang-in, South Korean footballer","url":"https://en.wikipedia.org/wiki/Lee_Kang-in"},{"year":2001,"text":"David Mazouz, American actor","url":"https://en.wikipedia.org/wiki/David_Mazouz"},{"year":1998,"text":"Katharina Gerlach, German tennis player","url":"https://en.wikipedia.org/wiki/Katharina_Gerlach"},{"year":1998,"text":"Chappell Roan, American singer and songwriter","url":"https://en.wikipedia.org/wiki/Chappell_Roan"},{"year":1998,"text":"Jungwoo, South Korean singer","url":"https://en.wikipedia.org/wiki/Jungwoo"},{"year":1996,"text":"Mabel, British-Swedish singer","url":"https://en.wikipedia.org/wiki/Mabel_(singer)"},{"year":1996,"text":"D. J. Wilson, American basketball player","url":"https://en.wikipedia.org/wiki/D._J._Wilson"}],"deaths":[{"year":2020,"text":"José Mojica Marins, Brazilian filmmaker, actor, composer, screenwriter, and television horror host (born 1936)","url":"https://en.wikipedia.org/wiki/Jos%C3%A9_Mojica_Marins"},{"year":2020,"text":"Pop Smoke, American rapper (born 1999)","url":"https://en.wikipedia.org/wiki/Pop_Smoke"},{"year":2019,"text":"Karl Lagerfeld, German fashion designer (born 1933)","url":"https://en.wikipedia.org/wiki/Karl_Lagerfeld"},{"year":2017,"text":"Larry Coryell, American jazz guitarist (born 1943)","url":"https://en.wikipedia.org/wiki/Larry_Coryell"},{"year":2016,"text":"Umberto Eco, Italian novelist, literary critic, and philosopher (born 1932)","url":"https://en.wikipedia.org/wiki/Umberto_Eco"},{"year":2016,"text":"Harper Lee, American author (born 1926)","url":"https://en.wikipedia.org/wiki/Harper_Lee"},{"year":2016,"text":"Chiaki Morosawa, Japanese anime screenwriter (born 1959)","url":"https://en.wikipedia.org/wiki/Chiaki_Morosawa"},{"year":2016,"text":"Samuel Willenberg, Polish-Israeli sculptor and painter (born 1923)","url":"https://en.wikipedia.org/wiki/Samuel_Willenberg"}]},"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."}