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This consists of a set of definitions of the same concept made up of a general definition (in this case, one encompassing the entire environmental domain) along with additional definitions describing the concept from the perspective of the subdomains i","authors":["Martín, Antonio San"],"url":"https://arxiv.org/abs/1607.06330","arxiv_id":"1607.06330","published":"2026-05-22"},{"title":"Do Vision Models Encode Object-Level Semantic Relatedness? A Cognitive Psychology-Inspired Benchmark","abstract":"Modern vision models have achieved strong object-recognition performance, yet it remains unclear whether their representations encode object-level semantic relatedness, the meaningful connection between object concepts that supports human visual cognition. Existing benchmarks predominantly target category prediction or rely on image--text matching, leaving the visual representation itself underexamined. Drawing on co","authors":["Lee, Hansang","Lee, Haeil","Kim, Junmo"],"url":"https://arxiv.org/abs/1709.03806","arxiv_id":"1709.03806","published":"2026-05-22"},{"title":"Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples","abstract":"Spiking neural networks (SNNs) have attracted much attention for their high energy efficiency and recent advances in classification performance. However, unlike traditional deep learning approaches, the study of SNN robustness to adversarial examples remains relatively underdeveloped. In this work, we advance the adversarial attack side of SNNs through three contributions. First, we show that successful white-box adv","authors":["Xu, Nuo","Mahmood, Kaleel","Fang, Haowen","Rathbun, Ethan","Ding, Caiwen","Wen, Wujie"],"url":"https://arxiv.org/abs/2209.03358","arxiv_id":"2209.03358","published":"2026-05-22"},{"title":"Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs","abstract":"Code analysis is fundamental in Software Engineering, supporting debugging, optimization, and security assessment. Human developers approach it through syntax parsing, static semantics inference, and dynamic reasoning. Traditional tools are effective but limited by language specificity and weak cross-language generalization. Large language models (LLMs) are promising for code tasks, yet their capabilities for fundame","authors":["Ma, Wei","Lin, Zhihao","Liu, Shangqing","Hu, Qiang","Liu, Ye","Wang, Wenhan"],"url":"https://arxiv.org/abs/2305.12138","arxiv_id":"2305.12138","published":"2026-05-22"},{"title":"TreeDQN: Sample-Efficient Off-Policy Reinforcement Learning for Combinatorial Optimization","abstract":"A convenient approach to optimally solving combinatorial optimization tasks is the Branch-and-Bound method. Its branching heuristic can be learned to solve a large set of similar tasks. The promising results here are achieved by the recently appeared on-policy reinforcement learning method based on the tree Markov Decision Process. To overcome its main disadvantages, namely, very large training time and unstable trai","authors":["Sorokin, D.","Kostin, A.","Savchenko, L.","Gusev, G.","Savchenko, A. V."],"url":"https://arxiv.org/abs/2306.05905","arxiv_id":"2306.05905","published":"2026-05-22"},{"title":"Cumulative Reasoning with Large Language Models","abstract":"Recent advancements in large language models (LLMs) have shown remarkable progress, yet their ability to solve complex problems remains limited. In this work, we introduce Cumulative Reasoning (CR), a structured framework that enhances LLM problem-solving by emulating human-like iterative and cumulative thought processes. CR orchestrates LLMs in three distinct roles: Proposer, Verifier(s), and Reporter, to systematic","authors":["Zhang, Yifan","Yang, Jingqin","Yuan, Yang","Yao, Andrew Chi-Chih"],"url":"https://arxiv.org/abs/2308.04371","arxiv_id":"2308.04371","published":"2026-05-22"},{"title":"Improved DDIM Sampling with Moment Matching Gaussian Mixtures","abstract":"We propose using a Gaussian Mixture Model (GMM) as reverse transition operator (kernel) within the Denoising Diffusion Implicit Models (DDIM) framework, which is one of the most widely used approaches for accelerated sampling from pre-trained Denoising Diffusion Probabilistic Models (DDPM). Specifically we match the first and second order central moments of the DDPM forward marginals by constraining the parameters of","authors":["Gabbur, Prasad"],"url":"https://arxiv.org/abs/2311.04938","arxiv_id":"2311.04938","published":"2026-05-22"},{"title":"Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning","abstract":"This paper introduces a causal attribution model to enhance the interpretability of large language models (LLMs) and improve their causal reasoning abilities via precise fine-tuning. Despite LLMs' proficiency in diverse tasks, their reasoning processes often remain black box, and thus restrict targeted enhancement. We propose a novel causal attribution model that utilizes &#34;do-operators&#34; for constructing i","authors":["Cai, Hengrui","Liu, Shengjie","Song, Rui"],"url":"https://arxiv.org/abs/2401.00139","arxiv_id":"2401.00139","published":"2026-05-22"},{"title":"Decoding News Narratives: A Critical Analysis of Large Language Models in Framing Detection","abstract":"The growing complexity and diversity of news coverage have made framing analysis a crucial yet challenging task in computational social science. Traditional approaches, including manual annotation and fine-tuned models, remain limited by high annotation costs, domain specificity, and inconsistent generalisation. Instruction-based large language models (LLMs) offer a promising alternative, yet their reliability for fr","authors":["Pastorino, Valeria","Sivakumar, Jasivan A.","Moosavi, Nafise Sadat"],"url":"https://arxiv.org/abs/2402.11621","arxiv_id":"2402.11621","published":"2026-05-22"},{"title":"Enhancing Instructional Quality: Leveraging Computer-Assisted Textual Analysis to Generate In-Depth Insights from Educational Artifacts","abstract":"This paper explores the transformative potential of computer-assisted textual analysis in enhancing instructional quality through in-depth insights from educational artifacts. We integrate Richard Elmore's Instructional Core Framework to examine how artificial intelligence (AI) and machine learning (ML) methods, particularly natural language processing (NLP), can analyze educational content, teacher discourse, an","authors":["Tian, Zewei","Sun, Min","Liu, Alex","Sarkar, Shawon","Liu, Jing"],"url":"https://arxiv.org/abs/2403.03920","arxiv_id":"2403.03920","published":"2026-05-22"},{"title":"QKFormer: Hierarchical Spiking Transformer using Q-K Attention","abstract":"Spiking Transformers, which integrate Spiking Neural Networks (SNNs) with Transformer architectures, have attracted significant attention due to their potential for energy efficiency and high performance. However, existing models in this domain still suffer from suboptimal performance. We introduce several innovations to improve the performance: i) We propose a novel spike-form Q-K attention mechanism, tailored for S","authors":["Zhou, Chenlin","Zhang, Han","Zhou, Zhaokun","Yu, Liutao","Huang, Liwei","Fan, Xiaopeng"],"url":"https://arxiv.org/abs/2403.16552","arxiv_id":"2403.16552","published":"2026-05-22"},{"title":"4D Radar Semantic Segmentation of People in Field Conditions Using Temporal Multi-View Networks","abstract":"Reliable people detection is crucial for the safe autonomy of mobile robots and heavy vehicles, both on roads and in industrial settings like mining and construction. However, common sensors like cameras or lidars are prone to failure in adverse conditions such as dust, fog, or smoke, which limits their use in real-world robotic systems. Radar, on the other hand, delivers robust measurements in a wide range of enviro","authors":["Skog, Mikael","Kotlyar, Oleksandr","Kubelka, Vladimír","Magnusson, Martin"],"url":"https://arxiv.org/abs/2404.05307","arxiv_id":"2404.05307","published":"2026-05-22"},{"title":"Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence","abstract":"Causal machine learning holds promise for estimating individual treatment effects from complex data. For successful real-world applications of machine learning methods, it is of paramount importance to obtain reliable insights into which variables drive heterogeneity in the response to treatment. We propose PermuCATE, an algorithm based on the Conditional Permutation Importance (CPI) method, for statistically rigorou","authors":["Paillard, Joseph","Lobo, Angel Reyero","Kolodyazhniy, Vitaliy","Thirion, Bertrand","Engemann, Denis A."],"url":"https://arxiv.org/abs/2408.13002","arxiv_id":"2408.13002","published":"2026-05-22"},{"title":"ImProver: Agent-Based Automated Proof Optimization","abstract":"Large language models (LLMs) have been used to generate formal proofs of mathematical theorems in proofs assistants such as Lean. However, we often want to optimize a formal proof with respect to various criteria, depending on its downstream use. For example, we may want a proof to adhere to a certain style, or to be readable, concise, or modularly structured. Having suitably optimized proofs is also important for le","authors":["Ahuja, Riyaz","Avigad, Jeremy","Tetali, Prasad","Welleck, Sean"],"url":"https://arxiv.org/abs/2410.04753","arxiv_id":"2410.04753","published":"2026-05-22"},{"title":"Music102: An $D_{12}$-equivariant transformer for chord progression accompaniment","abstract":"We present Music102, an advanced model aimed at enhancing chord progression accompaniment through a $D_{12}$-equivariant transformer. Inspired by group theory and symbolic music structures, Music102 leverages musical symmetry--such as transposition and reflection operations--integrating these properties into the transformer architecture. By encoding prior music knowledge, the model maintains equivariance across both ","authors":["Luo, Weiliang"],"url":"https://arxiv.org/abs/2410.18151","arxiv_id":"2410.18151","published":"2026-05-22"},{"title":"Leveraging Multi-Temporal Sentinel 1 and 2 Satellite Data for Leaf Area Index Estimation With Deep Learning","abstract":"The Leaf Area Index (LAI) is a critical parameter to understand ecosystem health and vegetation dynamics. In this paper, we propose a novel method for pixel-wise LAI prediction by leveraging the complementary information from Sentinel 1 radar data and Sentinel 2 multi-spectral data at multiple timestamps. Our approach uses a deep neural network based on multiple U-nets tailored specifically to this task. To handle th","authors":["Wang, Clement","Debouchage, Antoine","Goldité, Valentin","Wery, Aurélien","Salzinger, Jules"],"url":"https://arxiv.org/abs/2410.19787","arxiv_id":"2410.19787","published":"2026-05-22"},{"title":"A Mechanistic Explanatory Strategy for XAI","abstract":"Despite significant advancements in XAI, scholars note a persistent lack of solid conceptual foundations and integration with broader scientific discourse on explanation. In response, emerging research draws on explanatory strategies from various sciences and the philosophy of science literature to fill these gaps. This paper outlines a mechanistic strategy for explaining the functional organization of deep learning ","authors":["Rabiza, Marcin"],"url":"https://arxiv.org/abs/2411.01332","arxiv_id":"2411.01332","published":"2026-05-22"},{"title":"Deep learning-based modularized loading protocol for parameter estimation of Bouc-Wen class models","abstract":"This study proposes a modularized deep learning-based loading protocol for optimal parameter estimation of Bouc-Wen (BW) class models. The protocol consists of two key components: optimal loading history construction and CNN-based rapid parameter estimation. Each component is decomposed into independent sub-modules tailored to distinct hysteretic behaviors-basic hysteresis, structural degradation, and pinching effect","authors":["Oh, Sebin","Song, Junho","Kim, Taeyong"],"url":"https://arxiv.org/abs/2411.02776","arxiv_id":"2411.02776","published":"2026-05-22"},{"title":"Sparse Orthogonal Parameters Tuning for Continual Learning","abstract":"Continual learning methods based on pre-trained models (PTM) have recently gained attention which adapt to successive downstream tasks without catastrophic forgetting. These methods typically refrain from updating the pre-trained parameters and instead employ additional adapters, prompts, and classifiers. In this paper, we from a novel perspective investigate the benefit of sparse orthogonal parameters for continual ","authors":["Ning, Kun-Peng","Ke, Hai-Jian","Liu, Yu-Yang","Yao, Jia-Yu","Tian, Yong-Hong","Yuan, Li"],"url":"https://arxiv.org/abs/2411.02813","arxiv_id":"2411.02813","published":"2026-05-22"},{"title":"Deeply Learned Robust Matrix Completion for Large-scale Low-rank Data Recovery","abstract":"Robust matrix completion (RMC) is a widely used machine learning tool that simultaneously tackles two critical issues in low-rank data analysis: missing data entries and extreme outliers. This paper proposes a novel scalable and learnable non-convex approach, coined Learned Robust Matrix Completion (LRMC), for large-scale RMC problems. LRMC enjoys low computational complexity with linear convergence. Motivated by the","authors":["Cai, HanQin","Kundu, Chandra","Liu, Jialin","Yin, Wotao"],"url":"https://arxiv.org/abs/2501.00677","arxiv_id":"2501.00677","published":"2026-05-22"},{"title":"Neuro-Symbolic AI for Analytical Solutions of Differential Equations","abstract":"Analytical solutions to differential equations offer exact, interpretable insight but are rarely available because discovering them requires expert intuition or exhaustive search of combinatorial spaces. We introduce SIGS, a neuro-symbolic framework for equation-driven closed-form solution discovery. SIGS uses a context-free grammar to generate mathematically valid and physically meaningful building blocks, with a us","authors":["Oikonomou, Orestis","Lingsch, Levi","Grund, Dana","Mishra, Siddhartha","Kissas, Georgios"],"url":"https://arxiv.org/abs/2502.01476","arxiv_id":"2502.01476","published":"2026-05-22"},{"title":"Uncertainty quantification for Markov chain induced martingales with application to temporal difference learning","abstract":"We establish novel and general high-dimensional concentration inequalities and Berry-Esseen bounds for vector-valued martingales induced by Markov chains. We apply these results to analyze the performance of the Temporal Difference (TD) learning algorithm with linear function approximations, a widely used method for policy evaluation in Reinforcement Learning (RL), obtaining a sharp high-probability consistency guara","authors":["Wu, Weichen","Wei, Yuting","Rinaldo, Alessandro"],"url":"https://arxiv.org/abs/2502.13822","arxiv_id":"2502.13822","published":"2026-05-22"},{"title":"Prior shift estimation for positive unlabeled data through the lens of kernel embedding","abstract":"We study estimation of a class prior for unlabeled target samples which possibly differs from that of source population. Moreover, it is assumed that the source data is partially observable: only samples from the positive class and from the whole population are available (PU learning scenario). We introduce a novel direct estimator of a class prior which avoids estimation of posterior probabilities in both population","authors":["Mielniczuk, Jan","Rejchel, Wojciech","Teisseyre, Paweł"],"url":"https://arxiv.org/abs/2502.21194","arxiv_id":"2502.21194","published":"2026-05-22"},{"title":"LFX: Towards Unified Light Field Dense Semantic Segmentation and Salient Object Detection","abstract":"Light field cameras capture multi-view observations within a single exposure. However, existing studies are typically tailored to specific LF representations, leaving the field without a unified learning framework. To bridge this gap, we present LFX, the first unified framework for LF perception. LFX establishes a representation-invariant feature modulation space, enabling it to adapt to heterogeneous LF representati","authors":["Teng, Fei","Huang, Lingxin","Deng, Buyin","Luo, Kai","Zheng, Boyuan","Fang, Zheng"],"url":"https://arxiv.org/abs/2503.00747","arxiv_id":"2503.00747","published":"2026-05-22"},{"title":"&#34;Would You Want an AI Tutor?&#34; Understanding Stakeholder Perceptions of LLM-based Systems in the Classroom","abstract":"Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following early skepticism and bans, many schools and universities have begun integrating these systems into curricula. Yet decisions about whether and how to deploy LLM-based tools are frequently made without systematic engagement with the full range of stakeholders they affect. In this p","authors":["Fuligni, Caterina","Figaredo, Daniel Dominguez","Lewis, Armanda","Stoyanovich, Julia"],"url":"https://arxiv.org/abs/2503.02885","arxiv_id":"2503.02885","published":"2026-05-22"}],"history":{"events":[{"year":2026,"text":"A gas explosion at a coal mine in Changzhi, Shanxi, China, leaves at least 82 people dead.","url":"https://en.wikipedia.org/wiki/2026_Liushenyu_coal_mine_explosion"},{"year":2014,"text":"Prayut Chan-o-cha (pictured), the commander-in-chief of the Royal Thai Army, launched a coup d'état against the caretaker government following six months of political crisis.","url":"https://en.wikipedia.org/wiki/Prayut_Chan-o-cha"},{"year":2010,"text":"Upon landing in Mangalore, Air India Express Flight 812 overshot the runway and fell down a hillside, killing 158 of the 166 people on board.","url":"https://en.wikipedia.org/wiki/Mangaluru"},{"year":2002,"text":"Police announced that the skeletal remains of Federal Bureau of Prisons intern Chandra Levy, who had been missing for a year, had been found in Rock Creek Park in Washington, D.C.","url":"https://en.wikipedia.org/wiki/Federal_Bureau_of_Prisons"},{"year":1998,"text":"In Public Prosecutor v Taw Cheng Kong, the Court of Appeal of Singapore overruled a High Court decision in the only time a statute in Singapore had been ruled unconstitutional.","url":"https://en.wikipedia.org/wiki/Public_Prosecutor_v_Taw_Cheng_Kong"},{"year":1987,"text":"During Hindu–Muslim rioting in Meerut, India, 19 members of the Provincial Armed Constabulary allegedly massacred 42 Muslims and dumped their bodies in water canals.","url":"https://en.wikipedia.org/wiki/Religious_violence_in_India"},{"year":1980,"text":"Location testing for Pac-Man, a Japanese arcade game that became an icon of 1980s popular culture, began in Shibuya, Tokyo.","url":"https://en.wikipedia.org/wiki/Pac-Man"},{"year":1972,"text":"The Dominion of Ceylon changed its name to Sri Lanka, adopted a new constitution, and officially became a republic within the Commonwealth.","url":"https://en.wikipedia.org/wiki/Dominion_of_Ceylon"},{"year":1960,"text":"The most powerful earthquake ever recorded, registering approximately 9.5 Mw, struck near Valdivia, Chile, generating tsunamis that reached Hawaii and Japan.","url":"https://en.wikipedia.org/wiki/1960_Valdivia_earthquake"},{"year":1958,"text":"Ethnic riots mostly targeting the minority Sri Lankan Tamils broke out in Ceylon, resulting in at least 158 deaths over the next few days.","url":"https://en.wikipedia.org/wiki/1958_anti-Tamil_pogrom"},{"year":1939,"text":"Germany and Italy signed the Pact of Steel, a military and political alliance.","url":"https://en.wikipedia.org/wiki/Pact_of_Steel"},{"year":1915,"text":"California's Lassen Peak violently erupted, the only volcanic eruption in the contiguous U.S. in the 20th century until Mount St. Helens erupted in 1980.","url":"https://en.wikipedia.org/wiki/Lassen_Peak"},{"year":1905,"text":"Sultan Abdul Hamid II established the Ullah millet, a separate millet for the Aromanians within the Ottoman Empire.","url":"https://en.wikipedia.org/wiki/Abdul_Hamid_II"},{"year":1897,"text":"The first Blackwall Tunnel under the River Thames was opened to improve commerce and trade in the East End of London.","url":"https://en.wikipedia.org/wiki/Blackwall_Tunnel"},{"year":1874,"text":"Giuseppe Verdi's Requiem was first performed in the San Marco church in Milan to commemorate the first anniversary of Alessandro Manzoni's death.","url":"https://en.wikipedia.org/wiki/Giuseppe_Verdi"},{"year":1856,"text":"Senator Charles Sumner (pictured) was assaulted by Representative Preston Brooks in the United States Senate chamber in retaliation for a speech in which Sumner fiercely criticized slaveholders.","url":"https://en.wikipedia.org/wiki/Charles_Sumner"},{"year":1849,"text":"Abraham Lincoln was issued a patent for an invention to lift boats over obstacles in a river, making him the only U.S. president ever to hold a patent.","url":"https://en.wikipedia.org/wiki/Abraham_Lincoln"},{"year":1844,"text":"In Shiraz, Iran, the Báb declared himself to be a messenger of God to Mullá Husayn, leading to the foundation of Bábism, considered to be a precursor to the Baháʼí Faith.","url":"https://en.wikipedia.org/wiki/Shiraz"}],"births":[{"year":2004,"text":"Peyton Elizabeth Lee, American actress","url":"https://en.wikipedia.org/wiki/Peyton_Elizabeth_Lee"},{"year":2002,"text":"Anthony Richardson, American football player","url":"https://en.wikipedia.org/wiki/Anthony_Richardson_(American_football)"},{"year":2001,"text":"Enzo Barrenechea, Argentine footballer","url":"https://en.wikipedia.org/wiki/Enzo_Barrenechea"},{"year":2001,"text":"Emma Chamberlain, American internet personality","url":"https://en.wikipedia.org/wiki/Emma_Chamberlain"},{"year":2001,"text":"Joshua Zirkzee, Dutch footballer","url":"https://en.wikipedia.org/wiki/Joshua_Zirkzee"},{"year":2000,"text":"Julián Carranza, Argentine footballer","url":"https://en.wikipedia.org/wiki/Juli%C3%A1n_Carranza"},{"year":1999,"text":"Samuel Chukwueze, Nigerian footballer","url":"https://en.wikipedia.org/wiki/Samuel_Chukwueze"},{"year":1999,"text":"Femke Huijzer, Dutch model","url":"https://en.wikipedia.org/wiki/Femke_Huijzer"}],"deaths":[{"year":2026,"text":"Richard A. Tapia, American mathematician, National Medal of Science recipient (born 1939)","url":"https://en.wikipedia.org/wiki/Richard_A._Tapia"},{"year":2024,"text":"David Wilkie, Scottish swimmer (born 1954)","url":"https://en.wikipedia.org/wiki/David_Wilkie_(swimmer)"},{"year":2022,"text":"Dervla Murphy, Irish touring cyclist and author (born 1931)","url":"https://en.wikipedia.org/wiki/Dervla_Murphy"},{"year":2020,"text":"Denise Cronenberg, Canadian costume designer (born 1938)","url":"https://en.wikipedia.org/wiki/Denise_Cronenberg"},{"year":2019,"text":"Judith Kerr, German-born British writer and illustrator (born 1923)","url":"https://en.wikipedia.org/wiki/Judith_Kerr"},{"year":2017,"text":"Nicky Hayden, American motorcycle racer (born 1981)","url":"https://en.wikipedia.org/wiki/Nicky_Hayden"},{"year":2016,"text":"Velimir \"Bata\" Živojinović, Serbian actor and politician (born 1933)","url":"https://en.wikipedia.org/wiki/Bata_%C5%BDivojinovi%C4%87"},{"year":2015,"text":"Marques Haynes, American basketball player and coach (born 1926)","url":"https://en.wikipedia.org/wiki/Marques_Haynes"}]},"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."}