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arXiv:2602.19575v1 Announce Type: new Abstract: Personalized text-to-image generation suffers from concept entanglement, where irrelevant residual information from reference images is captured, leading to a trade-off...
arXiv:2602.19577v1 Announce Type: new Abstract: Autonomous odor source localization remains a challenging problem for aerial robots due to turbulent airflow, sparse and delayed sensory signals,...
arXiv:2602.19580v1 Announce Type: new Abstract: We introduce Leap+Verify, a framework that applies speculative execution -- predicting future model weights and validating predictions before acceptance --...
arXiv:2602.19582v1 Announce Type: new Abstract: Extensive research demonstrates that Deep Reinforcement Learning (DRL) models are susceptible to adversarially constructed inputs (i.e., adversarial examples), which can...
arXiv:2602.19583v1 Announce Type: new Abstract: Comparative evaluation of several systems is a recurrent task in researching. It is a key step before deciding which system...
arXiv:2602.19584v1 Announce Type: new Abstract: Despite the success of machine learning (ML) in surrogate modeling, its use in radiation dose assessment is limited by safety-critical...
arXiv:2602.19585v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) integrates language, visual, and acoustic modalities to infer human sentiment. Most existing methods either focus on...
arXiv:2602.19587v1 Announce Type: new Abstract: Power system operators are increasingly deploying Grid Enhancing Technologies (GETs) to mitigate operational challenges such as line and transformer congestion,...
arXiv:2602.19591v1 Announce Type: new Abstract: Small and Medium Enterprises (SMEs) constitute 99.9% of U.S. businesses and generate 44% of economic activity, yet systematically identifying high-potential...
arXiv:2602.19594v1 Announce Type: new Abstract: We introduce ISO-Bench, a benchmark for coding agents to test their capabilities on real-world inference optimization tasks. These tasks were...
arXiv:2602.19595v1 Announce Type: new Abstract: Generating graphs subject to strict structural constraints is a fundamental computational challenge in network science. Simultaneously preserving interacting properties-such as...
arXiv:2602.19596v1 Announce Type: new Abstract: Collaborative perception (CP) enables data sharing among connected and autonomous vehicles (CAVs) to enhance driving safety. However, CP systems are...
arXiv:2602.19597v1 Announce Type: new Abstract: This paper introduces a Bayesian framework that combines Markov chain Monte Carlo (MCMC) sampling, dimensionality reduction, and neural density estimation...
arXiv:2602.19598v1 Announce Type: new Abstract: Eye-tracking-while-reading corpora are a valuable resource for many different disciplines and use cases. Use cases range from studying the cognitive...
arXiv:2602.19603v1 Announce Type: new Abstract: Interoperability across industrial automation systems is a cornerstone of Industry 4.0. To address this need, the OPC Unified Architecture (OPC...
arXiv:2602.19604v1 Announce Type: new Abstract: Secure comparison is a fundamental primitive in multi-party computation, supporting privacy-preserving applications such as machine learning and data analytics. A...
arXiv:2602.19605v1 Announce Type: new Abstract: Multimodal learning aims to capture both shared and private information from multiple modalities. However, existing methods that project all modalities...
arXiv:2602.19606v1 Announce Type: new Abstract: Identifying the vulnerabilities exploited during cyberattacks is essential for enabling timely responses and effective mitigation in software security. This paper...
arXiv:2602.19608v1 Announce Type: new Abstract: Looting at archaeological sites poses a severe risk to cultural heritage, yet monitoring thousands of remote locations remains operationally difficult....
arXiv:2602.19609v1 Announce Type: new Abstract: Reasoning about concurrent programs executed on weak memory models is an inherently complex task. So far, existing proof calculi for...
arXiv:2602.19610v1 Announce Type: new Abstract: We develop a Coordinate Ascent Variational Inference (CAVI) algorithm for Bayesian Mixed Data Sampling (MIDAS) regression with linear weight parameteri...
arXiv:2602.19611v1 Announce Type: new Abstract: Unsupervised Anomaly Detection (UAD) aims to identify abnormal regions by establishing correspondences between test images and normal templates. Existing methods...
arXiv:2602.19612v1 Announce Type: new Abstract: Machine Unlearning (MU) enables Large Language Models (LLMs) to remove unsafe or outdated information. However, existing work assumes that all...
arXiv:2602.19614v1 Announce Type: new Abstract: The adoption of large language models in safety-critical system engineering is constrained by trustworthiness, traceability, and alignment with established verification...