Academic
arXiv:2602.18486v1 Announce Type: new Abstract: Classical radar detection techniques rely on adaptive detectors that estimate the noise covariance matrix from target-free secondary data. While effective …
arXiv:2602.18493v1 Announce Type: new Abstract: Long-context LLMs and Retrieval-Augmented Generation (RAG) systems process information passively, deferring state tracking, contradiction resolution, and evidence aggregation to query …
arXiv:2602.18515v1 Announce Type: new Abstract: Partial differential equations (PDEs) form a central component of scientific computing. Among recent advances in deep learning, evolutionary neural networks …
arXiv:2602.18518v1 Announce Type: new Abstract: Content safety teams need metrics that reflect what users actually experience, not only what is reported. We study prevalence: the …
arXiv:2602.18519v1 Announce Type: new Abstract: Traditional approaches to measuring visual exploratory behavior in soccer rely on counting visual exploratory actions (VEAs) based on rapid head …
arXiv:2602.18521v1 Announce Type: new Abstract: Continuous stress forecasting could potentially contribute to lifestyle interventions. This paper presents a novel, explainable, and individualized approach for stress …
arXiv:2602.18523v1 Announce Type: new Abstract: Grokking -- the abrupt transition from memorization to generalization long after near-zero training loss -- has been studied mainly in …
arXiv:2602.18528v1 Announce Type: new Abstract: Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary domains, where either or …
arXiv:2602.18531v1 Announce Type: new Abstract: The energy management problem in the context of smart grids is inherently complex due to the interdependencies among diverse system …
arXiv:2602.18572v1 Announce Type: new Abstract: Reliable real estate price indicators are typically published at city level and low frequency, limiting their use for neighborhood-scale monitoring …
arXiv:2602.18581v1 Announce Type: new Abstract: Despite their apparent diversity, modern machine learning methods can be reduced to a remarkably simple core principle: learning is achieved …
arXiv:2602.18584v1 Announce Type: new Abstract: Targeted data selection has emerged as a crucial paradigm for efficient instruction tuning, aiming to identify a small yet influential …
