arXiv:2605.00366v4 Announce Type: replace-cross
Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit strong storage capabilities, but the dynamical and…
arXiv:2602.11354v3 Announce Type: replace
Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily…
arXiv:2606.31755v1 Announce Type: cross
Abstract: Research on artificial intelligence (AI) in the public sector often treats “AI” as a single category, neglecting technical distinctions between…
arXiv:2606.31991v1 Announce Type: cross
Abstract: The tendency of large generative models to memorize training data makes sample verification critical for privacy auditing and copyright enforcement….
arXiv:2606.30429v2 Announce Type: replace
Abstract: Text-to-3D systems can now synthesize a model from a single sentence, yet the result is a shape to render, not a design to edit. We present…
arXiv:2604.18546v2 Announce Type: replace
Abstract: We propose a distributionally robust approach to risk-sensitive estimation of an unknown signal x from an observed signal y. The observation and…
arXiv:2606.10410v2 Announce Type: replace
Abstract: Objective: Accurate classification of physiological signals in real-world deployments is challenged by sensor noise, motion artifacts, and…
arXiv:2606.08691v2 Announce Type: replace
Abstract: Modern data-driven applications increasingly involve learning from multiple heterogeneous sources, where a target dataset is limited but related…
arXiv:2405.01906v3 Announce Type: replace-cross
Abstract: In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is…
arXiv:2510.08762v2 Announce Type: replace
Abstract: Causal inference in spatial domains faces two intertwined challenges: (1) unmeasured spatial factors, such as weather, air pollution, or mobility,…