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arXiv:2601.18622v1 Announce Type: new Abstract: Over the past decade, Brazil has experienced a decline in vaccination coverage, reversing decades of public health progress achieved through...
arXiv:2601.18623v1 Announce Type: new Abstract: Cross-modal image translation remains brittle and inefficient. Standard diffusion approaches often rely on a single, global linear transfer between domains....
arXiv:2601.18625v1 Announce Type: new Abstract: Text-Based Person Search (TBPS) aims to retrieve pedestrian images from large galleries using natural language descriptions. This task, essential for...
arXiv:2601.18626v1 Announce Type: new Abstract: Natural gradients have long been studied in deep reinforcement learning due to their fast convergence properties and covariant weight updates....
arXiv:2601.18629v1 Announce Type: new Abstract: Real-to-Sim-to-Real technique is gaining increasing interest for robotic manipulation, as it can generate scalable data in simulation while having narrower...
arXiv:2601.18630v1 Announce Type: new Abstract: The escalating global mental health crisis, marked by persistent treatment gaps, availability, and a shortage of qualified therapists, positions Large...
arXiv:2601.18631v1 Announce Type: new Abstract: When humans face problems beyond their immediate capabilities, they rely on tools, providing a promising paradigm for improving visual reasoning...
arXiv:2601.18633v1 Announce Type: new Abstract: Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head...
arXiv:2601.18638v1 Announce Type: new Abstract: Inverse design is a central goal in much of science and engineering, including frequency-selective surfaces (FSS) that are critical to...
arXiv:2601.18639v2 Announce Type: new Abstract: The precise regulation of rotary actuation is fundamental in autonomous robotics, yet practical PID loops deviate from continuous-time theory due...
arXiv:2601.18640v2 Announce Type: new Abstract: Advances in single-cell and spatial transcriptomic technologies have transformed tumor ecosystem profiling at cellular resolution. However, large scale studies on...
arXiv:2601.18641v1 Announce Type: new Abstract: Speech remains one of the most visible yet overlooked vectors of inclusion and exclusion in contemporary society. While fluency is...
arXiv:2601.18642v1 Announce Type: new Abstract: Large language models deployed as autonomous agents face critical memory limitations, lacking selective forgetting mechanisms that lead to either catastrophic...
arXiv:2601.18644v1 Announce Type: new Abstract: The European Central Bank (ECB) is working on the "digital euro", an envisioned retail central bank digital currency for the...
arXiv:2601.18650v1 Announce Type: new Abstract: Machine unlearning, which aims to efficiently remove the influence of specific data from trained models, is crucial for upholding data...
arXiv:2601.18651v1 Announce Type: new Abstract: We study the independent approval model (IAM) for approval elections, where each candidate has its own approval probability and is...
arXiv:2601.18654v1 Announce Type: new Abstract: Generative artificial intelligence (Gen-AI) is reshaping content creation on digital platforms by reducing production costs and enabling scalable output of...
arXiv:2601.18655v1 Announce Type: new Abstract: We propose a quantum rotation diversity (QRD) scheme for optical quantum communication using binary phase-shift-keying displaced squeezed states and homodyne...
arXiv:2601.18661v1 Announce Type: new Abstract: In distributed computing with untrusted workers, the assignment of evaluation indices plays a critical role in determining both privacy and...
arXiv:2601.18664v1 Announce Type: new Abstract: Generative Recommendation (GR) has emerged as a transformative paradigm with its end-to-end generation advantages. However, existing GR methods primarily focus...
arXiv:2601.18670v1 Announce Type: new Abstract: Large-scale video streaming events attract millions of simultaneous viewers, stressing existing delivery infrastructures. Client-driven adaptation reacts slowly to shared congestion,...
arXiv:2601.18672v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have recently demonstrated promising potential in scientific machine learning, partly due to their capacity for grid adaptation...
arXiv:2601.18675v1 Announce Type: new Abstract: We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations without compromising predictive...
arXiv:2601.18676v1 Announce Type: new Abstract: This paper introduces quasi-Monte Carlo latent variable models (QLVMs): a class of deep generative models that are specialized for finding...