arXiv:2512.10600v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs), as valuable intellectual property, face unauthorized use. Existing protections, such as digital watermarking, are largely passive; they provide only post-hoc ownership verification and cannot actively prevent the illicit use of a…
arXiv:2512.10147v1 Announce Type: new Abstract: Early detection and characterization of coronavirus disease (COVID-19), caused by SARS-CoV-2, remain critical for effective clinical response and public-health planning. The global availability of large-scale viral sequence data presents significant opportunities for computational analysis; however,…
arXiv:2512.10745v1 Announce Type: cross Abstract: Continuous monitoring of blood pressure (BP) and hemodynamic parameters such as peripheral resistance (R) and arterial compliance (C) are critical for early vascular dysfunction detection. While photoplethysmography (PPG) wearables has gained popularity, existing data-driven methods…
arXiv:2512.10152v1 Announce Type: new Abstract: Causal discovery methods have traditionally been developed under two distinct regimes: independent and identically distributed (i.i.d.) and timeseries data, each governed by separate modelling assumptions. In this paper, we argue that the i.i.d. setting can…
arXiv:2512.10825v1 Announce Type: cross Abstract: We consider the design of smoothings of the (coordinate-wise) max function in $mathbb{R}^d$ in the infinity norm. The LogSumExp function $f(x)=ln(sum^d_iexp(x_i))$ provides a classical smoothing, differing from the max function in value by at most…
arXiv:2512.10178v1 Announce Type: new Abstract: In practical deep learning deployment, the scarcity of data and the imbalance of label distributions often lead to semantically uncovered regions within the real-world data distribution, hindering model training and causing misclassification near class boundaries…
arXiv:2512.10935v1 Announce Type: cross Abstract: We present Any4D, a scalable multi-view transformer for metric-scale, dense feed-forward 4D reconstruction. Any4D directly generates per-pixel motion and geometry predictions for N frames, in contrast to prior work that typically focuses on either 2-view…
arXiv:2512.10179v1 Announce Type: new Abstract: High-density surface electromyography (HD-sEMG) provides a noninvasive neural interface for assistive and rehabilitation control, but mapping neural activity to user motor intent remains challenging. We assess a spiking neural network (SNN) as a neuromorphic architecture…
arXiv:2503.24157v4 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have provided new opportunities for decision-making, particularly in the task of automated feature selection. In this paper, we first comprehensively evaluate LLM-based feature selection methods, covering the state-of-the-art…
arXiv:2512.10187v1 Announce Type: new Abstract: We present miniF2F-Dafny, the first translation of the mathematical reasoning benchmark miniF2F to an automated theorem prover: Dafny. Previously, the benchmark existed only in interactive theorem provers (Lean, Isabelle, HOL Light, Metamath). We find that…
