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Structure of QC$_2$D ground state fields at nonzero matter densities
A quantitative investigation into the modification of ground-state field structures in two-color QCD (QC$_2$D) is presented at finite chemical potential. Using lattice simulations with Wilson gauge and fermion actions, we explore the chromo-electromagnetic field strengths under varying matter…
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MVRD-Bench: Multi-View Learning and Benchmarking for Dynamic Remote Photoplethysmography under Occlusion
Remote photoplethysmography (rPPG) is a non-contact technique that estimates physiological signals by analyzing subtle skin color changes in facial videos. Existing rPPG methods often encounter performance degradation under facial motion and occlusion scenarios due to their reliance on static and…
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Approximating inter-point distances in directed Bernoulli graphs
In directed random graphs, in which edges can be assigned to have one of two directions, or perhaps both, the distance between two vertices $v$ and $v'$ can be computed along paths that are directed from $v$ to $v'$, or along paths that are directed from $v'$ to $v$. These two distances are in…
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Improving Safety Alignment via Balanced Direct Preference Optimization
With the rapid development and widespread application of Large Language Models (LLMs), their potential safety risks have attracted widespread attention. Reinforcement Learning from Human Feedback (RLHF) has been adopted to enhance the safety performance of LLMs. As a simple and effective…
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Profound impacts of interlayer interactions in bilayer altermagnetic V2S2O
Two-dimensional altermagnets exhibit exceptional potential for low-power spintronics via nonrelativistic spin splitting and zero net magnetization. Here, we systematically investigate the influence of interlayer interactions on the electronic, magnetic and quantum transport properties of bilayer…
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Option pricing model under the G-expectation framework
G-expectation, as a sublinear expectation, provides a powerful framework for modeling uncertainty in financial markets. Motivated by the need for robust valuation under model uncertainty, this work develops a unified risk-neutral valuation approach within the G-expectation environment, yielding a…
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Probing the Bias of Large-Scale Structure with Unlocalized Fast Radio Bursts
Large-scale structure (LSS) and tracer bias connect observable populations to the cosmic matter distribution. While galaxies are standard tracers, transient events such as gravitational-wave sources can also probe LSS despite large localization uncertainties. Fast radio bursts (FRBs), owing to…
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RC-HEOM Hybrid Method for Non-Perturbative Open System Dynamics
The Hierarchical equations of motion (HEOM) method is an important non-perturbative technique, allowing numerically exact treatment of open quantum systems with strong coupling and non-Markovian memory. However, its encoding of bath memory into auxiliary density operators often limits direct access…
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The Ricci-DeTurck flow on complete manifolds
Based on the framework of Koch-Lamm and tensor heat kernel estimates, we obtain a uniform proof of the short-time existence, uniqueness, and continuous dependence for Ricci flows starting from a complete Riemannian metric with bounded curvature. A new ingredient is an effective continuous…
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Breaking news
This paper examines how regulatory interventions in high-frequency financial markets affect price discovery. We focus on Breaking news, where dynamic circuit breakers trigger trading halts immediately after the release of macroeconomic fundamentals. Within a high-frequency signal-in-noise model, we…
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The Benjamin-Feir instability in KdV-like equations with general dispersion and monomial nonlinearity
Nonlinear waves in dispersive media can be succeptible to modulational instabilities. We examine a category of scalar equations, with general dispersion and monomial nonlinearity, including a large variety of KdV-like equations. For small-amplitude traveling wave solutions, we provide a complete…
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Analysing LLM Persona Generation and Fairness Interpretation in Polarised Geopolitical Contexts
Large language models (LLMs) are increasingly utilised for social simulation and persona generation, necessitating an understanding of how they represent geopolitical identities. In this paper, we analyse personas generated for Palestinian and Israeli identities by five popular LLMs across 640…
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Community Detection on Inhomogeneous Multilayer Networks with Extreme Sparsity
We study layer-specific community detection in an $L$-layer network $\{A^{(l)}\}_{l\in[L]}$ on a common set of $n$ nodes. Because modern networks are constructed from multi-modal data or with different contexts, the community labels $π^{(l)}\in[K]^n$ are layer-dependent and the degree heterogeneity…
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MultiCam: On-the-fly Multi-Camera Pose Estimation Using Spatiotemporal Overlaps of Known Objects
Multi-camera dynamic Augmented Reality (AR) applications require a camera pose estimation to leverage individual information from each camera in one common system. This can be achieved by combining contextual information, such as markers or objects, across multiple views. While commonly cameras are…
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URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
Unsupervised anomaly detection plays a pivotal role in industrial defect inspection and medical image analysis, with most methods relying on the reconstruction framework. However, these methods may suffer from over-generalization, enabling them to reconstruct anomalies well, which leads to poor…
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UAV-DETR: DETR for Anti-Drone Target Detection
Drone detection is pivotal in numerous security and counter-UAV applications. However, existing deep learning-based methods typically struggle to balance robust feature representation with computational efficiency. This challenge is particularly acute when detecting miniature drones against complex…
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L-UNet: An LSTM Network for Remote Sensing Image Change Detection
Change detection of high-resolution remote sensing images is an important task in earth observation and was extensively investigated. Recently, deep learning has shown to be very successful in plenty of remote sensing tasks. The current deep learning-based change detection method is mainly based on…
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Approximating the Shapley Value of Minimum Cost Spanning Tree Games: An FPRAS for Saving Games
In this research, we address the problem of computing the Shapley value in minimum-cost spanning tree (MCST) games. We introduce the saving game as a key framework for approximating the Shapley value. By reformulating MCST games into their saving-game counterparts, we obtain structural properties…
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DROP: Distributionally Robust Optimization for Multi-task Learning in Graphical Models
Gaussian Graphical Models (GGMs) are widely used to infer conditional dependence structures in high-dimensional data. However, standard precision matrix estimators are highly sensitive to data contamination, such as extreme outliers and heavy-tailed noise. In this paper, we propose DROP…
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Rethinking Token-Level Policy Optimization for Multimodal Chain-of-Thought
Multimodal Chain-of-Thought (CoT) reasoning requires large vision-language models to construct reasoning trajectories that interleave perceptual grounding with multi-step inference. However, existing Reinforcement Learning with Verifiable Rewards (RLVR) methods typically optimize reasoning at a…
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