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430

arXiv:2512.17284v1 Announce Type: new
Abstract: We develop an analytical Stackelberg game framework for optimal resource allocation in a sequential attacker--defender setting with a finite set of assets and probabilistic attacks. The defender commits to a mixed protection strategy, after which the …
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342

arXiv:2512.17710v1 Announce Type: new
Abstract: Software Bill of Materials (SBOM) provides new opportunities for automated vulnerability identification in software products. While the industry is adopting SBOM-based Vulnerability Scanning (SVS) to identify vulnerabilities, we increasingly observe i…
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331

arXiv:2512.17001v1 Announce Type: new
Abstract: This paper presents a Multi-Robot Multi-Source Term Estimation (MRMSTE) framework that enables teams of mobile robots to collaboratively sample gas concentrations and infer the parameters of an unknown number of airborne releases. The framework is bui…
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329

arXiv:2512.17540v1 Announce Type: new
Abstract: Automating code review with Large Language Models (LLMs) shows immense promise, yet practical adoption is hampered by their lack of reliability, context-awareness, and control. To address this, we propose Specification-Grounded Code Review (SGCR), a f…
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322

arXiv:2512.17885v1 Announce Type: cross
Abstract: Magnetic fields are critical at many scales to galactic dynamics and structure, including multiphase pressure balance, dust processing, and star formation. Dynamo action determines their dynamical structure and strength. Simulations of combined larg…
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329

arXiv:2512.17325v1 Announce Type: new
Abstract: We provide causal mechanistic validation that in-context learning (ICL) decomposes into two separable mechanisms: Task Schema (abstract task type recognition) and Binding (specific input-output associations). Through activation patching experiments ac…
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220

arXiv:2412.20878v3 Announce Type: replace
Abstract: We present the first formal correctness proof of Edmonds' blossom shrinking algorithm for maximum cardinality matching in general graphs. We focus on formalising the mathematical structures and properties that allow the algorithm to run in worst-c…
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233

arXiv:2512.17246v1 Announce Type: new
Abstract: With the rapid development of distributed renewable energy, multi-microgrids play an increasingly important role in improving the flexibility and reliability of energy supply. Reinforcement learning has shown great potential in coordination strategies…
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222

arXiv:2507.18242v3 Announce Type: replace
Abstract: Despite their theoretical appeal, totally corrective boosting methods based on linear programming have received limited empirical attention. In this paper, we conduct the first large-scale experimental study of six LP-based boosting formulations, …
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211

arXiv:2512.17109v1 Announce Type: new
Abstract: Training large neural networks and merging task-specific models both exploit low-rank structure and require parameter importance estimation, yet these challenges have been pursued in isolation. Current workflows compute curvature information during tr…
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221

arXiv:2406.00780v2 Announce Type: replace
Abstract: Hybrid model predictive control with both continuous and discrete variables is widely applicable to robotic control tasks, especially those involving contacts with the environment. Due to combinatorial complexity, the solving speed of hybrid MPC c…
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222

arXiv:2507.13717v3 Announce Type: replace
Abstract: Reconfigurable data center networks (DCNs) enhance traditional architectures with optical circuit switches (OCSs), enabling dynamic reconfiguration of inter-pod links, i.e., the logical topology. Optimizing this topology is crucial for adapting to…
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221

A Brazilian study has confirmed that Joseph’s Coat, a plant used for generations in folk medicine, can significantly reduce inflammation and arthritis symptoms in lab tests. Researchers observed less swelling, healthier joints, and signs of tissue protection. Just as important, the extract showed a …
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124

arXiv:2511.09801v2 Announce Type: replace-cross
Abstract: This work extends the recently introduced Alpha-Procrustes family of Riemannian metrics for symmetric positive definite (SPD) matrices by incorporating generalized versions of the Bures-Wasserstein (GBW), Log-Euclidean, and Wasserstein dista…
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119

arXiv:2512.17371v1 Announce Type: new
Abstract: We present GraphCue, a topology-grounded retrieval and agent-in-the-loop framework for automated SDN configuration. Each case is abstracted into a JSON graph and embedded using a lightweight three-layer GCN trained with contrastive learning. The neare…
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111

arXiv:2512.17846v1 Announce Type: new
Abstract: We present Planning as Descent (PaD), a framework for offline goal-conditioned reinforcement learning that grounds trajectory synthesis in verification. Instead of learning a policy or explicit planner, PaD learns a goal-conditioned energy function ov…
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