Mahalanobis
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A Novel Detection Method for Single-RF MIMO-OFDM Systems
arXiv:2606.03311v1 Announce Type: new Abstract: A novel detection method based on maximum-likelihood (ML) detection leveraging Mahalanobis distance is proposed for single-radio-frequency (RF) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. It can enhance bit error rate (BER) performance and is based on the observation that when using reconfigurable antennas (such as electronically steerable parasitic array radiators (ESPARs) to create a...
Learning Hyperspherical Time-Frequency Representations for Time-Series Out-of-Distribution Detection
arXiv:2605.31155v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection for time-series data remains comparatively underexplored compared to vision and language, with a limited principled understanding of how supervised time-series representations can be leveraged for reliable detection under distributional shifts. This work formulates time-series OOD detection as representation learning with hyperspherical embeddings, where class-conditional structure is induced by a von...
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
arXiv:2512.05291v3 Announce Type: replace Abstract: Actor-critic (AC) methods are a cornerstone of reinforcement learning (RL) but offer limited interpretability. Current explainable RL methods seldom use state attributions to assist training. Rather, they treat all state features equally, thereby neglecting the heterogeneous impacts of individual state dimensions on the reward.
An Embarrassingly Simple Detector for Model Extraction Attacks in Large Language Model API Traffic
Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed through hosted APIs, making model extraction a practical threat to model ownership and service security. However, individual extraction queries often resemble benign requests, and existing evaluations often focus on single-query anomaly scoring or pure benign-versus-attacker user settings. We formulate model extraction monitoring as benign-calibrated traffic-window distribution testing and show that an...
Prospects for Astrobiology and Technosignature Searches with the Vera C. Rubin Observatory Legacy Survey of Space and Time
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CLIF: Cross-layer LEO-ISL Fingerprinting for Physical and Network Attack Detection in Dense LEO Constellations
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Cone-Compatible Monge Geometry for High-Dimensional Ordered Optimal Transport
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Disambiguation of two-tone images reveals semantic contributions to object recognition in the EEG
Electrophysiological responses to visual objects carry information about stimulus identity and semantic category, but it remains difficult to know whether such information represents semantic knowledge or merely regularities in physical image features. Here, we presented two-tone images while recording EEG to dissociate the learned semantic concept from physical stimulus properties in the electrophysiological signal. Seventeen healthy participants completed a semantic disambiguation...
Channel Chart Location Privacy Based on Geo-Indistinguishability
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CLIF: Cross-layer LEO-ISL Fingerprinting for Physical and Network Attack Detection in Dense LEO Constellations
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