arXiv:2602.06206v1 Announce Type: new Abstract: This paper develops a framework for analyzing UAV-enabled short-packet communication, leveraging fluid antenna system (FAS)-assisted relaying networks. Operating in the short-packet regime and focusing on challenging urban environments, we derive novel, closed-form expressions for the block error rate (BLER). This is achieved by modeling the spatially correlated Nakagami-$m$ fading link via a tractable eigenvalue-based approach. A high-signal-to-noise ratio (SNR) asymptotic analysis is also presented, revealing the system’s fundamental diversity order. Building on this […]

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In side-channel analysis, simple power analysis (SPA) is a widely used technique for recovering secret information by exploiting differences between operations in traces. However, in realistic measurement environments, SPA is often hindered by noise, temporal misalignment, and weak or transient leakage, which obscure secret-dependent features in single or very few power traces. In this paper, we provide a systematic analysis of moving-skewness-based trace preprocessing for enhancing asymmetric leakage characteristics relevant to SPA. The method computes local skewness within […]

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arXiv:2602.18528v1 Announce Type: new Abstract: Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary domains, where either or both modalities can be distributionally shifted, which hampers online cross-modal learning and eventually leads to poor accuracy. While previous works have tackled this problem, we find that SOTA methods suffer from catastrophic forgetting, where the model’s performance drops well below the source model due to continual parameter updates at test-time. In this work, […]

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arXiv:2601.09725v1 Announce Type: new Abstract: Punctuation plays a critical role in resolving semantic and structural ambiguity in written language. Machine Translation (MT) systems are now widely applied across diverse domains and languages, including many low-resource settings. In this work, we focus on Marathi, a low- to middle-resource language. We introduce Vir=am, the first diagnostic benchmark for assessing punctuation robustness in English-to-Marathi machine translation, consisting of 54 manually curated, punctuation-ambiguous instances. We evaluate two primary strategies for enhancing reliability: […]

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Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, […]

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Anthropic is officially entering its ‘Thinking’ era. Today, the company announced Claude 4.6 Sonnet, a model designed to transform how devs and data scientists handle complex logic. Alongside this release comes Improved Web Search with Dynamic Filtering, a feature that uses internal code execution to verify facts in real-time. https://www.anthropic.com/news/claude-sonnet-4-6 Adaptive Thinking: A New Logic Engine The core update in Claude 4.6 Sonnet is the Adaptive Thinking engine. Accessed via the extended thinking API, this allows the model […]

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arXiv:2602.18474v1 Announce Type: new Abstract: The contemporary governance discourse on Artificial Intelligence often emphasizes catastrophic loss-of-control scenarios. This article suggests that such framing may obscure a more immediate failure mode: chancellorization, or the gradual hollowing out of sovereignty through administrative mediation. In high-throughput, digitally legible organizations, AI-mediated decision support can reduce the probability that failures become publicly legible and politically contestable, even when underlying operational risk does not decline. Drawing on the institutional history of Imperial China, the […]

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To minimize cybersecurity risks in weapon systems, the implementation of the Ko-rean Risk Management Framework (K-RMF) has become essential. However, a significant ‘strategic gap’ exists between high-level RMF controls and technical MITRE ATT&CK techniques, rendering manual mapping labor-intensive. This study proposes an automated mitigation-driven pipeline that integrates Sentence-BERT (SBERT) with the struc-tural defense relationships of the ATT&CK knowledge graph. To address the data cover-age limitations of the CTID silver standard, we introduce Recall@restricted as a calibrated performance metric. […]

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