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arXiv:2604.05070v1 Announce Type: new Abstract: Simulation is essential for autonomous driving, yet current frameworks often model vehicles as rigid assets and fail to capture part-level articulation.…
arXiv:2604.05018v1 Announce Type: new Abstract: Synthesizing unstructured research materials into manuscripts is an essential yet under-explored challenge in AI-driven scientific discovery. Existing a…
arXiv:2604.04941v1 Announce Type: new Abstract: Many combinatorial optimisation problems hide algebraic structures that, once exposed, shrink the search space and improve the chance of finding the glo…
arXiv:2604.04940v1 Announce Type: new Abstract: Designing effective heuristics for NP-hard combinatorial optimization problems remains a challenging and expertise-intensive task. Existing applications…
arXiv:2604.04939v1 Announce Type: new Abstract: The paper considers a new quantitative-qualitative proximity measure for the features of information objects, where data enters a common information res…
arXiv:2604.04938v1 Announce Type: new Abstract: Metacognition, understood as the monitoring and regulation of one's own cognitive processes, is inherently sequential: an agent evaluates an internal st…
arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researc…
arXiv:2604.04993v1 Announce Type: cross Abstract: We introduce the Hiremath Early Detection (HED) Score, a principled, measure-theoretic evaluation criterion for quantifying the time-value of informat…
arXiv:2604.04978v1 Announce Type: cross Abstract: Claude Code's auto mode is the first deployed permission system for AI coding agents, using a two-stage transcript classifier to gate dangerous tool c…
arXiv:2604.04977v1 Announce Type: cross Abstract: Software supply chain security compromises often stem from cascaded interactions of vulnerabilities, for example, between multiple vulnerable componen…
arXiv:2604.06148v1 Announce Type: new Abstract: The governance of artificial intelligence has a blind spot: the machine identities that AI systems use to act. AI agents, service accounts, API tokens, …
arXiv:2604.06101v1 Announce Type: new Abstract: In the light of the growing connectivity and sensitivity of industrial data, cyberattacks and data breaches are becoming more common in the Industrial I…
arXiv:2604.06100v1 Announce Type: new Abstract: Post-quantum migration in TLS 1.3 should not be understood as a flat substitution problem in which one signature algorithm is replaced by another and de…
arXiv:2604.06095v1 Announce Type: new Abstract: Code decompilation analysis is a fundamental yet challenging task in malware reverse engineering, particularly due to the pervasive use of sophisticated…
arXiv:2604.06092v1 Announce Type: new Abstract: The value of proof-of-work cryptocurrencies critically depends on miners having incentives to follow the protocol. However, the Bitcoin mining protocol …
arXiv:2604.06019v1 Announce Type: new Abstract: The advancement of Large Language Models (LLMs) has raised concerns regarding their dual-use potential in cybersecurity. Existing evaluation frameworks …
arXiv:2604.05969v1 Announce Type: new Abstract: The Model Context Protocol (MCP), introduced by Anthropic in November 2024 and now governed by the Linux Foundation's Agentic AI Foundation, has rapidly…
arXiv:2604.05872v1 Announce Type: new Abstract: The deployment of large language models (LLMs) in Swiss financial and regulatory contexts demands empirical evidence of both production reliability and …
arXiv:2604.05809v1 Announce Type: new Abstract: Multimodal pretrained models are vulnerable to backdoor attacks, yet most existing methods rely on visual or multimodal triggers, which are impractical …
arXiv:2604.05793v1 Announce Type: new Abstract: In LLM/VLM agents, prompt privacy risk propagates beyond a single model call because raw user content can flow into retrieval queries, memory writes, to…
arXiv:2604.05770v1 Announce Type: new Abstract: Anti-forensics includes a growing set of techniques designed to obstruct forensic analysis. While cybercriminals increasingly rely on these methods, the…
arXiv:2604.05719v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has created new opportunities for Automated Penetration Testing (AutoPT), spawning numerous framew…
arXiv:2604.05674v1 Announce Type: new Abstract: Cyber-physical systems often contend with incomplete architectural documentation or outdated information resulting from legacy technologies, knowledge m…
arXiv:2604.05642v1 Announce Type: new Abstract: This paper studies the creation of textual descriptions of user activities and interactions on smartphones. Our approach of referring to encrypted mobil…