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arXiv:2604.02504v1 Announce Type: new Abstract: Electric utilities must make massive capital investments in the coming years to respond to explosive growth in demand, aging assets and rising threats f…
arXiv:2604.02500v1 Announce Type: new Abstract: As ongoing research explores the ability of AI agents to be insider threats and act against company interests, we showcase the abilities of such agents …
arXiv:2604.02478v1 Announce Type: new Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for anomaly classification and s…
arXiv:2604.02476v1 Announce Type: new Abstract: This paper examines the role of threshold logic in understanding generative artificial intelligence. Threshold functions, originally studied in the 1960…
arXiv:2604.02434v1 Announce Type: new Abstract: We study structured abstraction-based reasoning for the Abstraction and Reasoning Corpus (ARC) and compare its generalization to test-time approaches. P…
arXiv:2604.02368v1 Announce Type: new Abstract: As Large Language Models (LLMs) exhibit plateauing performance on conventional benchmarks, a pivotal challenge persists: evaluating their proficiency in…
arXiv:2604.02334v1 Announce Type: new Abstract: As large language models (LLM)-driven agents transition from isolated task solvers to persistent digital entities, the emergence of the Agentic Web, an …
arXiv:2603.11029v2 Announce Type: replace Abstract: We resolve an open question of Jain, Raskhodnikova, Sivakumar, and Smith (ICML 2023) by exhibiting a problem separating differential privacy under c…
arXiv:2512.16284v2 Announce Type: replace Abstract: Synthetic data generation is gaining traction as a privacy enhancing technology (PET). When properly generated, synthetic data preserve the analytic…
arXiv:2410.13900v3 Announce Type: replace Abstract: The scrutiny surrounding vote-by-mail (VBM) in the United States has increased in recent years, highlighting the need for a rigorous quantitative fr…
arXiv:2410.13891v3 Announce Type: replace Abstract: Transferable Targeted Attacks (TTAs) face significant challenges due to severe overfitting to surrogate models. Recent breakthroughs heavily rely on…
arXiv:2406.06958v2 Announce Type: replace Abstract: Online advertising relies on a complex and opaque supply chain that involves multiple stakeholders, including advertisers, publishers, and ad-networ…
arXiv:2604.03199v1 Announce Type: cross Abstract: All prior membership inference attacks for fine-tuned language models use hand-crafted heuristics (e.g., loss thresholding, Min-K\%, reference calibra…
arXiv:2604.02617v1 Announce Type: cross Abstract: Scientific and Technical Intelligence (S&TI) analysis requires verifying complex technical claims across rapidly growing literature, where existing ap…
arXiv:2604.02457v1 Announce Type: cross Abstract: Automatic license plate reader (ALPR) systems are widely deployed to identify and track vehicles. While prior work has demonstrated vulnerabilities in…
arXiv:2604.02366v1 Announce Type: cross Abstract: In a companion paper, we prove that the Burau-Lyapunov exponent LE discriminates focused from dispersed privilege escalation ratchets in cloud IAM gra…
arXiv:2604.03205v1 Announce Type: new Abstract: The rapid adoption of the Internet of Medical Things (IoMT) is transforming healthcare by enabling seamless connectivity among medical devices, systems,…
arXiv:2604.03131v1 Announce Type: new Abstract: Tool-augmented AI agents substantially extend the practical capabilities of large language models, but they also introduce security risks that cannot be…
arXiv:2604.03121v1 Announce Type: new Abstract: Kimi K2.5 is an open-weight LLM that rivals closed models across coding, multimodal, and agentic benchmarks, but was released without an accompanying sa…
arXiv:2604.03104v1 Announce Type: new Abstract: Cyber-attacks continue to grow in scale and sophistication, yet existing network intrusion detection approaches lack the semantic depth required for pat…
arXiv:2604.03081v1 Announce Type: new Abstract: LLM-based coding agents extend their capabilities via third-party agent skills distributed through open marketplaces without mandatory security review. …
arXiv:2604.03070v1 Announce Type: new Abstract: Third-party skills extend LLM agents with powerful capabilities but often handle sensitive credentials in privileged environments, making leakage risks …
arXiv:2604.03043v1 Announce Type: new Abstract: In a healthcare environment, the healthcare interoperability platforms based on HL7 FHIR allow concurrent, asynchronous access to a set of shared patien…
arXiv:2604.02837v1 Announce Type: new Abstract: Agent Skills is an emerging open standard that defines a modular, filesystem-based packaging format enabling LLM-based agents to acquire domain-specific…