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arXiv:2604.13206v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly integrated into agentic workflows, their unpredictability stemming from numerical instability has emerg…
arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab…
arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these…
arXiv:2208.13583v3 Announce Type: replace Abstract: Most programs compiled to WebAssembly (Wasm) today are written in unsafe languages like C and C++. Unfortunately, memory-unsafe C code remains unsaf…
arXiv:2604.15115v1 Announce Type: cross Abstract: Most existing Byzantine-robust federated learning (FL) methods suffer from slow and unstable convergence. Moreover, when handling a substantial propor…
arXiv:2604.15063v1 Announce Type: cross Abstract: Gradient inversion attacks threaten client privacy in federated learning by reconstructing training samples from clients' shared gradients. Gradients …
arXiv:2604.14957v1 Announce Type: cross Abstract: Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their per…
arXiv:2604.14865v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and Nu…
arXiv:2604.14717v1 Announce Type: cross Abstract: Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior…
arXiv:2604.14495v1 Announce Type: cross Abstract: Financial institutions face tension between maximizing data utility and mitigating the re-identification risks inherent in traditional anonymization m…
arXiv:2604.14357v1 Announce Type: cross Abstract: Existing language-based information-flow control (IFC) tools face a fundamental tension: Denning-style systems that track explicit and implicit flows …
arXiv:2512.22174v2 Announce Type: cross Abstract: Large Language Models (LLMs) deployed in practical and safety-critical settings are increasingly susceptible to bit-flip faults caused by hardware deg…
arXiv:2604.15249v1 Announce Type: new Abstract: Post-quantum cryptographic accelerators require side-channel resistance evidence for FIPS 140-3 certification. However, exact masking-verification tools…
arXiv:2604.15136v1 Announce Type: new Abstract: Binary analysis increasingly relies on large language models (LLMs) to perform semantic reasoning over complex program behaviors. However, existing appr…
arXiv:2604.15118v1 Announce Type: new Abstract: Permission control vulnerabilities in Non-fungible token (NFT) contracts can result in significant financial losses, as attackers may exploit these weak…
arXiv:2604.15073v1 Announce Type: new Abstract: Increasing system-on-chip (SoC) heterogeneity, deep hardware/software integration, and the proliferation of third-party intellectual property (IP) have …
arXiv:2604.15022v1 Announce Type: new Abstract: Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the routing s…
arXiv:2604.14996v1 Announce Type: new Abstract: The incidence of cybersecurity attacks utilizing social engineering techniques has increased. Such attacks exploit the fact that in every secure system,…
arXiv:2604.14973v1 Announce Type: new Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, brightne…
arXiv:2604.14909v1 Announce Type: new Abstract: Private set intersection (PSI) enables a sender holding a set $Q$ of size $m$ and a receiver holding a set $W$ of size $n$ to securely compute the inter…
arXiv:2604.14685v1 Announce Type: new Abstract: Provenance-based intrusion detection has emerged as a promising approach for analyzing complex attack behaviors through system-level provenance graphs. …
arXiv:2604.14663v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative intrusion detection without raw data exchange, but conventional FL incurs high communication overhead from…
arXiv:2604.14604v1 Announce Type: new Abstract: Modern Large audio-language models (LALMs) power intelligent voice interactions by tightly integrating audio and text. This integration, however, expand…
arXiv:2604.14512v1 Announce Type: new Abstract: Agent communication languages (ACLs) enable heterogeneous agents to share knowledge and coordinate across diverse domains. This diversity demands extens…