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arXiv:2604.19761v1 Announce Type: new Abstract: Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly…
arXiv:2604.19760v1 Announce Type: new Abstract: We present a simulation-based evaluation of the Inference Headroom Ratio (IHR), a dimensionless diagnostic quantity for characterizing inference stabili…
arXiv:2604.19759v1 Announce Type: new Abstract: Clinical trials require strict adherence to medication protocols, yet dosing errors remain a persistent challenge affecting patient safety and trial int…
arXiv:2604.19758v1 Announce Type: new Abstract: We present ThermoQA, a benchmark of 293 open-ended engineering thermodynamics problems in three tiers: property lookups (110 Q), component analysis (101…
arXiv:2604.19755v1 Announce Type: new Abstract: Anti-money laundering (AML) transaction monitoring generates large volumes of alerts that must be rapidly triaged by investigators under strict audit an…
arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories p…
arXiv:2604.19753v1 Announce Type: new Abstract: We propose a feature-free approach to algorithm selection that replaces hand-crafted instance features with pretrained text embeddings. Our method, Zero…
arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs shoul…
arXiv:2604.19749v1 Announce Type: new Abstract: Equipping LLMs with external tools effectively addresses internal reasoning limitations. However, it introduces a critical yet under-explored phenomenon…
arXiv:2409.07609v2 Announce Type: replace Abstract: Deploying adversarially robust machine learning systems requires continuous trade-offs between robustness, cost, and latency. We present an autonomi…
arXiv:2405.12042v3 Announce Type: replace Abstract: The Messaging Layer security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographi…
arXiv:2604.20596v1 Announce Type: cross Abstract: Federated learning (FL) enables training of a global model while keeping raw data on end-devices. Despite this, FL has shown to leak private user info…
arXiv:2604.20245v1 Announce Type: cross Abstract: Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as n…
arXiv:2604.20211v1 Announce Type: cross Abstract: Logging code plays an important role in software systems by recording key events and behaviors, which are essential for debugging and monitoring. Howe…
arXiv:2604.20062v1 Announce Type: cross Abstract: The rise of IoT devices and the uptake of cloud computing have informed a new era of data-driven intelligence. Traditional centralized machine learnin…
arXiv:2604.20047v1 Announce Type: cross Abstract: Vision Transformers (ViTs) have achieved remarkable success across vision tasks, yet recent studies show they remain vulnerable to backdoor attacks. E…
arXiv:2604.19785v1 Announce Type: cross Abstract: Sensitive information, such as knowledge about an individual's personality, can be can be misused to influence behavior (e.g., via personalized messag…
arXiv:2604.20833v1 Announce Type: new Abstract: As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-pro…
arXiv:2604.20826v1 Announce Type: new Abstract: Phishing attacks remain one of the most prevalent threats to online security, with the Anti-Phishing Working Group reporting over 890,000 attacks in Q3 …
arXiv:2604.20801v1 Announce Type: new Abstract: LLM agents have begun to find real security vulnerabilities that human auditors and automated fuzzers missed for decades, in source-available targets wh…
arXiv:2604.20793v1 Announce Type: new Abstract: Post-quantum cryptographic (PQC) accelerators for ML-KEM (FIPS 203) and ML-DSA (FIPS 204) rely on pipelined Number Theoretic Transform (NTT) stages over…
arXiv:2604.20771v1 Announce Type: new Abstract: The Internet of Vehicles (IoV) is advancing modern transportation by improving safety, efficiency, and intelligence. However, the reliance on the Contro…
arXiv:2604.20765v1 Announce Type: new Abstract: Critical vulnerabilities with Common Vulnerability Scoring System scores of 9.0 or higher pose severe risks to organisations' information systems. Timel…
arXiv:2604.20704v1 Announce Type: new Abstract: Adversarial robustness evaluation underpins every claim of trustworthy ML deployment, yet the field suffers from fragmented protocols and undetected gra…