cyberintel.kalymoon.com · 2828 articles · updated every 4 hours · grows forever
arXiv:2603.27270v1 Announce Type: new Abstract: Credal sets, i.e., closed convex sets of probability measures, provide a natural framework to represent aleatoric and epistemic uncertainty in machine l…
arXiv:2603.27195v1 Announce Type: new Abstract: Designing microstructures that satisfy coupled cross-physics objectives is a fundamental challenge in material science. This inverse design problem invo…
arXiv:2603.27169v1 Announce Type: new Abstract: Recent research has demonstrated the effectiveness of large language models (LLMs) in solving combinatorial optimization problems (COPs) by representing…
arXiv:2603.27164v1 Announce Type: new Abstract: The foundational pretraining phase determines a model's capability ceiling, as post-training struggles to overcome capability foundations established du…
arXiv:2603.27150v1 Announce Type: new Abstract: Large language models (LLMs) have revolutionized medical reasoning tasks, yet single-agent systems often falter on complex, interdisciplinary problems r…
arXiv:2603.27116v1 Announce Type: new Abstract: Every major AI memory system in production today organises information by meaning. That organisation enables generalisation, analogy, and conceptual ret…
arXiv:2603.27076v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for automated tutoring, but their reliability in structured symbolic domains remains unclear. We stud…
arXiv:2603.26996v1 Announce Type: new Abstract: We present FormalProofBench, a private benchmark designed to evaluate whether AI models can produce formally verified mathematical proofs at the graduat…
arXiv:2603.26983v1 Announce Type: new Abstract: Art. 50 II of the EU Artificial Intelligence Act mandates dual transparency for AI-generated content: outputs must be labeled in both human-understandab…
arXiv:2603.26948v1 Announce Type: new Abstract: Existing approaches for predictive process monitoring are sub-symbolic, meaning that they learn correlations between descriptive features and a target f…
arXiv:2603.26944v1 Announce Type: new Abstract: Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring. Existing data-driven approaches learn correlatio…
arXiv:2603.26838v1 Announce Type: new Abstract: This paper surveys uncertainty-aware explainable artificial intelligence (UAXAI), examining how uncertainty is incorporated into explanatory pipelines a…
arXiv:2603.26782v1 Announce Type: new Abstract: Text-to-level generation aims to translate natural language descriptions into structured game levels, enabling intuitive control over procedural content…
arXiv:2603.26765v1 Announce Type: new Abstract: The efficiency of game engines and policy optimization algorithms is crucial for training reinforcement learning (RL) agents in complex sequential decis…
arXiv:2603.28654v1 Announce Type: new Abstract: Network security threats in embedded systems pose significant challenges to critical infrastructure protection. This paper presents a comprehensive fram…
arXiv:2603.28626v1 Announce Type: new Abstract: The transition to a cloud-native 5G Service-Based Architecture (SBA) improves scalability but exposes control-plane signaling to emerging quantum threat…
arXiv:2603.28551v1 Announce Type: new Abstract: Personalized computer-use agents are rapidly moving from expert communities into mainstream use. Unlike conventional chatbots, these systems can install…
arXiv:2603.28434v1 Announce Type: new Abstract: The synergy between Federated Learning and blockchain has been considered promising; however, the computationally intensive nature of contribution measu…
arXiv:2603.28313v1 Announce Type: new Abstract: Recently, a two-way RFID authentication protocol based on the AM-SUEO-DBLTKM variable matrix encryption algorithm was proposed for low-cost mobile RFID …
arXiv:2603.28309v1 Announce Type: new Abstract: Vulnerability detection in C programs is a critical challenge in software security. Although large language models (LLMs) achieve strong detection perfo…
arXiv:2603.28166v1 Announce Type: new Abstract: Equipping LLM agents with real-world tools can substantially improve productivity. However, granting agents autonomy over tool use also transfers the as…
arXiv:2603.28143v1 Announce Type: new Abstract: As machine learning as a service (MLaaS) gains increasing popularity, it raises two critical challenges: privacy and verifiability. For privacy, clients…
arXiv:2603.28043v1 Announce Type: new Abstract: Illicit online promotion is a persistent threat that evolves to evade detection. Existing moderation systems remain tethered to platform-specific superv…
arXiv:2603.28013v1 Announce Type: new Abstract: We present a stage-decomposed analysis of prompt injection attacks against five frontier LLM agents. Prior work measures task-level attack success rate …