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Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support
May 10, 2026Elyson A. De La Cruz, Rishikesh Sahay, Md Rasel Al MamunArtificial Intelligence Governance Governed
Emergent Communication for Co-constructed Emotion Between Embodied Agents via Collective Predictive Coding
May 10, 2026Zehang Zhang, Nguyen Le Hoang, Tadahiro Taniguchi +1Predictive Coding Emotion
Hidden Error Awareness in Chain-of-Thought Reasoning: The Signal Is Diagnostic, Not Causal
May 10, 2026Aojie Yuan, Zhiyuan Julian Su, Haiyue Zhang +2Chain-of-Thought Reasoning Reasoning Errors
LASSA Architecture-Based Autonomous Fault-Tolerant Control of Unmanned Underwater Vehicles
May 10, 2026Hong Chen, Zixiang Tang, Yuanbao Chen +1Autonomous Underwater Vehicles Iterative Reinforcement Learning
SEMASIA: A Large-Scale Dataset of Semantically Structured Latent Representations
May 10, 2026Mario Edoardo Pandolfo, Enrico Grimaldi, Lorenzo Marinucci +4Latent Representation Latent Representation Alignment
fmxcoders: Factorized Masked Crosscoders for Cross-Layer Feature Discovery
May 10, 2026Andreas D. Demou, Panagiotis Koromilas, James Oldfield +2Cross-Layer Interactions Cross-Attention
A Controlled Diagnostic Study of Hardware-Induced Distortions in Hardware-Aware Training
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Sparsity Moves Computation: How FFN Architecture Reshapes Attention in Small Transformers
May 10, 2026Gabriel Smithline, Chris MascioliTransformer Attention Feed-Forward Network
Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoning
May 10, 2026Lin Li, Jiawei Huang, Qihao Quan +7Time-Series Classification Few-Shot Learning
What Happens Before Decoding? Prefill Determines GUI Grounding in VLMs
May 10, 2026Jiaping Lin, Fei Shen, Junzhe Li +4Attention-Guided Transunet Visual Grounding
Position: Avoid Overstretching LLMs for every Enterprise Task
May 10, 2026Kuldeep Singh, Anson Bastos, Isaiah Onando Mulang'Large Language Model Performance Workflow Automation and Optimization
Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective
May 10, 2026Akihito Taya, Yuuki Nishiyama, Kaoru SezakiFederated Learning Distributional Learning
The Wittgensteinian Representation Hypothesis: Is Language the Attractor of Multimodal Convergence?
May 10, 2026Zhaoyang Zhang, Run Shao, Dongyue Wu +4Multi-Modal Representation Learning Convergence
RuPLaR : Efficient Latent Compression of LLM Reasoning Chains with Rule-Based Priors From Multi-Step to One-Step
May 10, 2026Xiaocheng Luo, Kang Wang, Zaifu Zhan +2Large Language Model Reasoning Latent Reasoning Tokens
Perceptual Asymmetry Between Hue Categories: Evidence from Human Color Categorization
May 10, 2026Elnara Kadyrgali, Nuray Toganas, Muragul Muratbekova +1Asymmetry
Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning
May 10, 2026Seungwoo KumGraph Neural Networks Heterogeneous Graph Transformers
Reinforcement Learning Measurement Model
May 10, 2026Wenqian Xu, Feng JiPsychometrics
Towards Conversational Medical AI with Eyes, Ears and a Voice
May 10, 2026Meet Shah, Jason Gusdorf, Anil Palepu +50Ear
Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation
May 9, 2026Lei Ma, Suhani Chaudhary, Ethan Shanbaum +5Anomaly Detection Localization Methods
Kinetic theory for Transformers and the lost-in-the-middle phenomenon
May 9, 2026Mitia Duerinckx, Borjan Geshkovski, Stefano RossiMean-Field Limit Causal Attention
Emergent Semantic Role Understanding in Language Models
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Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan
May 9, 2026Ahan Chatterjee, Matthias Schöffel, Matthias Aßenmacher +2Grammaticality Latin
Evaluating Federated Learning approaches for mammography under breast density heterogeneity
May 9, 2026Gonzalo Iñaki Quintana, Franco Martin Di Maria, Laurence VancambergFederated Learning Mammography
Methods for Formal Verification of Agent Skills: Three Layers Toward a Mechanically Checkable Capability-Containment Proof
May 9, 2026Alfredo MetereReusable Agent Skills Formal Verification
IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization
May 9, 2026Jiayun Li, Dejian Gong, Georgia ChalvatzakiTrajectory Optimization Model Predictive Control
AI Native Asset Intelligence
May 9, 2026Gal Engelberg, Leon Goldberg, Konstantin Koutsyi +3Artificial Intelligence Safety
Dynamic Meta-Metrics: Source-Sentence Conditioned Weighting for MT Evaluation
May 9, 2026Luke Zhang, Justin Vasselli, Aditya Khan +2Neural Machine Translation Models Evaluation Metrics
Predicting Plasticity in Deep Continual Learning: A Theoretical Perspective
May 9, 2026Jiuqi Wang, Jayanth Srinivasa, Claire Chen +3Plasticity Efficient Continual Learning
Evaluating Pragmatic Reasoning in Large Language Models: Evidence from Scalar Diversity
May 9, 2026Ye-eun ChoDiversity
A Quantum Inspired Variational Kernel and Explainable AI Framework for Cross Region Solar and Wind Energy Forecasting
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May 10, 2026 · cs.CRJ/K move · Enter open · S save

Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support

Elyson A. De La Cruz, Rishikesh Sahay, Md Rasel Al Mamun

Department of Artificial Intelligence, University of the Cumberlands, Williamsburg, KY, USA · Department of Management Information Systems, University of Illinois Springfield, Springfield, IL, USA

Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding agents into high-risk operational functions without weakening accountability, privacy, cost discipline, or auditability. The central message of this study is that AI-assisted operational decision support should be managed as a governed engineering capability before it is scaled as automation. Security operations centers (SOCs) provide a suitable setting because they combine privileged telemetry, specialist expertise, software repositories, cloud services, and evidence-sensitive decisions. This study uses Kusto Query Language (KQL) and Microsoft Azure security capabilities as a bounded technical instantiation of that broader engineering management problem. KQL is read-only in ordinary query use, but read-only does not mean risk-free: AI-assisted queries can still create privacy, cost, performance, schema-validity, and decision-quality risks through broad scans, sensitive-field exposure, stale intelligence, and misleading interpretations. Using design science research, the study develops a governed AI query-broker artifact that separates AI planning from operational execution through schema-grounded retrieval, approved templates, policy validation, read-only adapters, normalized outputs, auditable agent traces, and engineering review board gates. The contribution is not a new KQL technique, security product, or detection algorithm. Rather, the study contributes a management framework for governing AI-assisted operational decision support in high-risk digital infrastructure by specifying design propositions, role accountability, maturity stages, quality gates, evaluation criteria, and evidence boundaries.

Artificial Intelligence Governance Governed Decision Support Engineering

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