Vol. 1 No. 2 (2026): International Journal of Artificial Intelligence Research

View Vol. 1 No. 2 (2026): International Journal of Artificial Intelligence Research

Published: 2026-04-23

Articles

Research on a Risk Prediction Model for Hypoxemia During Spontaneous Breathing Intravenous Anesthesia Using Endoscopic Nasal Masks Based on Machine Learning Algorithms

Maria Hernandez
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Accelerating Autonomous System Evaluation via Reinforcement Learning Driven Large Language Model Agents for Real Time Performance Diagnostics and Strategy Refinement

Arthur Redcliffe, Paul Sutherland
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Governing Autonomous Agent Intelligence through Decentralized Policy Enforcement Frameworks for Robust Alignment and Accountability in Multi-Agent Ecosystems

Richard Carmichael
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Advancing Model Transparency via Self-Explaining Deep Learning Architectures Integrating Symbolic Logic and Neural Representations

Timothy Langford
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Accelerating Autonomous Protein Sequence Engineering via Generative Multi-Agent Systems Leveraging High-Throughput Structural Bioinformatic Validation Pipelines

Shawn Harrington
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Advancing Backdoor Attack Detection in Transformer Models using Feature Squeezing and Statistical Anomaly Filtering Techniques

Simon Grant
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Estimating Individualized Treatment Effects in Clinical Trials via Causal Survival Analysis Integrating Counterfactual Reasoning and Deep Latent Variable Models

Raymond Redcliffe
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Quantifying Systematic Financial Risk via Generative Adversarial Networks Synthesizing Correlated Extreme Market Scenarios for Enhanced Stress Testing Reliability

Lucas Wainwright, Keith Pennington
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Optimizing Protein Sequence Engineering through Autonomous Agent Systems Leveraging Reinforcement Learning and High Throughput Structural Bioinformatic Pipelines

David Prescott
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Bridging the Gap between Human Intuition and Machine Logic using Visual Analytics for Interactive Model Behavior Interpretation

Trevor Hollis
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AI-Augmented Cross-Domain Resource Orchestration in Next-Generation Mobile Networks

Marcus T. Chen, Sarah J. Williams, David L. Hoffmann
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Advancing Adaptive Quantitative Trading Systems through Continual Learning Architectures Designed for Non-Stationary Financial Distribution Shifting Environments

Carl Linton
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Facilitating Zero Shot Decision Generalization through Conservative Offline Reinforcement Learning and Semantic Policy Pre training with Large Language Models

Arthur Westbrook
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Goal Drift and Emergent Misalignment in Multi-Agent Large Language Model Systems

Benjamin Redford, Julian V. Thorne
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Quantifying Model Vulnerabilities through Automated Red Teaming Frameworks Leveraging Generative Adversarial Reasoning

Raymond Redford, William Blackwell
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Optimizing Algorithmic Trading Strategies via Multi Agent Reinforcement Learning Architectures Integrating Market Microstructure Dynamics and Competitive Game Logic

Dennis Westbrook
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Enhancing System Robustness through Adversarial Reinforcement Learning and Large Language Model Reasoning for Automated Vulnerability Assessment in Complex Decision Environments

Derek Ashcroft
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Behavioral Governance for AI Agents: Integrating Dynamic Oversight into Autonomous Decision Systems

Colin Wexford
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Evaluating the Reliability of Post Hoc Explanation Methods under Adversarial Perturbations in High-Stakes Predictive Modeling

Blake Kensington
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Advancing Functional Genomic Interpretation through Large Language Model Empowered Agents Navigating Hierarchical Biological Knowledge Graphs and Regulatory Networks

Matthew Remington
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Strengthening Edge AI Security via Differential Privacy and Hardware Level Trust Execution Environments for Sensitive Data Processing

Patrick Ellsworth
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Advancing Functional Genomic Interpretation via Multi-Agent Collaborative Architectures Integrating Large Language Model Reasoning and Hierarchical Biological Knowledge Graphs

Derek Whitman
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Enhancing Algorithmic Trust through Counterfactual Explanation Frameworks for Auditing Black Box Neural Networks in Critical Decision Systems

Leon Prescott
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Simulating Cellular Trajectory Dynamics through Multi-Agent Reinforcement Learning Architectures Integrating Single-Cell Transcriptomic Landscapes and Spatial Constraints

Zachary Ellsworth
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Securing Deep Learning Infrastructures via Certified Robustness Training against Adaptive Adversarial Attacks in Real Time Environments

Gerald Lockwood
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Understanding Information Framing and Its Psychological Effects through Large-Scale Text Analysis

Marcus Chen
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Predicting Dynamic Market Liquidity via Temporal Graph Neural Networks Integrating Limit Order Book Evolution and Cross Asset Spillover Effects

Patrick Nolan, Keith Ellison
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Refining Decision Boundaries via Stepwise Reinforcement Learning from Human Feedback Integrating Intermediate Logic Verification and Large Language Model Reasoning

William Whitaker
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From Rule Compliance to Value-Constrained Agency: A New Paradigm for AI Governance

Oscar Langford
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Improving Interpretability in Large Language Models through Layer Wise Relevance Propagation for Identifying Latent Reasoning Biases

Miles Redcliffe, Matthew Blackwood
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Enhancing Predictive Robustness in Financial Time Series Analysis through Cross-Modal Transformer Networks Leveraging Denoised Wavelet Representations and Latent Factor Modeling

Daniel Grant
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Empowering Sequential Decision Intelligence via Long Term Memory Augmentation and Recurrent Reinforcement Learning within Large Language Model Architectures

Jason Brooks, Stephen Hensley
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Sandbox Boundary Violations in Autonomous Agents: Technical Risks and Governance Implications

Elliot Redford
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Mitigating Data Poisoning Risks in Federated Learning through Blockchain Integrated Verifiable Model Aggregation Protocols

Aaron Whitaker
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