Learning-Augmented Online Allocation under Unreliable Advice: Robustness, Exposure Fairness, and Distribution Shift

arXiv:2608.26889 · cs.AI · Submitted 2026-08-27 · Read on arXiv

cs.AI

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

• Robustness — 11× in this paper · explained in 5 episodes
• Distribution Shift — 7× in this paper · explained in 5 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection