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Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Certified to Drive: A Policy Proposal for Mandatory Train...
2025-04-11 · via cs.IT updates on arXiv.org

Although the Boeing 737 Max incidents resulted from a mix of design shortcomings, regulatory oversights, and systemic issues, they also highlight a critical gap in pilot training on managing automated systems during abnormal conditions. This example demonstrates the urgent need for focused, concise training on human-automation interaction - a need that is equally critical for operators of Level 2 ADAS-equipped vehicles, as discussed in detail later in this article. The lack of structured education for semi-automated vehicle operators mirrors similar risks in other industries, where formal training is critical for safe operation. Two policy recommendations are proposed. First, governments should create concise, official resources in accessible and official format to educate drivers on system capabilities and limitations. Second, mandatory training and certification programs should be introduced, combining theoretical and hands-on components to prepare drivers for real-world scenarios. These measures will improve driver understanding, reduce misuse, and foster public trust in semi-automated vehicle technologies. By addressing the knowledge gap, policymakers can ensure a safer, more responsible transition to automation, maximizing its benefits while minimizing risks to public safety.