A Multi-level Information Integration Framework for Physically Verifiable Fault Diagnosis of Rotating Machinery

arXiv:2607.22797 · cs.LG, cs.AI · Submitted 2026-07-24 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-07-24

Updated: 2026-09-24

Terminology

• Accuracy — 51× in this paper · explained in 1 episode
• Transformer — 16× in this paper · explained in 2 episodes
• Fine-Tuning — 14× in this paper · explained in 5 episodes
• Adaptation — 11× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• AUROC — 8× in this paper · explained in 2 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Uncertainty Quantification — 5× in this paper · explained in 8 episodes
• Interpretability — 4× in this paper · explained in 15 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Actionability — 3× in this paper · explained in 3 episodes
• Domain Adaptation — 3× in this paper · explained in 5 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Verifiability — 3× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Case Western Reserve University — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Multimodal Reasoning — 2× in this paper · explained in 5 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Calibration Failure — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Dynamic Weighting — 1× in this paper · explained in 3 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• SHAP values — 1× in this paper · explained in 2 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• State Space Models (SSMs) — 1× in this paper · explained in 4 episodes

Sources

• A Unified Approach to Interpreting Model Predictions
• A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
• Energy-based Out-of-distribution Detection
• Selective Classification for Deep Neural Networks

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