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Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational cost using a single decision framework. While recent work has focused on reinforcement learning (RL) for maintenance scheduling, direct comparisons with planning approach...
Findings identify evidence localization and fine-grained type discrimination as distinct challenges and show that compact supervised encoders are strong baselines for this task.
Results show consistent gains from lightweight domain adaptation on both held-out synthetic data and real-world recordings, confirming that synthetic data generation combined with LoRA-based fine-tuning is an effective and computationally practical strategy for improving ASR accuracy in specialized technical domains wh...
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