ConceptRM: The Quest to Mitigate Alert Fatigue through Consensus-Based Purity-Driven Data Cleaning for Reflection Modelling

Ali Nemati5 days ago23 sec read27 views

The paper introduces ConceptRM, a method for mitigating alert fatigue caused by false alerts from intelligent agents by training reflection models to filter them effectively. By using consensus-based learning and minimal expert annotations, ConceptRM creates high-quality data for model training, significantly improving false alert interception compared to existing methods.

Read the full article at arXiv cs.CL (NLP)

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ConceptRM: The Quest to Mitigate Alert Fatigue through Consensus-Based Purity-Driven Data Cleaning for Reflection Modelling

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