SANE is a new schema-aware benchmark paradigm for text-to-SQL evaluation that demonstrates few-shot LLMs with structured prompting can generate accurate queries on constrained biological data schemas without fine-tuning.
Detection of disturbances and cyber-at tacks in smart grids using explain- able machine learning
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Genetic algorithm feature selection with Extra Trees reduces PMU features from 112 to an average of 27.4 while raising macro-F1 from 0.9118 to 0.9212 and ROC-AUC from 0.9791 to 0.9837 on the MSU/ORNL dataset.
citing papers explorer
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SANE Schema-aware Natural-language Evaluation of Biological Data
SANE is a new schema-aware benchmark paradigm for text-to-SQL evaluation that demonstrates few-shot LLMs with structured prompting can generate accurate queries on constrained biological data schemas without fine-tuning.
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Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization
Genetic algorithm feature selection with Extra Trees reduces PMU features from 112 to an average of 27.4 while raising macro-F1 from 0.9118 to 0.9212 and ROC-AUC from 0.9791 to 0.9837 on the MSU/ORNL dataset.