LLM-labeled training sets for entity matching produce student models with F1 scores within 2 points of benchmark-trained models on five datasets at a cost of $28-41 versus 470 hours of manual work.
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SGER applies a two-phase curriculum to fine-tune LLMs for name matching, reporting 99.02% accuracy and 0.994 F1 on 50,000 real-world Indian name pairs while outperforming baselines and deploying in production.
citing papers explorer
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Labeling Training Data for Entity Matching Using Large Language Models
LLM-labeled training sets for entity matching produce student models with F1 scores within 2 points of benchmark-trained models on five datasets at a cost of $28-41 versus 470 hours of manual work.
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Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts
SGER applies a two-phase curriculum to fine-tune LLMs for name matching, reporting 99.02% accuracy and 0.994 F1 on 50,000 real-world Indian name pairs while outperforming baselines and deploying in production.