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Entity Resolution On Wdc Computers Xlarge
Metrics
F1 (%)
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| RoBERTa-SupCon | 98.33 | Supervised Contrastive Learning for Product Matching | |
| JointBERT | 97.49 | Dual-Objective Fine-Tuning of BERT for Entity Matching | - |
| BERT | 97.37 | Intermediate Training of BERT for Product Matching | - |
| HG | 96.50 | Entity Resolution with Hierarchical Graph Attention Networks | - |
| Ditto | 95.45 | Deep Entity Matching with Pre-Trained Language Models | |
| Random Forest | 78.0 | Profiling Entity Matching Benchmark Tasks | - |
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