Entity Resolution On Amazon Google
Metriken
F1 (%)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | F1 (%) |
|---|---|
| supervised-contrastive-learning-for-product | 79.28 |
| profiling-entity-matching-benchmark-tasks | 79.0 |
| can-foundation-models-wrangle-your-data | 54.30 |
| cordel-a-contrastive-deep-learning-approach | 70.2 |
| fine-tuning-large-language-models-for-entity | 59.20 |
| deep-learning-for-entity-matching-a-design | 69.3 |
| deduplication-over-heterogeneous-attribute | 67.5 |
| fine-tuning-large-language-models-for-entity | 80.25 |
| entity-matching-using-large-language-models | 85.21 |
| fine-tuning-large-language-models-for-entity | 51.44 |
| fine-tuning-large-language-models-for-entity | 50.00 |
| entity-resolution-with-hierarchical-graph | 76.4 |
| fine-tuning-large-language-models-for-entity | 49.16 |
| fine-tuning-large-language-models-for-entity | 63.45 |
| probing-the-robustness-of-pre-trained | 79.06 |
| can-foundation-models-wrangle-your-data | 63.50 |
| deep-entity-matching-with-pre-trained | 75.58 |