Analyzing How BERT Performs Entity Matching
Summary: Multi-facet analysis of BERT-based EM: fine-tuning mainly reshapes the last layers, with different effects on matching vs non-matching tokens. BERT also leverages the pairwise-structured descriptions, while pairwise token similarity is not the core knowledge exploited. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,396 | Automatic Data Repair: Are We Ready to Deploy? | 2024 | VLDB | 7.1455126e-05 |
| 7,052 | Pre-trained Embeddings for Entity Resolution: An Experimental Analysis | 2023 | VLDB | 4.8497453e-05 |
| 8,908 | Deep Active Alignment of Knowledge Graph Entities and Schemata | 2023 | SIGMOD | 4.427232e-05 |
| 10,617 | Deduplicated Sampling On-Demand | 2025 | VLDB | 4.1945683e-05 |
| 10,835 | Large Language Models for Spatial Analysis Queries | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 221 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00033121824 |
| 300 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00028441466 |
| 754 | Distributed Representations of Tuples for Entity Resolution | 2018 | VLDB | 0.00017117211 |
| 3,640 | Deep Learning for Blocking in Entity Matching: A Design Space Exploration | 2021 | VLDB | 6.8891671e-05 |
| 5,533 | Dual-Objective Fine-Tuning of BERT for Entity Matching | 2021 | VLDB | 5.4544359e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,345 | Entity Matching: How Similar Is Similar | 2011 | VLDB | 0.00012468408 |
| 319 | Evaluation of entity resolution approaches on real-world match problems | 2010 | VLDB | 0.00027781866 |
| 9,460 | The Battleship Approach to the Low Resource Entity Matching Problem | 2023 | SIGMOD | 4.3366491e-05 |
| 3,640 | Deep Learning for Blocking in Entity Matching: A Design Space Exploration | 2021 | VLDB | 6.8891671e-05 |
| 3,915 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB | 6.6332294e-05 |
| 221 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00033121824 |
| 2,767 | A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching | 2020 | SIGMOD | 8.1513883e-05 |
| 300 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00028441466 |
| 7,052 | Pre-trained Embeddings for Entity Resolution: An Experimental Analysis | 2023 | VLDB | 4.8497453e-05 |
| 5,533 | Dual-Objective Fine-Tuning of BERT for Entity Matching | 2021 | VLDB | 5.4544359e-05 |