PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching
Summary: PromptEM: first low-resource generalized entity matching method using GEM-specific prompt-tuning, improved pseudo-labeling, and efficient self-training to align heterogeneous record formats. Outperforms prior methods on eight real benchmarks in effectiveness and efficiency. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pengfei Wang
- 2. Xiaocan Zeng
- 3. Lu Chen
- 4. Fan Ye
- 5. Yuren Mao
- 6. Junhao Zhu
- 7. Yunjun Gao
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,040 | 3dSAGER: Geospatial Entity Resolution over 3D Objects | 2026 | SIGMOD | 4.1945683e-05 |
| 11,006 | FusionQuery: On-demand Fusion Queries over Multi-source Heterogeneous Data | 2024 | VLDB | 4.1945683e-05 |
| 11,054 | Enriching Relations with Additional Attributes for ER | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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