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 (Zhejiang University)
- 2. Xiaocan Zeng (Zhejiang University)
- 3. Lu Chen (Zhejiang University)
- 4. Fan Ye (Zhejiang University)
- 5. Yuren Mao (Zhejiang University)
- 6. Junhao Zhu (Zhejiang University)
- 7. Yunjun Gao (Zhejiang University)
BibTeX Citation
@article{wang_vldb23,
title = {{PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching}},
author = {Wang, Pengfei and Zeng, Xiaocan and Chen, Lu and Ye, Fan and Mao, Yuren and Zhu, Junhao and Gao, Yunjun},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {2},
pages = {369--378},
doi = {10.14778/3565816.3565836},
url = {https://doi.org/10.14778/3565816.3565836},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,203 | BEACON: Budget-Aware Entity Matching Across Domains | 2026 | SIGMOD | 5.093636e-05 |
| 10,248 | Generalized Entity Matching with Adaptivity via Large Language Models | 2026 | SIGMOD | 5.093636e-05 |
| 10,334 | 3dSAGER: Geospatial Entity Resolution over 3D Objects | 2026 | SIGMOD | 5.093636e-05 |
| 11,217 | FusionQuery: On-demand Fusion Queries over Multi-source Heterogeneous Data | 2024 | VLDB | 5.093636e-05 |
| 11,262 | Enriching Relations with Additional Attributes for ER | 2024 | VLDB | 5.093636e-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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| 1 | 11,255 | Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution | 2024 | VLDB |
| 2 | 4,050 | Revisiting Prompt Engineering via Declarative Crowdsourcing | 2024 | CIDR |
| 3 | 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD |
| 4 | 10,247 | GEM: A Native Graph-based Index for Multi-Vector Retrieval | 2026 | SIGMOD |
| 5 | 4,056 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB |
| 6 | 9,610 | The Battleship Approach to the Low Resource Entity Matching Problem | 2023 | SIGMOD |
| 7 | 11,226 | ZeroEA: A Zero-Training Entity Alignment Framework via Pre-Trained Language Model | 2024 | VLDB |
| 8 | 2,463 | A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching | 2020 | SIGMOD |
| 9 | 9,560 | Ground Truth Inference for Weakly Supervised Entity Matching | 2023 | SIGMOD |
| 10 | 10,248 | Generalized Entity Matching with Adaptivity via Large Language Models | 2026 | SIGMOD |