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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)

Paper ID
13386
Venue
VLDB
Year
2023
Pagerank
5.6942765e-05
Overall Rank
7,134 | 51.06%
DOI
10.14778/3565816.3565836

Incoming Non-self Citations Over Time

Authors

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}
}

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