RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
Summary: RPT: denoising tuple-to-tuple autoencoder; Transformer encoder-decoder unifies BERT and GPT. Pre-trained, it enables data cleaning, auto-completion, and normalization and annotation, plus few-shot and collaborative ER/IE. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nan Tang (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 2. Ju Fan (Renmin University of China)
- 3. Fangyi Li (Renmin University of China)
- 4. Jianhong Tu (Renmin University of China)
- 5. Xiaoyong Du (Renmin University of China)
- 6. Guoliang Li (Tsinghua University)
- 7. Sam Madden (Massachusetts Institute of Technology)
- 8. Mourad Ouzzani (Hamad Bin Khalifa University; Qatar Computing Research Institute)
BibTeX Citation
@article{tang_vldb21,
title = {{RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation}},
author = {Tang, Nan and Fan, Ju and Li, Fangyi and Tu, Jianhong and Du, Xiaoyong and Li, Guoliang and Madden, Sam and Ouzzani, Mourad},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {8},
pages = {1254--1261},
doi = {10.14778/3457390.3457391},
url = {https://doi.org/10.14778/3457390.3457391},
year = {2021}
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