Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration
Summary: Unicorn: a unified multi-task data-matching model for diverse integration tasks. A single Encoder+Matcher with mixture-of-experts enables cross-task knowledge sharing and zero-shot support across 20 datasets and 7 tasks, outperforming ad-hoc baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jianhong Tu (Renmin University of China)
- 2. Ju Fan (Renmin University of China)
- 3. Nan Tang (Hong Kong University of Science and Technology; Qatar Computing Research Institute)
- 4. Peng Wang (Renmin University of China)
- 5. Guoliang Li (Tsinghua University)
- 6. Xiaoyong Du (Renmin University of China)
- 7. Xiaofeng Jia (Beijing Academy of Artificial Intelligence)
- 8. Song Gao (Beijing Academy of Artificial Intelligence)
BibTeX Citation
@inproceedings{tu_sigmod23,
title = {{Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration}},
author = {Tu, Jianhong and Fan, Ju and Tang, Nan and Wang, Peng and Li, Guoliang and Du, Xiaoyong and Jia, Xiaofeng and Gao, Song},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3588938},
url = {https://dl.acm.org/doi/10.1145/3588938},
year = {2023}
}
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