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ZeroER: Entity Resolution using Zero Labeled Examples
Summary: ZeroER uses zero-labeled data for ER with a Gaussian Mixture Model separating match vs. unmatch. It adds adaptive regularization and a transitivity-informed generative model, yielding strong unsupervised results close to supervised on five ER benchmarks.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5958
- Venue
- SIGMOD
- Year
- 2020
- Pagerank
- 7.4841763e-05
- Overall Rank
- 3,140 | 78.16%
- DOI
-
10.1145/3318464.3389743
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 22 of 22 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 2,349 |
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation |
2021 |
VLDB |
8.9876423e-05 |
| 2,839 |
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition |
2021 |
VLDB |
8.0378978e-05 |
| 3,396 |
Automatic Data Repair: Are We Ready to Deploy? |
2024 |
VLDB |
7.1455126e-05 |
| 3,640 |
Deep Learning for Blocking in Entity Matching: A Design Space Exploration |
2021 |
VLDB |
6.8891671e-05 |
| 5,096 |
Auto-Transform: Learning-to-Transform by Patterns |
2020 |
VLDB |
5.7011825e-05 |
| 5,434 |
Auto-FuzzyJoin: Auto-Program Fuzzy Similarity Joins Without Labeled Examples |
2021 |
SIGMOD |
5.5045402e-05 |
| 5,869 |
Demonstration of Panda: A Weakly Supervised Entity Matching System |
2021 |
VLDB |
5.2959029e-05 |
| 6,553 |
How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses |
2024 |
VLDB |
5.0157344e-05 |
| 6,894 |
TableDC: Deep Clustering for Tabular Data |
2025 |
SIGMOD |
4.8925595e-05 |
| 7,052 |
Pre-trained Embeddings for Entity Resolution: An Experimental Analysis |
2023 |
VLDB |
4.8497453e-05 |
| 8,008 |
Entity Resolution On-Demand |
2022 |
VLDB |
4.6067684e-05 |
| 8,182 |
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning |
2023 |
VLDB |
4.5659133e-05 |
| 9,192 |
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale |
2022 |
VLDB |
4.3765131e-05 |
| 9,355 |
Discovering Top-k Rules using Subjective and Objective Criteria |
2023 |
SIGMOD |
4.3514328e-05 |
| 9,409 |
Ground Truth Inference for Weakly Supervised Entity Matching |
2023 |
SIGMOD |
4.3441378e-05 |
| 9,460 |
The Battleship Approach to the Low Resource Entity Matching Problem |
2023 |
SIGMOD |
4.3366491e-05 |
| 10,040 |
3dSAGER: Geospatial Entity Resolution over 3D Objects |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,624 |
Evaluating Methods for Efficient Entity Count Estimation |
2025 |
VLDB |
4.1945683e-05 |
| 11,223 |
Splitting Tuples of Mismatched Entities |
2023 |
SIGMOD |
4.1945683e-05 |
| 11,230 |
VersaMatch: Ontology Matching with Weak Supervision |
2023 |
VLDB |
4.1945683e-05 |
| 11,342 |
FILA: Online Auditing of Machine Learning Model Accuracy under Finite Labelling Budget |
2022 |
SIGMOD |
4.1945683e-05 |
| 11,431 |
Ease.ML: A Lifecycle Management System for MLDev and MLOps |
2021 |
CIDR |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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