GOGGLES: Automatic Image Labeling with Affinity Coding
Summary: GOGGLES introduces affinity coding, a domain-agnostic approach to automatic image labeling using affinity functions to compare instance pairs and separate same-class from different-class pairs. A hierarchical generative model infers labels from a small development set, delivering 71-98% accuracy and outperforming Snuba and few-shot baselines while approaching fully supervised performance. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nilaksh Das (Georgia Institute of Technology)
- 2. Sanya Chaba (Georgia Institute of Technology)
- 3. Renzhi Wu (Georgia Institute of Technology)
- 4. Sakshi Gandhi (Georgia Institute of Technology)
- 5. Duen Horng Chau (Georgia Institute of Technology)
- 6. Xu Chu (Georgia Institute of Technology)
BibTeX Citation
@inproceedings{das_sigmod20,
title = {{GOGGLES: Automatic Image Labeling with Affinity Coding}},
author = {Das, Nilaksh and Chaba, Sanya and Wu, Renzhi and Gandhi, Sakshi and Chau, Duen Horng and Chu, Xu},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3380592},
url = {https://dl.acm.org/doi/10.1145/3318464.3380592},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,736 | OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning | 2021 | SIGMOD | 6.4304185e-05 |
| 7,898 | CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties | 2021 | VLDB | 5.4143104e-05 |
| 8,718 | Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming | 2022 | VLDB | 5.2705676e-05 |
| 9,065 | LANCET: Labeling Complex Data at Scale | 2021 | VLDB | 5.2135215e-05 |
| 9,744 | Ground Truth Inference for Weakly Supervised Entity Matching | 2023 | SIGMOD | 5.1180929e-05 |
| 10,017 | The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format | 2024 | SIGMOD | 5.0825892e-05 |
| 11,242 | A Cost-Effective LLM-based Approach to Identify Wildlife Trafficking in Online Marketplaces | 2025 | SIGMOD | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 100 | HoloClean: Holistic Data Repairs with Probabilistic Inference | 2017 | VLDB | 0.00033951027 |
| 200 | Snorkel: Rapid Training Data Creation with Weak Supervision | 2018 | VLDB | 0.00025443474 |
| 1,123 | Snuba: Automating Weak Supervision to Label Training Data | 2019 | VLDB | 0.00011901566 |
| 1,283 | Fusing Data with Correlations | 2014 | SIGMOD | 0.00011195703 |
| 3,797 | SLiMFast: Guaranteed Results for Data Fusion and Source Reliability | 2017 | SIGMOD | 6.9951279e-05 |
| 7,839 | Towards Globally Optimal Crowdsourcing Quality Management: The Uniform Worker Setting | 2016 | SIGMOD | 5.4264161e-05 |
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