Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations
Summary: Auto-Formula recommends spreadsheet cell formulas by retrieving/adapting formulas from similar enterprise spreadsheets, exploiting the recurring structure and computation patterns across org-specific tables. Key idea: contrastive learning for table/spreadsheet representations to predict target formulas more accurately than prior approaches. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sibei Chen (Renmin University of China)
- 2. Yeye He (Microsoft)
- 3. Weiwei Cui (Microsoft)
- 4. Ju Fan (Renmin University of China)
- 5. Song Ge (Microsoft)
- 6. Haidong Zhang (Microsoft)
- 7. Dongmei Zhang (Microsoft)
- 8. Surajit Chaudhuri (Microsoft)
BibTeX Citation
@inproceedings{chen_sigmod24,
title = {{Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations}},
author = {Chen, Sibei and He, Yeye and Cui, Weiwei and Fan, Ju and Ge, Song and Zhang, Haidong and Zhang, Dongmei and Chaudhuri, Surajit},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3654925},
url = {https://dl.acm.org/doi/10.1145/3654925},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,466 | In-depth Analysis of Graph-based RAG in a Unified Framework | 2025 | VLDB | 7.2783993e-05 |
| 4,114 | Automatic Database Configuration Debugging using Retrieval-Augmented Language Models | 2025 | SIGMOD | 6.7971182e-05 |
| 10,466 | HAMMER: An Automatic RAG Tuning System via Hierarchical Memory-Guided Monte Carlo Tree Search | 2026 | SIGMOD | 4.9793485e-05 |
| 10,791 | BookRAG: A Hierarchical Structure-aware Index-based Approach for Retrieval-Augmented Generation on Complex Documents | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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