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
- 2. Yeye He
- 3. Weiwei Cui
- 4. Ju Fan
- 5. Song Ge
- 6. Haidong Zhang
- 7. Dongmei Zhang
- 8. Surajit Chaudhuri
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,564 | Automatic Database Configuration Debugging using Retrieval-Augmented Language Models | 2025 | SIGMOD | 5.0037892e-05 |
| 7,933 | In-depth Analysis of Graph-based RAG in a Unified Framework | 2025 | VLDB | 4.6089395e-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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| 2,585 | Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks | 2024 | SIGMOD | 8.4909917e-05 |
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| 13,209 | Cornet: Learning Spreadsheet Formatting Rules By Example | 2023 | VLDB | - |
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| 8,679 | FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language | 2024 | VLDB | 4.4644049e-05 |
| 11,247 | Cornet: Learning Table Formatting Rules By Example | 2023 | VLDB | 4.1905499e-05 |