Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V
Summary: Explain-Da-V: framework that explains semantic changes between dataset versions by synthesizing concise data-transformation explanations. Proposes validity, generalizability and explainability metrics and empirically outperforms prior transformation-synthesis methods. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Roee Shraga
- 2. Renée J. Miller
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,399 | TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations | 2025 | VLDB | 4.3441378e-05 |
| 9,646 | Discovering Functional Dependencies through Hitting Set Enumeration | 2024 | SIGMOD | 4.3109001e-05 |
| 10,109 | Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations | 2026 | SIGMOD | 4.1945683e-05 |
| 10,430 | ChARLES: Change-Aware Recovery of Latent Evolution Semantics in Relational Data | 2025 | SIGMOD | 4.1945683e-05 |
| 10,610 | Weak-to-Strong Prompts with Lightweight-to-Powerful LLMs for High-Accuracy, Low-Cost, and Explainable Data Transformation | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 30 of 30 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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