Mind the Data Gap: Bridging LLMs to Enterprise Data Integration
Summary: LLM-based integration methods trained on public corpora falter on enterprise “dark” data; current public benchmarks overestimate real-world performance. Presents the Goby Benchmark and three remedies—hierarchical annotation, runtime class-learning, and ontology synthesis—that restore LLM performance on enterprise integration to parity with public-data scenarios. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Moe Kayali (University of Washington)
- 2. Fabian Wenz (Massachusetts Institute of Technology; Technical University of Munich)
- 3. Nesime Tatbul (Intel; Massachusetts Institute of Technology)
- 4. Çağatay Demiralp (Amazon; Massachusetts Institute of Technology)
BibTeX Citation
@inproceedings{kayali_cidr25,
address = {Amsterdam, Netherlands},
series = {{CIDR} '25},
title = {{Mind the Data Gap: Bridging LLMs to Enterprise Data Integration}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Kayali, Moe and Wenz, Fabian and Tatbul, Nesime and Demiralp, Çağatay},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,074 | A Vision for Autonomous Data Agent Collaboration: From Query-by-Integration to Query-by-Collaboration | 2026 | CIDR | 5.2258409e-05 |
| 9,078 | Unveiling Challenges for LLMs in Enterprise Data Engineering | 2026 | VLDB | 5.2258409e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 89 | WebTables: Exploring the Power of Tables on the Web | 2008 | VLDB | 0.00035115118 |
| 329 | Can Foundation Models Wrangle Your Data? | 2023 | VLDB | 0.00020867521 |
| 496 | Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes | 2024 | VLDB | 0.00017318538 |
| 514 | Data Curation at Scale: The Data Tamer System | 2013 | CIDR | 0.00016999652 |
| 1,778 | Annotating Columns with Pre-trained Language Models | 2022 | SIGMOD | 9.6578031e-05 |
| 1,929 | CHORUS: Foundation Models for Unified Data Discovery and Exploration | 2024 | VLDB | 9.3551286e-05 |
| 2,520 | GitTables: A Large-Scale Corpus of Relational Tables | 2023 | SIGMOD | 8.3489561e-05 |
| 7,063 | Towards NLP-Enhanced Data Profiling Tools | 2022 | CIDR | 5.6078438e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,473 | Generalized Entity Matching with Adaptivity via Large Language Models | 2026 | SIGMOD |
| 2 | 9,498 | LLM-PBE: Assessing Data Privacy in Large Language Models | 2024 | VLDB |
| 3 | 11,033 | Bridging LLMs and Database Systems: A Deep Dive into Enhanced Relational Operators | 2026 | VLDB |
| 4 | 8,688 | Unstructured Data Analysis Using LLMs: A Comprehensive Benchmark | 2026 | VLDB |
| 5 | 3,236 | How Large Language Models Will Disrupt Data Management | 2023 | VLDB |
| 6 | 5,686 | DTT: An Example-Driven Tabular Transformer for Joinability by Leveraging Large Language Models | 2024 | SIGMOD |
| 7 | 10,538 | In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration | 2026 | SIGMOD |
| 8 | 11,047 | Semantic Data Systems: From Data Management to Data Understanding | 2026 | VLDB |
| 9 | 4,727 | LLM for Data Management | 2024 | VLDB |
| 10 | 9,078 | Unveiling Challenges for LLMs in Enterprise Data Engineering | 2026 | VLDB |