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Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations

Summary: Introduce a retrieve-and-verify framework that selects compact, informative column contexts (instead of serializing whole tables) via unsupervised retrieval balancing relevance and diversity and role-aware target-context encoding (REVEAL). REVEAL+ adds a learned verification classifier with top-down inference to efficiently refine context subsets (quadratic search), yielding consistent CTA/CPA accuracy gains over SOTA across six benchmarks. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
h5a0111ff0eb837ff
Venue
SIGMOD
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,595 | 28.77%
DOI
10.1145/3769823

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Authors

BibTeX Citation

@inproceedings{ding_sigmod26,
        title = {{Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations}},
        author = {Ding, Zhihao and Sun, Yongkang and Shi, Jieming},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769823},
        url = {https://dl.acm.org/doi/10.1145/3769823},
        year = {2026}
}

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Showing 19 of 19 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
377 TURL: Table Understanding through Representation Learning 2021 VLDB 0.00019570264
694 JOSIE: Overlap Set Similarity Search for Finding Joinable Tables in Data Lakes 2019 SIGMOD 0.00014727089
765 Table Union Search on Open Data 2018 VLDB 0.00014125424
1,780 Annotating Columns with Pre-trained Language Models 2022 SIGMOD 9.6560923e-05
1,852 Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning 2023 VLDB 9.5004635e-05
1,978 Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks 2024 SIGMOD 9.2730152e-05
1,988 SANTOS: Relationship-based Semantic Table Union Search 2023 SIGMOD 9.2482448e-05
2,092 Sato: Contextual Semantic Type Detection in Tables 2020 VLDB 9.0626928e-05
2,382 DeepJoin: Joinable Table Discovery with Pre-trained Language Models 2023 VLDB 8.5458532e-05
2,521 GitTables: A Large-Scale Corpus of Relational Tables 2023 SIGMOD 8.3479333e-05
3,473 Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration 2023 SIGMOD 7.2728706e-05
4,159 Integrating Data Lake Tables 2023 VLDB 6.7717519e-05
4,409 LakeBench: A Benchmark for Discovering Joinable and Unionable Tables in Data Lakes 2024 VLDB 6.6120807e-05
4,589 ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models 2024 VLDB 6.5144711e-05
4,944 PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy 2023 SIGMOD 6.3439252e-05
5,097 Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V 2023 VLDB 6.2742361e-05
8,594 RECA: Related Tables Enhanced Column Semantic Type Annotation Framework 2023 VLDB 5.3063445e-05
8,988 Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation 2023 SIGMOD 5.2425067e-05
9,109 Generation of Training Examples for Tabular Natural Language Inference 2023 SIGMOD 5.2280464e-05
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