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Cents: A Flexible and Cost-Effective Framework for LLM-Based Table Understanding

Summary: Cents unifies LLM-based table-understanding tasks in a flexible framework, rather than task-specific systems. Its tabular-input compression reduces token cost while improving accuracy, outperforming prior LLM baselines across tasks at equal or lower cost. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h65e67138426e7ca7
Venue
VLDB
Year
2025
Pagerank
5.0682654e-05
Overall Rank
10,165 | 31.66%
DOI
10.14778/3749646.3749714

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{xiao_vldb25,
        title = {{Cents: A Flexible and Cost-Effective Framework for LLM-Based Table Understanding}},
        author = {Xiao, Guorui and He, Dong and Wang, Jin and Balazinska, Magdalena},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4574--4587},
        doi = {10.14778/3749646.3749714},
        url = {https://doi.org/10.14778/3749646.3749714},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,499 Shape-Agnostic Table Overlap Discovery: A Maximum Common Subhypergraph Approach 2026 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 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 0.00035129658
316 Annotating and Searching Web Tables Using Entities, Types and Relationships 2010 VLDB 0.00021221602
329 Can Foundation Models Wrangle Your Data? 2023 VLDB 0.00020858443
367 InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables 2012 SIGMOD 0.00019884846
377 TURL: Table Understanding through Representation Learning 2021 VLDB 0.00019570264
1,683 ReAcTable: Enhancing ReAct for Table Question Answering 2024 VLDB 9.8822754e-05
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
1,932 CHORUS: Foundation Models for Unified Data Discovery and Exploration 2024 VLDB 9.34643e-05
1,978 Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks 2024 SIGMOD 9.2730152e-05
2,092 Sato: Contextual Semantic Type Detection in Tables 2020 VLDB 9.0626928e-05
2,521 GitTables: A Large-Scale Corpus of Relational Tables 2023 SIGMOD 8.3479333e-05
4,159 Integrating Data Lake Tables 2023 VLDB 6.7717519e-05
4,218 Magneto: Combining Small and Large Language Models for Schema Matching 2025 VLDB 6.7270169e-05
4,589 ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models 2024 VLDB 6.5144711e-05
5,332 Observatory: Characterizing Embeddings of Relational Tables 2024 VLDB 6.1766186e-05
7,965 Efficient Approximate Algorithms for Empirical Entropy and Mutual Information 2021 SIGMOD 5.4161136e-05
8,988 Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation 2023 SIGMOD 5.2425067e-05
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