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: 5.1950133e-05
Overall Rank: 9,201 | 38.33%
DOI: 10.14778/3749646.3749714
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Guorui Xiao (University of Washington)
2. Dong He (University of Washington)
3. Jin Wang (Arizona State University)
4. Magdalena Balazinska (University of Washington)

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 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,409	SemDistill: Bootstrapping a Low-Latency, Low-Cost Semantic Table Annotator from Noisy LLM	2027	SIGMOD	4.9605343e-05
10,576	Shape-Agnostic Table Overlap Discovery: A Maximum Common Subhypergraph Approach	2026	SIGMOD	4.9605343e-05

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
88	WebTables: Exploring the Power of Tables on the Web	2008	VLDB	0.00035500667
314	Annotating and Searching Web Tables Using Entities, Types and Relationships	2010	VLDB	0.0002126519
323	Can Foundation Models Wrangle Your Data?	2023	VLDB	0.00021022156
366	TURL: Table Understanding through Representation Learning	2021	VLDB	0.00019902067
367	InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables	2012	SIGMOD	0.00019882429
1,600	ReAcTable: Enhancing ReAct for Table Question Answering	2024	VLDB	0.00010093108
1,669	Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks	2024	SIGMOD	9.9157758e-05
1,690	Annotating Columns with Pre-trained Language Models	2022	SIGMOD	9.8426663e-05
1,742	Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning	2023	VLDB	9.7283207e-05
1,838	CHORUS: Foundation Models for Unified Data Discovery and Exploration	2024	VLDB	9.5195856e-05
1,985	Sato: Contextual Semantic Type Detection in Tables	2020	VLDB	9.2378767e-05
2,334	GitTables: A Large-Scale Corpus of Relational Tables	2023	SIGMOD	8.6058607e-05
4,047	Magneto: Combining Small and Large Language Models for Schema Matching	2025	VLDB	6.8177935e-05
4,158	Integrating Data Lake Tables	2023	VLDB	6.7595989e-05
4,335	ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models	2024	VLDB	6.6432811e-05
5,301	Observatory: Characterizing Embeddings of Relational Tables	2024	VLDB	6.1761723e-05
7,970	Efficient Approximate Algorithms for Empirical Entropy and Mutual Information	2021	SIGMOD	5.3997018e-05
8,161	Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation	2023	SIGMOD	5.37207e-05

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