Data Imputation with Limited Data Redundancy Using Data Lakes

Summary: LakeFill leverages LLMs and data lakes for tuple-level retrieval and encoding of incomplete tuples to find cross-table candidates when intra-table redundancy is low. It uses checklist-based reranking and a two-stage confidence-aware reasoner, beating prior methods. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14154
Venue: VLDB
Year: 2025
Pagerank: 5.2528121e-05
Overall Rank: 9,550 | 34.48%
DOI: 10.14778/3748191.3748200

Incoming Non-self Citations Over Time

Authors

1. Chenyu Yang (Hong Kong University of Science and Technology)
2. Yuyu Luo (Hong Kong University of Science and Technology)
3. Chuanxuan Cui (Renmin University of China)
4. Ju Fan (Renmin University of China)
5. Chengliang Chai (Beijing Institute of Technology)
6. Nan Tang (Hong Kong University of Science and Technology)

BibTeX Citation

@article{yang_vldb25,
        title = {{Data Imputation with Limited Data Redundancy Using Data Lakes}},
        author = {Yang, Chenyu and Luo, Yuyu and Cui, Chuanxuan and Fan, Ju and Chai, Chengliang and Tang, Nan},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {10},
        pages = {3354--3367},
        doi = {10.14778/3748191.3748200},
        url = {https://doi.org/10.14778/3748191.3748200},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,131	Towards Scalable Visual Data Wrangling via Direct Manipulation	2026	CIDR	5.093636e-05
10,587	LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning	2026	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
112	HoloClean: Holistic Data Repairs with Probabilistic Inference	2017	VLDB	0.00032801121
141	Deep Entity Matching with Pre-Trained Language Models	2021	VLDB	0.0002964847
397	TURL: Table Understanding through Representation Learning	2021	VLDB	0.00019278189
420	Can Foundation Models Wrangle Your Data?	2023	VLDB	0.00018789852
998	Towards Certain Fixes with Editing Rules and Master Data	2010	VLDB	0.0001275238
1,101	KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing	2015	SIGMOD	0.00012168934
1,351	Detecting Data Errors: Where are we and what needs to be done?	2016	VLDB	0.00011064851
1,476	Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning	2020	VLDB	0.00010659277
2,019	RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation	2021	VLDB	9.2983994e-05
2,099	Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks	2024	SIGMOD	9.1682353e-05
2,852	The Dawn of Natural Language to SQL: Are We Fully Ready?	2024	VLDB	8.0455088e-05
5,366	HAIChart: Human and AI Paired Visualization System	2024	VLDB	6.2457679e-05
7,199	Learned Data-aware Image Representations of Line Charts for Similarity Search	2023	SIGMOD	5.6759927e-05
9,177	VerifAI: Verified Generative AI	2024	CIDR	5.3078984e-05

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