On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing
Summary: UnIMP: unified LLM-enhanced imputation for mixed-type (numeric/categorical/text) tables using a cell-oriented hypergraph and BiHMP — a bidirectional high-order message-passing network that captures inter-column heterogeneity and intra-column homogeneity. Xfusion adapters align BiHMP with LLMs and a pretrain+fine-tune pipeline with chunking and progressive masking yields theoretical guarantees and superior empirical results on 10 real-world datasets. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jianwei Wang
- 2. Kai Wang
- 3. Ying Zhang
- 4. Wenjie Zhang
- 5. Xiwei Xu
- 6. Xuemin Lin
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,843 | Machine Learning for Graph Data Management and Query Processing | 2025 | VLDB | 4.1945683e-05 |
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 517 | Can Foundation Models Wrangle Your Data? | 2023 | VLDB | 0.00021169035 |
| 2,587 | Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks | 2024 | SIGMOD | 8.4924618e-05 |
| 6,259 | Neural Attributed Community Search at Billion Scale | 2023 | SIGMOD | 5.1355079e-05 |
| 6,600 | Missing Data Imputation with Uncertainty-Driven Network | 2024 | SIGMOD | 4.9972581e-05 |
| 8,821 | Efficient Unsupervised Community Search with Pre-trained Graph Transformer | 2024 | VLDB | 4.4417735e-05 |