LDI introduces localized LLM-based imputation for text-rich tables by selecting compact relevant subsets of attributes and tuples per missing value, reporting up to 8% accuracy gains over prior methods.
Xgboost: A scalable tree boosting system
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First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
A bilateral branch network with hypergraph-based parameter generation and cluster adversarial learning models radiation-attraction transformations and regional competition for improved OD demand prediction.
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LDI: Localized Data Imputation for Text-Rich Tables
LDI introduces localized LLM-based imputation for text-rich tables by selecting compact relevant subsets of attributes and tuples per missing value, reporting up to 8% accuracy gains over prior methods.
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Diffusion and Flow Matching Models for Tabular Data: A Survey
First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
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Origin-Destination Demand Prediction: An Urban Radiation and Attraction Perspective
A bilateral branch network with hypergraph-based parameter generation and cluster adversarial learning models radiation-attraction transformations and regional competition for improved OD demand prediction.