Cutpurse improves model extraction on tabular data
Cutpurse achieves 16.3 percentage point fidelity gain on continuous features without explanation APIs.
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Stories tagged #tabular-data
arXiv releases CoRTeC for differentially private synthetic tabular data
CoRTeC releases synthetic data under differential privacy using noisy counts, decodable without language models or real records.
How-to covers zero-training tabular predictions with NVIDIA models
The fetched page is a cookie consent wall, so the tutorial steps and model details are not available.
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Tabular anomaly detection fuses foundation-model semantics with domain features
Authors report the method beats competitors when training uses only eight labeled anomalies.
Efficient Provably Private Classification with a Tabular Foundation Model
PrivTab is a differentially private tabular foundation model that classifies sensitive data in one forward pass.
Adapting prior-data fitted networks for tabular anomaly detection
Researchers adapt TabPFN features for tabular anomaly detection, with ZEN and FOCUS beating ADBench baselines.
CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data
CDMD trains one mixed-type diffusion model jointly across heterogeneous tabular schemas and beats single-dataset baselines.
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction
NVIDIA announces Kumo Tabular, claiming a new accuracy-efficiency frontier for tabular prediction.
Prior Labs Releases TabPFN-3.5: A Tabular Foundation Model That Beats the Winning Otto Kaggle Solution With Default Settings
Prior Labs releases TabPFN-3.5, a 220M-parameter open-weights tabular foundation model that beats the 2015 Otto Kaggle winning score with default settings.
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LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence
LimiX-2 scales Contextual Mechanism Networks pretrained via context-conditional masked modeling, beating tabular foundation models on TabArena, TALENT, and BCCO benchmarks.
Quantum Feature Engineering for Credit Default Prediction: When and Why IQP Circuits Help Linear Classifiers
Quantum IQP circuit features lift logistic-regression credit-default F1 from 0.462 to 0.517, beating Kernel PCA at an equal feature budget.