LLMs support taxonomy-agnostic detection and value extraction of PII in HTTP traffic via a deterministic pre-processing plus classification pipeline, plus an LLM generator for synthetic labeled traffic.
Modeling tabular data using conditional gan
3 Pith papers cite this work. Polarity classification is still indexing.
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Proposes three metrics for inter-column logical relationships in synthetic tabular data and reports that current generators often fail to preserve them on an industrial dataset.
A framework using structural causal models simulates parametric drifts to evaluate classifier robustness more realistically than static tests or noise perturbations.
citing papers explorer
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Addressing Labelled Data Scarcity: Taxonomy-Agnostic Annotation of PII Values in HTTP Traffic using LLMs
LLMs support taxonomy-agnostic detection and value extraction of PII in HTTP traffic via a deterministic pre-processing plus classification pipeline, plus an LLM generator for synthetic labeled traffic.
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Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation
Proposes three metrics for inter-column logical relationships in synthetic tabular data and reports that current generators often fail to preserve them on an industrial dataset.
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Causal Parametric Drift Simulation: A Digital Twin Framework for Classifier Robustness Evaluation
A framework using structural causal models simulates parametric drifts to evaluate classifier robustness more realistically than static tests or noise perturbations.