Synthetic Resume Credibility Assessment Dataset for NLP

CAD-S is the first openly available dataset for resume credibility assessment using NLP. It supports supervised learning for detecting inconsistencies between claimed skills and supporting evidence within resumes. The dataset was created by aselasperera and was last updated in March 2026.

Use Cases

• Train a supervised model to detect inconsistencies between claimed skills and supporting evidence in resumes.
• Develop NLP techniques for resume verification systems using labeled synthetic data.
• Build classifiers to assess the credibility of skill claims based on textual evidence in resumes.

Strengths

• First openly available dataset specifically designed for resume credibility assessment.
• Dataset is synthetic, potentially allowing for controlled experimentation and label consistency.
• Last updated in March 2026, indicating recent maintenance.

Limitations

• Dataset is synthetic, which may not fully capture the complexity and noise of real-world resume data.
• Key details like row count, column features, and sample data are unavailable, hindering initial assessment.

Provenance

Source

huggingface

Collection Method

Synthetically generated for NLP-based credibility assessment.

Time Range

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Freshness

Last updated 2026-03-25.

Geography

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