Muhammad Shoaib Altaf

We built inference-audit, a reproducible Python toolkit for systematically auditing NLP dataset quality across five core dimensions. The pipeline combines deterministic checks for label distribution, missing values, near-duplicates, language contamination, and annotation consistency. Extensive testing and real-corpus evaluation exposed performance and reliability issues, leading to targeted fixes and measurable optimizations. The final system emphasizes reproducibility, explicit failure states, citable evidence, and transparent limitations.