Mohammad R. Hasan

A Context-Aware Approach for Enhancing Data Imputation with Pre-trained Language Models

This paper presents a novel approach named Contextually Relevant Imputation leveraging pre-trained Language Models (CRILM) for handling missing data in tabular datasets. Instead of relying on traditional numerical estimations, CRILM uses pre-trained language models (LMs) to create contextually relev…