The researchers worked on improving question-answering models like BERT for natural language processing tasks. They found that fine-tuning these models with domain-specific data helps them perform better on answering questions. The BERT-Large model had the highest accuracy among all models tested, consistently outperforming others in precision, recall, and F1 score.