A Comparative Study of Transformer-Based Language Models on Extractive Question Answering

Understand

Question Answering (QA) is a task in natural language processing that has seen considerable growth after the advent of transformers.

• There has been a surge in QA datasets that have been proposed to challenge natural language processing models to improve human and existing model performance.
• Many pre-trained language models have proven to be incredibly effective at the task of extractive question answering.
• However, generalizability remains as a challenge for the majority of these models.