NLP · 2021

Descriptive Question Answering System

NLP Research (Bachelor's Thesis)

Transformer-based descriptive question answering system using a fine-tuned BERT model and sentence-ranking pipeline, published at an IEEE conference.

Highlights

  • Built a transformer-based architecture for descriptive question answering, fine-tuning BERT to retrieve and rank relevant passages from document collections.
  • Implemented a sentence-ranking pipeline that scores candidate answers using transfer learning and semantic similarity for accurate response generation.
  • Published the work at the IEEE Pune Section International Conference (Dec 2021) as part of a bachelor's final-year project.