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NLP problem that focuses on generating clarification questions for a given product description.Amazon QuAC and Amazon review datasets were used. Pretrained BART model from hugging face platform has been used.
An Answer-Aware Question Generation Application Using Wikipedia as the Knowledge Source. Using T5-small and Instruction Fine-Tuning to generate a wonderful answer-aware questions.
this is a repository for question and answer generation (QAG). here we train answer extraction (AE) and question generation (QG) models. models with soon be publicly available at pbe.achybl.com
A detailed study on enhancing the working of an Automated Question Generation & Answering system in a real-time environment. Also, the paper gives a glimpse of bringing this system to freeware like WhatsApp.
This is a series of R Programs used to randomly generate questions and answers within WMU's D2L E-learning system. Several nice features are included or in production, such as user-friendly function wrappers and clear comments to outline the code. The final results are thousands of multiple-choice questions as D2L-compatible CSV and JPG files.