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.
EQGG: Automatic Question Group Generation
This app allows users to auto-generate unlimited exam preparation questions, based off their own, or a community created question.
Code for the paper 'A Lightweight Method to Generate Unanswerable Questions in English' (Findings of EMNLP 2023)
The Culinary Query is an AI-Enhanced Menu Item Question Generator for training purpose's built using Django REST Framework and OpenAI's API
PIE-QG: Paraphrased Information Extraction for Unsupervised Question Generation from Small Corpora
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 repository contains recommendation system for dating apps based on personality evaluation by automatic question generation and sentiment + zero shot classification and user embeddings based on swipe history, made with FastAPI, validated by Pydantic Models
Natural language Processing System, that takes a document as an input then applies NLP Techniques to generate a list of possible Questions and related possible distractors (choices). Implemented as a Web Application in Flask Python.
Q&Arabic is an NLP framework that generates Arabic FAQs from a given material. The project uses deep learning models (BERT and T5) and includes a detailed report and brief presentation covering the system analysis, related work, and future plans.
REST API for automated question generation using Flask for different topics in discrete mathematics.
This repository is the official implementation of our paper MVP: Multi-task Supervised Pre-training for Natural Language Generation.
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
a tool to generate questions and answers from pdf files
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
Question-Answer Generation Control for English, using the T5 model and Pytorch lightning. Training, inference and evaluation scripts included.
The official codes and data of our ACL-IJCNLP 2021 SRW paper: "Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation"
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