TreeInstruct is a novel method that uses state space estimation and dynamic tree-based questioning for multi-turn Socratic instruction, applied to code debugging.
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Updated
Jul 26, 2024 - Python
TreeInstruct is a novel method that uses state space estimation and dynamic tree-based questioning for multi-turn Socratic instruction, applied to code debugging.
Text2Text: Crosslingual NLP/G toolkit
AI powered API for generating personalised study questions. All you have to do is to pass in your course material as a PDF file, and then question would be generated based on its content
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 tool to generate questions and answers from pdf files
This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.
Mimix: A Text Generation Tool and Pretrained Chinese Models
A study on Knowledge-based question generation from images. Undergraduate Thesis for 2023-2024.
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Question-Answer Generation Control for English, using the T5 model and Pytorch lightning. Training, inference and evaluation scripts included.
Code for paper "FairytaleQA Translated: Enabling Educational Question and Answer Generation in Less-Resourced Languages"
Indonesian Question Answering and Question Generation using Transformers
This paper introduces a systematic and large-scale study of the Vietnamese question generation task. Different from prior work that only investigates the task with a small number (1-2) of datasets, the study reports the performance of question generation models on a wide range of Vietnamese machine reading comprehension corpora in different setting
Multilingual/multidomain question generation datasets, models, and python library for question generation.
Code for the paper 'A Lightweight Method to Generate Unanswerable Questions in English' (Findings of EMNLP 2023)
An NLP system for generating reading comprehension questions
This is a package for generating questions and answers from unstructured data to be used for NLP tasks.
An original implementation of "Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank" (ACL BEA workshop 2023)
Question generation using state-of-the-art Natural Language Processing algorithms
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