Pre-Training With Scientific Text Improves Educational Question Generation

7 December 2022

Papers citing "Pre-Training With Scientific Text Improves Educational Question Generation"

7 / 7 papers shown

Title
Leaf: Multiple-Choice Question Generation Kristiyan Vachev Momchil Hardalov Georgi Karadzhov Georgi Georgiev Ivan Koychev Preslav Nakov AI4Ed 53 22 0 22 Jan 2022
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution Sahan Bulathwela Maria Perez-Ortiz C. Holloway John Shawe-Taylor 67 19 0 03 Dec 2021
BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation Haoran Xu Benjamin Van Durme Kenton W. Murray 65 59 0 09 Sep 2021
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources Sahan Bulathwela Maria Perez-Ortiz Emine Yilmaz John Shawe-Taylor AI4Ed CLL 45 42 0 21 Nov 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 394 20,114 0 23 Oct 2019
Crowdsourcing Multiple Choice Science Questions Johannes Welbl Nelson F. Liu Matt Gardner AI4Ed 60 502 0 19 Jul 2017
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 256 8,124 0 16 Jun 2016