Luca Benedetto
Luca Benedetto
Postdoc Research Associate, University of Cambridge
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R2DE: a NLP approach to estimating IRT parameters of newly generated questions
L Benedetto, A Cappelli, R Turrin, P Cremonesi
Proceedings of the Tenth International Conference on Learning Analyticsá…, 2020
Introducing a framework to assess newly created questions with Natural Language Processing
L Benedetto, A Cappelli, R Turrin, P Cremonesi
Artificial Intelligence in Education: 21st International Conference, AIED 2020, 2020
A Virtual Teaching Assistant for Personalized Learning
L Benedetto, P Cremonesi, M Parenti
arXiv preprint arXiv:1902.09289, 2019
On the application of Transformers for estimating the difficulty of Multiple-Choice Questions from text
L Benedetto, G Aradelli, P Cremonesi, A Cappelli, A Giussani, R Turrin
Proceedings of the 16th Workshop on Innovative Use of NLP for Buildingá…, 2021
On the application of Large Language Models for language teaching and assessment technology
A Caines, L Benedetto, S Taslimipoor, C Davis, Y Gao, O Andersen, ...
arXiv preprint arXiv:2307.08393, 2023
A survey on recent approaches to question difficulty estimation from text
L Benedetto, P Cremonesi, A Caines, P Buttery, A Cappelli, A Giussani, ...
ACM Computing Surveys 55 (9), 1-37, 2023
Rexy, A Configurable Application for Building Virtual Teaching Assistants
L Benedetto, P Cremonesi
IFIP Conference on Human-Computer Interaction, 233-241, 2019
Towards the application of calibrated Transformers to the unsupervised estimation of question difficulty from text
E Loginova, L Benedetto, D Benoit, P Cremonesi
RANLP 2021, 846-855, 2021
A quantitative study of NLP approaches to question difficulty estimation
L Benedetto
International Conference on Artificial Intelligence in Education, 428-434, 2023
The Cambridge Multiple-Choice Questions Reading Dataset
A Mullooly, ě Andersen, L Benedetto, P Buttery, A Caines, MJF Gales, ...
Cambridge University Press and Assessment, 2023
An assessment of recent techniques for question difficulty estimation from text
L Benedetto
Distractor Generation Using Generative and Discriminative Capabilities of Transformer-based Models
S Taslimipoor, L Benedetto, M Felice, P Buttery
Proceedings of the 2024 Joint International Conference on Computationalá…, 2024
Complexity-based partitioning of CSFI problem instances with Transformers
L Benedetto, P Fantozzi, L Laura
arXiv preprint arXiv:2106.14481, 2021
A Machine Learning Approach to Detecting Cyber Security Issues on PCs and Printers
L Benedetto
Politecnico di Torino, 2018
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