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Luca Benedetto

2 accepted papers

2024

Distractor Generation Using Generative and Discriminative Capabilities of Transformer-based Models

COLING 2024main

Multiple Choice Questions (MCQs) are very common in both high-stakes and low-stakes examinations, and their effectiveness in assessing students relies on the quality and diversity of distractors, which are the incorrect answer options provided alongside the correct answer. Motivated by the progress…

Cited by 1SourcePDFScholar
2024

Using LLMs to simulate students’ responses to exam questions

EMNLP 2024finding

Previous research leveraged Large Language Models (LLMs) in numerous ways in the educational domain. Here, we show that they can be used to answer exam questions simulating students of different skill levels and share a prompt, engineered for GPT-3.5, that enables the simulation of varying student s…

Cited by 1SourcePDFScholar