Papers by Antonia Donvito
Using LLMs to simulate students’ responses to exam questions (2024.findings-emnlp)
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Luca Benedetto, Giovanni Aradelli, Antonia Donvito, Alberto Lucchetti, Andrea Cappelli, Paula Buttery
| Challenge: | Existing studies have used Large Language Models to simulate students answering exam questions . a proposed prompt for GPT-3.5 is not suitable for all LLMs, and there is no correlation between the quality of the rationales obtained with the model and the accuracy of the student simulation task. |
| Approach: | They propose a large language model prompt engineered for GPT-3.5 that can be used to answer exam questions simulating students of different skill levels. |
| Outcome: | The proposed prompt is robust to different educational domains and generalise to data unseen during prompt engineering phase. |
Beyond Names: How Grammatical Gender Markers Bias LLM-based Educational Recommendations (2026.eacl-long)
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| Challenge: | grammatical gender cues alone trigger substantial distributional shifts in educational recommendations . authors show that up to 76% of the bias exhibited when using prompts with proper names is already present with grammatical gender markers alone. |
| Approach: | They investigate gender biases exhibited by LLM-based virtual assistants in Italian . they show that simply changing noun and adjective endings significantly shifts recommendations . |
| Outcome: | The findings highlight the need for robust bias evaluation and mitigation strategies before deploying LLM-based virtual assistants in student-facing contexts. |