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Davide Mazzaccara

2 accepted papers

2025

Playpen: An Environment for Exploring Learning From Dialogue Game Feedback

EMNLP 2025

Interaction between learner and feedback-giver has come into focus recently for post-training of Large Language Models (LLMs), through the use of reward models that judge the appropriateness of a model’s response. In this paper, we investigate whether Dialogue Games—goal-directed and rule-governed a

2024

Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain

EMNLP 2024finding

Questions are essential tools for acquiring the necessary information to complete information-seeking tasks. However, large language models (LLMs), especially open-source models, often perform poorly in generating informative questions, as measured by expected information gain (EIG). In this paper,…