Papers by Jerome Ramos

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Challenge:	Recent advances in Large Language Models (LLMs) rely on implicit or explicit feedback from users to suggest new items, resulting in a lack of transparency and a user's ability to scrutinize and modify their preferences.
Approach:	They propose to use a natural language (NL) user profile to summarize a user's preferences and then use it to fine-tune a LLM using only NL profiles to make transparent and scrutable recommendations.
Outcome:	The proposed model performs on two benchmarking rating prediction datasets and is comparable to existing models.