Transparent and Scrutable Recommendations Using Natural Language User Profiles (2024.acl-long)
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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. |
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