UP5: Unbiased Foundation Model for Fairness-aware Recommendation (2024.eacl-long)
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| Challenge: | Large Language Models (LLMs) are gaining a foothold in Recommender Systems (RS) but there is growing concern that LLMs perpetuate stereotypes and may result in unfair recommendations. |
| Approach: | They propose a counterfactually-fair-prompt method for LLM-based recommendation that is based on unbiased foundation mOdels. |
| Outcome: | The proposed method achieves better recommendation performance with a high level of fairness on two real-world datasets. |
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