Safety as a Constraint: Fine-Tuning a LLM Recommender to Explain Itself
arXiv:2609.13657v1 Announce Type: new Abstract: Traditional recommender systems are typically trained to predict what item users will interact with next, but not why. However, offering personalized evidence for why a user might like the...
Read more: https://arxiv.org/abs/2609.13657
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