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Found 5 papers, 4 papers with code
Diffusion Cocktail: Fused Generation from Diffusion Models
In this work, we study the combinations of diffusion models.
GEMRec: Towards Generative Model Recommendation
With recent advances in Generative AI such as GPT and Diffusion models, a new form of recommendation task is yet to be explored where items are to be created by generative models with personalized prompts.
Evaluating Music Recommendations with Binary Feedback for Multiple Stakeholders
High quality user feedback data is essential to training and evaluating a successful music recommendation system, particularly one that has to balance the needs of multiple stakeholders.
Correcting the User Feedback-Loop Bias for Recommendation Systems
We empirically validated the existence of such user feedback-loop bias in real world recommendation systems and compared the performance of our method with the baseline models that are either without de-biasing or with propensity scores estimated by other methods.
Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
Recommender systems play an important role in modern information and e-commerce applications.
