3 papers
cs.IR2026
Efficient Dataset Selection for Continual Adaptation of Generative Recommenders
Cathy Jiao, Juan Elenter, Praveen Ravichandran +7
Recommendation systems must continuously adapt to evolving user behavior, yet the volume of data generated in large-scale streaming environments makes frequent full retraining impr…
cs.CL2025
Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models
Bernd Huber, Ghazal Fazelnia, Andreas Damianou +6
Large language models (LLMs) excel at generating contextually relevant content. However, tailoring these outputs to individual users for effective personalization is a significant…
cs.IR2023
Evaluation Framework for Understanding Sensitive Attribute Association Bias in Latent Factor Recommendation Algorithms
Lex Beattie, Isabel Corpus, Lucy H. Lin +1
We present a novel evaluation framework for representation bias in latent factor recommendation (LFR) algorithms. Our framework introduces the concept of attribute association bias…