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cs.IR2025
Automating Personalization: Prompt Optimization for Recommendation Reranking
Chen Wang, Mingdai Yang, Zhiwei Liu +4
Modern recommender systems increasingly leverage large language models (LLMs) for reranking to improve personalization. However, existing approaches face two key limitations: (1) h…
cs.IR2024
Sequential Recommendation via Adaptive Robust Attention with Multi-dimensional Embeddings
Linsey Pang, Amir Hossein Raffiee, Wei Liu +1
Sequential recommendation models have achieved state-of-the-art performance using self-attention mechanism. It has since been found that moving beyond only using item ID and positi…