56 citations · 69 across the 17 of their papers we have counts for
4 papers · 1 filter
Training-Free LLM-Based Recommendation with Post-LLM Item Refinement Using Collaborative Signals
Kyungho Kim, Sunwoo Kim, Geon Lee +6
Large language models (LLMs) have shown promise for training-free recommendation, but LLM-generated user interests are often too broad for fine-grained item retrieval. Existing met…
On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies
Sunwoo Kim, Sunkyung Lee, Clark Mingxuan Ju +5
Generative recommendation (GR) has emerged as a promising direction for recommender systems. Recently, large language models (LLMs) have been increasingly adopted for GR, as their…
Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and a Simple Remedy
Geon Lee, Sunwoo Kim, Kyungho Kim +1
Graph collaborative filtering (GCF) is a dominant paradigm in recommender systems, where contrastive learning (CL) objectives such as the Sampled Softmax (SSM) loss are widely used…
Personalized Parameter-Efficient Fine-Tuning of Foundation Models for Multimodal Recommendation
Sunwoo Kim, Hyunjin Hwang, Kijung Shin
In recent years, substantial research has integrated multimodal item metadata into recommender systems, often by using pre-trained multimodal foundation models to encode such data.…