3 papers
cs.IR2025
An Efficient LLM-based Evolutional Recommendation with Locate-Forget-Update Paradigm
Hao Liu, Le Wu, Min Hou +4
Nowadays, Large Language Models (LLMs) have shown exceptional performance in sequential recommendations, and the adoption of LLM-based recommender systems (LLMRec) is becoming incr…
cs.IR2025
WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
Min Hou, Xin Liu, Le Wu +5
Cross-Domain Sequential Recommendation (CDSR) seeks to improve user preference modeling by transferring knowledge from multiple domains. Despite the progress made in CDSR, most exi…
cs.LG2025
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Dacao Zhang, Kun Zhang, Shimao Chu +3
With the rapid development of Large Language Models (LLMs), Parameter-Efficient Fine-Tuning (PEFT) methods have gained significant attention, which aims to achieve efficient fine-t…