3 citations · 3 across the 3 of their papers we have counts for
Showing cs.IRShow all
3 papers · 1 filter
cs.IR2025
Do Reviews Matter for Recommendations in the Era of Large Language Models?
Chee Heng Tan, Huiying Zheng, Jing Wang +5
With the advent of large language models (LLMs), the landscape of recommender systems is undergoing a significant transformation. Traditionally, user reviews have served as a criti…
cs.IR2024
Hesitation and Tolerance in Recommender Systems
Kuan Zou, Aixin Sun, Yitong Ji +5
Users' interactions with recommender systems often involve more than simple acceptance or rejection. We highlight two overlooked states: hesitation, when people deliberate without…
cs.IR2024★ 3 cited
LANE: Logic Alignment of Non-tuning Large Language Models and Online Recommendation Systems for Explainable Reason Generation
Hongke Zhao, Songming Zheng, Likang Wu +2
The explainability of recommendation systems is crucial for enhancing user trust and satisfaction. Leveraging large language models (LLMs) offers new opportunities for comprehensiv…