3 papers
cs.IR2026
A Dual-Expert Strategy Integrating LLMs to Mitigate Negative Transfer in Cross-Domain Sequential Recommendation
Hyeongjun Yun, Kihyuk Song, Jaegul Choo +1
Cross-Domain Sequential Recommendation (CDSR) predicts the next item a user will interact with based on their historical interaction sequences across multiple domains. Recent appro…
cs.LG2026
Don't Let Bandit Feedback Pull Continual LLM-Recommender Updates Off Target
Taesan Kim, Hyeongjun Yun, Jaegul Choo +1
Generative LLM-based recommenders (LLM-Rec) require continual post-deployment updates, yet deployment logs provide only policy-shaped contextual bandit feedback: outcomes are obser…
cs.IR2025
Towards Trustworthy LLM-Based Recommendation via Rationale Integration
Chung Park, Taesan Kim, Hyeongjun Yun +7
Traditional recommender systems (RS) have been primarily optimized for accuracy and short-term engagement, often overlooking transparency and trustworthiness. Recently, platforms s…