Keqin Bao

Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation

2024 · arXiv (Cornell University)

Recent advancements in recommender systems have focused on leveraging Large Language Models (LLMs) to improve user preference modeling, yielding promising outcomes. However, current LLM-based approaches struggle to fully leverage user behavior sequences, resulting in suboptimal …

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation

2023

Large Language Models (LLMs) have demonstrated remarkable performance across diverse domains, thereby prompting researchers to explore their potential for use in recommendation systems. Initial attempts have leveraged the exceptional capabilities of LLMs, such as rich …