24 citations · 47 across the 12 of their papers we have counts for
4 papers · 1 filter
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
Jianxun Lian, Yuxuan Lei, Xu Huang +3
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs). RecAI…
Aligning Large Language Models for Controllable Recommendations
Wensheng Lu, Jianxun Lian, Wei Zhang +4
Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommend…
Aligning Language Models for Versatile Text-based Item Retrieval
Yuxuan Lei, Jianxun Lian, Jing Yao +3
This paper addresses the gap between general-purpose text embeddings and the specific demands of item retrieval tasks. We demonstrate the shortcomings of existing models in capturi…
Ada-Retrieval: An Adaptive Multi-Round Retrieval Paradigm for Sequential Recommendations
Lei Li, Jianxun Lian, Xiao Zhou +1
Retrieval models aim at selecting a small set of item candidates which match the preference of a given user. They play a vital role in large-scale recommender systems since subsequ…