13 citations · 44 across the 12 of their papers we have counts for
12 papers
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds
Lei Wang, Jianxun Lian, Yi Huang +5
Role-playing is a crucial capability of Large Language Models (LLMs), enabling a wide range of practical applications, including intelligent non-player characters, digital twins, a…
COMET: NFT Price Prediction with Wallet Profiling
Tianfu Wang, Liwei Deng, Chao Wang +5
As the non-fungible token (NFT) market flourishes, price prediction emerges as a pivotal direction for investors gaining valuable insight to maximize returns. However, existing wor…
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…
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…
Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations
Jing Yao, Wei Xu, Jianxun Lian +3
The significant progress of large language models (LLMs) provides a promising opportunity to build human-like systems for various practical applications. However, when applied to s…
A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems
Xu Huang, Jianxun Lian, Hao Wang +2
Recommendation systems effectively guide users in locating their desired information within extensive content repositories. Generally, a recommendation model is optimized to enhanc…