1 citations · 1 across the 7 of their papers we have counts for
7 papers
Efficient Cold-Start Recommendation via BPE Token-Level Embedding Initialization with LLM
Yushang Zhao, Xinyue Han, Qian Leng +3
The cold-start issue is the challenge when we talk about recommender systems, especially in the case when we do not have the past interaction data of new users or new items. Conten…
RLHF Fine-Tuning of LLMs for Alignment with Implicit User Feedback in Conversational Recommenders
Zhongheng Yang, Aijia Sun, Yushang Zhao +3
Conversational recommender systems (CRS) based on Large Language Models (LLMs) need to constantly be aligned to the user preferences to provide satisfying and context-relevant item…
Meta-Learning for Cold-Start Personalization in Prompt-Tuned LLMs
Yushang Zhao, Huijie Shen, Dannier Li +3
Generative, explainable, and flexible recommender systems, derived using Large Language Models (LLM) are promising and poorly adapted to the cold-start user situation, where there…
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
Haowei Yang, Yu Tian, Zhongheng Yang +3
With the rapid adoption of large language models (LLMs) in recommendation systems, the computational and communication bottlenecks caused by their massive parameter sizes and large…
Research on Personalized Financial Product Recommendation by Integrating Large Language Models and Graph Neural Networks
Yushang Zhao, Yike Peng, Dannier Li +3
With the rapid growth of fintech, personalized financial product recommendations have become increasingly important. Traditional methods like collaborative filtering or content-bas…
Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
Junli Shao, Jing Dong, Dingzhou Wang +3
With the rapid growth of Internet services, recommendation systems play a central role in delivering personalized content. Faced with massive user requests and complex model archit…
Research on E-Commerce Long-Tail Product Recommendation Mechanism Based on Large-Scale Language Models
Qingyi Lu, Haotian Lyu, Jiayun Zheng +3
As e-commerce platforms expand their product catalogs, accurately recommending long-tail items becomes increasingly important for enhancing both user experience and platform revenu…