activity
20222024
most citedLlamaRec: Two-Stage Recommendation using Large Language Models for Ranking

14 citations · 21 across the 9 of their papers we have counts for

collaborators

9 papers

cs.IR2024

Transferable Sequential Recommendation via Vector Quantized Meta Learning

Zhenrui Yue, Huimin Zeng, Yang Zhang +2

While sequential recommendation achieves significant progress on capturing user-item transition patterns, transferring such large-scale recommender systems remains challenging due…

cs.CL2024

Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments

Zhenrui Yue, Huimin Zeng, Lanyu Shang +3

The rapid propagation of misinformation poses substantial risks to public interest. To combat misinformation, large language models (LLMs) are adapted to automatically verify claim…

cs.CL20243 cited

Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation

Zhenrui Yue, Huimin Zeng, Yimeng Lu +3

The proliferation of online misinformation has posed significant threats to public interest. While numerous online users actively participate in the combat against misinformation,…

cs.IR2024

Federated Recommendation via Hybrid Retrieval Augmented Generation

Huimin Zeng, Zhenrui Yue, Qian Jiang +1

Federated Recommendation (FR) emerges as a novel paradigm that enables privacy-preserving recommendations. However, traditional FR systems usually represent users/items with discre…

cs.IR20231 cited

Linear Recurrent Units for Sequential Recommendation

Zhenrui Yue, Yueqi Wang, Zhankui He +3

State-of-the-art sequential recommendation relies heavily on self-attention-based recommender models. Yet such models are computationally expensive and often too slow for real-time…

cs.IR202314 cited

LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking

Zhenrui Yue, Sara Rabhi, Gabriel de Souza Pereira Moreira +2

Recently, large language models (LLMs) have exhibited significant progress in language understanding and generation. By leveraging textual features, customized LLMs are also applie…