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

14 citations · 18 across the 8 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.IR2024

Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation

Yueqi Wang, Zhenrui Yue, Huimin Zeng +2

Despite recent advancements in language and vision modeling, integrating rich multimodal knowledge into recommender systems continues to pose significant challenges. This is primar…

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.IR2024

Your Causal Self-Attentive Recommender Hosts a Lonely Neighborhood

Yueqi Wang, Zhankui He, Zhenrui Yue +2

In the context of sequential recommendation, a pivotal issue pertains to the comparative analysis between bi-directional/auto-encoding (AE) and uni-directional/auto-regressive (AR)…

cs.CL2024

Open-Vocabulary Federated Learning with Multimodal Prototyping

Huimin Zeng, Zhenrui Yue, Dong Wang

Existing federated learning (FL) studies usually assume the training label space and test label space are identical. However, in real-world applications, this assumption is too ide…

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,…