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cs.IR2024

Hgformer: Hyperbolic Graph Transformer for Recommendation

Xin Yang, Xingrun Li, Heng Chang +8

The cold start problem is a challenging problem faced by most modern recommender systems. By leveraging knowledge from other domains, cross-domain recommendation can be an effectiv…

cs.IR2024

DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System

Xihong Yang, Heming Jing, Zixing Zhang +10

Benefiting from the strong reasoning capabilities, Large language models (LLMs) have demonstrated remarkable performance in recommender systems. Various efforts have been made to d…

cs.IR2024

Representation Learning with Large Language Models for Recommendation

Xubin Ren, Wei Wei, Lianghao Xia +5

Recommender systems have seen significant advancements with the influence of deep learning and graph neural networks, particularly in capturing complex user-item relationships. How…

cs.CL2024

GOVERN: Gradient Orientation Vote Ensemble for Multi-Teacher Reinforced Distillation

Wenjie Zhou, Zhenxin Ding, Xiaodong Zhang +3

Pre-trained language models have become an integral component of question-answering systems, achieving remarkable performance. However, for practical deployment, it is crucial to p…

cs.CL2024

FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding

Jingyang Deng, Zhengyang Shen, Boyang Wang +6

The development of Long-Context Large Language Models (LLMs) has markedly advanced natural language processing by facilitating the process of textual data across long documents and…