3 citations · 3 across the 3 of their papers we have counts for
4 papers
CausalRec: A CausalBoost Attention Model for Sequential Recommendation
Yunbo Hou, Tianle Yang, Ruijie Li +5
Recent advances in correlation-based sequential recommendation systems have demonstrated substantial success. Specifically, the attention-based model outperforms other RNN-based an…
AuroRA: Breaking Low-Rank Bottleneck of LoRA with Nonlinear Mapping
Haonan Dong, Wenhao Zhu, Guojie Song +1
Low-Rank Adaptation (LoRA) is a widely adopted parameter-efficient fine-tuning (PEFT) method validated across NLP and CV domains. However, LoRA faces an inherent low-rank bottlenec…
DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
Qin Chen, Liang Wang, Bo Zheng +1
The pre-train then fine-tune approach has advanced GNNs by enabling general knowledge capture without task-specific labels. However, an objective gap between pre-training and downs…
AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers
Wenhao Zhu, Guojie Song, Liang Wang +1
Graph Transformers (GTs) have significantly advanced the field of graph representation learning by overcoming the limitations of message-passing graph neural networks (GNNs) and de…