73 citations · 169 across the 12 of their papers we have counts for
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cs.IR2024★ 1 cited
L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering
Xinzhou Jin, Jintang Li, Liang Chen +6
Graph neural networks (GNNs) have recently emerged as an effective approach to model neighborhood signals in collaborative filtering. Towards this research line, graph contrastive…
cs.LG2024
CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network
Chenglin Li, Yuanzhen Xie, Chenyun Yu +4
Inductive representation learning on temporal heterogeneous graphs is crucial for scalable deep learning on heterogeneous information networks (HINs) which are time-varying, such a…
cs.CL2024
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm
Yuanzhen Xie, Xinzhou Jin, Tao Xie +7
In-context learning of large-language models (LLMs) has achieved remarkable success in the field of natural language processing, while extensive case studies reveal that the single…