27 citations · 49 across the 13 of their papers we have counts for
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cs.LG2024
Node Level Graph Autoencoder: Unified Pretraining for Textual Graph Learning
Wenbin Hu, Huihao Jing, Qi Hu +2
Textual graphs are ubiquitous in real-world applications, featuring rich text information with complex relationships, which enables advanced research across various fields. Textual…
cs.CR2024★ 3 cited
Simulate and Eliminate: Revoke Backdoors for Generative Large Language Models
Haoran Li, Yulin Chen, Zihao Zheng +4
With rapid advances, generative large language models (LLMs) dominate various Natural Language Processing (NLP) tasks from understanding to reasoning. Yet, language models' inheren…
cs.LG2024★ 1 cited
Learning Federated Neural Graph Databases for Answering Complex Queries from Distributed Knowledge Graphs
Qi Hu, Weifeng Jiang, Haoran Li +6
The increasing demand for deep learning-based foundation models has highlighted the importance of efficient data retrieval mechanisms. Neural graph databases (NGDBs) offer a compel…