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cs.LG2026
AL-GNN: Privacy-Preserving and Replay-Free Continual Graph Learning via Analytic Learning
Xuling Zhang, Jindong Li, Yifei Zhang +2
Continual graph learning (CGL) aims to enable graph neural networks to incrementally learn from a stream of graph structured data without forgetting previously acquired knowledge.…
cs.LG2025
Bridging Molecular Graphs and Large Language Models
Runze Wang, Mingqi Yang, Yanming Shen
While Large Language Models (LLMs) have shown exceptional generalization capabilities, their ability to process graph data, such as molecular structures, remains limited. To bridge…
cs.LG2025
LemmaHead: RAG Assisted Proof Generation Using Large Language Models
Tianbo Yang, Mingqi Yan, Hongyi Zhao +1
Developing the logic necessary to solve mathematical problems or write mathematical proofs is one of the more difficult objectives for large language models (LLMS). Currently, the…