Graph federated learning (FL) allows multiple agents to collaboratively train a global graph model while preserving data privacy. However, current methods overlook the issue of low-quality or malicious data contributions, which can degrade the global model’s performance. This paper addresses this gap by proposing a nov...
Cheng-Lu Pan, Jia-Rong Xu, Carl Yang et al.· ACM Transactions on Knowledg...· 0 citations
FraLLM is a novel LLM fine-tuning framework that seamlessly internalizes transaction-oriented knowledge for FRA and introduces the Memory Token Mechanism, which recurrently aggregates historical text prototypes into a compact, continuously updated memory token that allows LLMs to effectively synthesize long-term transa...
Si-Wei Zhang, Yun Xiong, Xi Chen et al.· Proceedings of the 32nd ACM...· 1 citation
Results show that DeepScrub improves fraud review accuracy, reduces first-stage review workload, and provides traceable evidence for production risk-review workflows, showing that domain adaptation can matter more than model scale in this setting.
