Author

Jiarong Xu

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Book Open access Aug 2026

Think-like-LSTM: Memory-Augmented Large Language Models via Dynamic Fine-Tuning for Financial Risk Assessment

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 transaction history while ensuring cost-efficiency.

Siwei Zhang, Yun Xiong, Xi Chen et al. · Proceedings of the 32nd ACM... · 0 citations

Review Jul 2026

Traceable LLM Reasoning for Fake-Order Fraud Detection

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.

Siqi You, Bingsong Xu, Zhixiang Zheng et al. · arXiv.org · 0 citations