Author

Xi Chen

Fudan University

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#machine learning Preprint Oct 2026

GRAM: Correcting Frozen Time-Series Foundation Models via Graph-Retrieved Amplitude Memory

Time-series foundation models (TSFMs) enable zero-shot forecasting through large-scale cross-domain pretraining, while retrieval augmentation further improves their performance by leveraging historical information. However, existing methods typically correct TSFM forecasts using the ground-truth futures of similar hist...

Xiao-Yun Yu, Xiangfei Qiu, Yong-Gui Huang et al. · 0 citations

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 transa...

Si-Wei Zhang, Yun Xiong, Xi Chen et al. · Proceedings of the 32nd ACM... · 1 citation

Book Open access Aug 2026

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

Financial risk assessment (FRA) seeks to forecast the likelihood of user default based on transaction sequences, which are inherently sequential and enriched with textual attributes. Despite the remarkable potential of large language models (LLMs) in sequential modeling and semantic understanding, developing LLM-based...

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