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ID2Pattern is proposed, a pretraining framework that brings high-cardinality identity fields into transaction foundation models and remains equally effective even when all identity values are unseen during training, highlighting its potential to generalize to new users and markets.
This work presents FinFraudBench, a heterogeneous graph benchmark for financial fraud detection, and establishes a standardized evaluation protocol covering both ranking and imbalance-sensitive classification metrics, and evaluates representative baselines.
FinRiskAtlas is introduced, a Chinese-language benchmark that evaluates financial LLMs along two complementary dimensions: operation execution under fixed evidence states and evidence-state control under evolving review conditions, and shows that broad financial capability scores do not fully capture where models are r...
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