Cross-Modal Temporal Graph Transformers for Explainable NFT Valuation and Information-Centric Risk Forecasting in Web3 Markets

NFT prices are shaped by heterogeneous signals including visual appearance, textual narratives, transaction trajectories, and on-chain interactions, yet existing studies often model these factors in isolation and rarely unify multimodal alignment, temporal non-stationarity, and heterogeneous relatio...

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Автори:	Fang Lin, Yitong Yang, Jianjun He
Формат:	Artigo
Мова:	Inglês
Опубліковано:	MDPI AG 2026-01-01
Серія:	Information
Предмети:	cross-modal fusion temporal–graph transformers heterogeneous graph modeling time-series forecasting explainable AI risk-aware learning
Онлайн доступ:	https://www.mdpi.com/2078-2489/17/2/112
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