This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 1441–1442 of 1442 papers
Junying Fan, Daojuan Wang, Yuhua Zheng
This paper proposes FinATG, an AI-driven framework for extracting sustainability-related financial information from English texts to support ESG investment decisions in emerging markets. It achieves entity F1 of 88.5 and REL F1 of 80.2 on s…
Nadia Mansour
This systematic review of 42 studies (2018–2025) examines AI, IoT, and blockchain in sustainable finance. It identifies three application areas: enhanced MRV of environmental impacts, improved physical and transition risk control via predic…
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