The Geometric Space, Architecture and Learning Objective for Large Pre-Trained Models (GALOP) workshop is an accepted half-day KDD 2026 workshop that examines how geometric principles can make large pretrained models more expressive, robust, interpretable, and efficient.
Meng-Lin Yang, Jia-Hong Liu, Lucas Vinh Tran et al.· Proceedings of the 32nd ACM...· 1 citation
Large Language Models (LLMs) are increasingly deployed in financial applications, particularly for interpreting U.S. Securities and Exchange Commission (SEC) filings. However, financial QA over these filings is challenging, as they are extremely long, numerically dense, and often require cross-document reasoning. Exist...
Eftychia Makri, Peiwen Li, Yidong Jiang et al.· Proceedings of the 32nd ACM...· 0 citations
Large pretrained models have reshaped artificial intelligence, yet their Euclidean design assumptions often limit their ability to model hierarchy, curvature, symmetry, and heterogeneous relations in real-world data. The Geometric Space, Architecture and Learning Objective for Large Pre-Trained Models (GALOP) workshop...
Menglin Yang, Jiahong Liu, Lucas Vinh Tran et al.· Proceedings of the 32nd ACM...· 0 citations
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