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0 results for “computational complexity”
Hierarchical Grading in Large Language Models
Researchers propose Graded Large Language Models (GLLMs), a theoretical extension of transformer architecture using algebraic grading to improve statistical efficiency for level-stratified prediction tasks, with claims of provable risk separation and pre-certified optimization.
Jul 28, 2026
On the Computational Complexity of Structural Generalization
A theoretical computer science paper formally defines structural generalization and proves that pure Transformer architectures cannot learn it under standard complexity assumptions, shifting focus from benchmark scores to architectural necessity.
Jul 23, 2026
STAGformer: A Spatio-temporal Agent Graph Transformer for Micro Mobility Demand Forecasting
STAGformer is a new graph transformer architecture designed for station-level bike-sharing demand forecasting, claiming linear computational complexity and superior accuracy over existing models on NYC and Chicago datasets.
Jul 10, 2026