QSV: Quat-Sphere-Vision for Coupled Quaternion Attention on Spherical Lattices

arXiv:2609.30592 · cs.LG, cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.LG, cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Accuracy — 34× in this paper · explained in 1 episode
• Transformer — 18× in this paper · explained in 2 episodes
• Ablation — 14× in this paper · explained in 1 episode
• Aggregation — 9× in this paper · explained in 1 episode
• Adam — 6× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 3× in this paper
• Regularization — 3× in this paper · explained in 3 episodes
• In International Conference on Machine Learning — 2× in this paper
• Point Clouds — 2× in this paper · explained in 2 episodes
• Attention Entropy — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 1× in this paper
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Entropy Collapse — 1× in this paper · explained in 2 episodes
• In Asian Conference on Machine Learning — 1× in this paper
• In European Conference on Computer Vision — 1× in this paper
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Riemannian optimization — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• Is Random Attention Sufficient for Sequence Modeling? Disentangling Trainable Components in the Transformer
• RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways
• Escaping the Big Data Paradigm with Compact Transformers
• RiemannFormer: A Framework for Attention in Curved Spaces
• CliffordNet: All You Need is Geometric Algebra
• Quaternion Self-Attention with Shared Scores
• GeoPE:A Unified Geometric Positional Embedding for Structured Tensors

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