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Locality Does Not Imply Reachability: Boundary Repair in Block-Sparse Causal Attention

Industrial AI

Summary

arXiv:2606.02680v1 Announce Type: new Abstract: Sparse causal attention is usually described by sequence locality: nearby tokens should remain easy to access, while distant tokens may be dropped to reduce cost. This paper studies a mismatch between sequence locality and attention-graph reachability. In fixed block causal attention, two adjacent tokens can be disconnected in the attention graph at every depth.

Why It Matters

This Industrial AI development deepens the link between AI compute and industrial productivity. For Asia, it is a signal worth tracking: it shapes who supplies, who scales, and who sets the standard over the next five years.

Key Facts

  • SectorIndustrial AI
  • Market
  • ImpactLow (42/100)
  • SignalResearch

Original Sources

arXiv AI / Machine Learning ↗ https://arxiv.org/abs/2606.02680

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