ChaCAL Resolvent
Cross-source consensus on ChaCAL Resolvent from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Benefits
Highlighted claims
- ChaCAL replaces one-hop attention with a resolvent-style operator applied to values. — Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity
- The ChaCAL resolvent aggregates multi-hop attention paths in one layer through the Neumann expansion. — Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity
- For causal attention matrices, the resolvent application can use forward substitution because the relevant matrix is triangular with positive diagonal entries. — Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity
- ChaCAL and Block-ChaCAL can solve shallow BOXES-style tasks because their inverse term aggregates longer paths directly. — Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity