Presents I/O-efficient algorithms for approximate attention with almost-linear cost in n, approaching lower bounds in most parameter regimes.
Smyrf-efficient attention using asymmetric clustering.Advances in Neural Information Processing Systems (NeurIPS), 33:6476–6489, 2020
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Approaching I/O-optimality for Approximate Attention
Presents I/O-efficient algorithms for approximate attention with almost-linear cost in n, approaching lower bounds in most parameter regimes.