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NeurIPS 2026ETH ZürichHuawei ResearchHuawei Technologies SwitzerlandEfficient attention & state-space models

Approaching I/O-optimality for Approximate Attention

Approximate attention algorithms achieve near-linear I/O cost in sequence length via efficient approximate methods with matching lower bounds proving near-optimality.

Pál András Papp, Aleksandros Sobczyk, Anastasios Zouzias

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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strict 3/5
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NeurIPS 2026Huawei ResearchHuawei Technologies Ltd.HuaweiHuawei Technologies SwitzerlandEfficient attention & state-space models

Fast and Stable Triangular Inversion for Delta-Rule Linear Transformers

Systematic analysis of triangular inversion for delta-rule linear transformers yields algorithms with up to 4.3x speedup on NPUs and preserved end-to-end accuracy across low-precision settings.

Aleksandros Sobczyk, Gioele Gottardo, Christos K Matzoros, Mirko De Vita and 3 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 7 of 20 reviewers recommend it
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medium 3/10
strict 0/5