TIDE is a neuro-inspired architecture using stabilized asymmetric E-I networks with lateral inhibition and 80:20 balance that trains in under half the time of CTM while gaining +1.65% top-1 accuracy on perturbed ImageNet.
Gomez, Łukasz Kaiser, and Illia Polosukhin
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
PTNet is a prototype-guided task-adaptive model that jointly performs change detection and captioning on bi-temporal UAV imagery by modeling structured change semantics, outperforming prior methods on the new UCCD urban construction benchmark and WHU-CDC.
citing papers explorer
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TIDE: Asymmetric Neural Circuits for Stabilized Temporal Inhibitory-Excitatory Dynamics
TIDE is a neuro-inspired architecture using stabilized asymmetric E-I networks with lateral inhibition and 80:20 balance that trains in under half the time of CTM while gaining +1.65% top-1 accuracy on perturbed ImageNet.
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UAV as Urban Construction Change Monitor: A New Benchmark and Change Captioning Model
PTNet is a prototype-guided task-adaptive model that jointly performs change detection and captioning on bi-temporal UAV imagery by modeling structured change semantics, outperforming prior methods on the new UCCD urban construction benchmark and WHU-CDC.