Flexformer learns attention kernels by treating spectral frequencies as trainable parameters in random Fourier feature-based linear attention, with stationary and nonstationary variants that outperform fixed-kernel baselines.
Parallel and serial grouping of image elements in visual perception.Journal of Experimental Psychology: Human Perception and Performance, 2010
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
-
Flexformer: Flexible Linear Transformer with Learnable Attention Kernel
Flexformer learns attention kernels by treating spectral frequencies as trainable parameters in random Fourier feature-based linear attention, with stationary and nonstationary variants that outperform fixed-kernel baselines.