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cs.LG2026
Weight Pair Encoding: Inducing a Smaller Grammar in Neural Network Weights
Irene Tallini, Daniele Solombrino, Alberto Cazzaniga +1
We show that neural network weights can be explicilty fintuned to admit a smaller grammar. Weight Pair Encoding (WeightPE) does so by placing a lossy Re-Pair compressor inside a st…
cs.LG2023★ 16 cited
The geometry of hidden representations of large transformer models
Lucrezia Valeriani, Diego Doimo, Francesca Cuturello +3
Large transformers are powerful architectures used for self-supervised data analysis across various data types, including protein sequences, images, and text. In these models, the…