Graph Memory Transformer replaces FFN sublayers with a graph memory cell using 128 centroids and transition matrices per block, yielding stable training at 82.2M parameters but higher validation loss than a 103M dense baseline.
Memory networks
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it