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Found 4 papers, 3 papers with code
Memory Transformer
Adding trainable memory to selectively store local as well as global representations of a sequence is a promising direction to improve the Transformer model.
Recurrent Memory Transformer
We implement a memory mechanism with no changes to Transformer model by adding special memory tokens to the input or output sequence.
Scaling Transformer to 1M tokens and beyond with RMT
A major limitation for the broader scope of problems solvable by transformers is the quadratic scaling of computational complexity with input size.
Continual and Multi-task Reinforcement Learning With Shared Episodic Memory
Episodic memory plays an important role in the behavior of animals and humans.
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