Semanlink - Favoris ; Artificial Intelligence ; Mémoire AND Guillaume Lample

Search Tag:

Search Doc:

Preferences...

Tag Cloud

Arxiv Doc - Guillaume Lample - Language Model - Ludovic Denoyer - Memory in deep learning - NLP@Facebook - Transformers - Tweet -

Favoris ; Artificial Intelligence ; Mémoire AND Guillaume Lample

Common descendants

2 Documents

Guillaume Lample sur Twitter : "Last year, we showed that you can outperform a 24-layer transformer in language modeling with just...

Tags:

2020-10-10 About

[1907.05242] Large Memory Layers with Product Keys

Tags:

> **a structured memory which can be easily integrated into a neural network.** The memory is very large by design and therefore significantly increases the capacity of the architecture, by up to a billion parameters with a negligible computational overhead. Its design and access pattern is based on **product keys**, which enable fast and exact nearest neighbor search. The ability to increase the number of parameters while keeping the same computational budget lets the overall system strike a better trade-off between prediction accuracy and computation efficiency both at training and test time.

> a key-value memory layer that can increase model capacity for a negligible computational cost. A 12-layer transformer with a memory outperforms a 24-layer transformer, and is 2x faster!

[Implementation](/doc/2019/08/product_key_memory_pkm_minima)

TODO: compare with [[2007.00849] Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge](doc:2020/07/2007_00849_facts_as_experts_)

2019-07-13 About