  Here we experiment with the use of information retrieval as an augmentation
for pre-trained language models. The text corpus used in information retrieval
can be viewed as form of episodic memory which grows over time. By augmenting
GPT 2.0 with information retrieval we achieve a zero shot 15% relative
reduction in perplexity on Gigaword corpus without any re-training. We also
validate our IR augmentation on an event co-reference task.
