Papers by Alberto Testolin

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Challenge:	Large Language Models (LLMs) have revolutionized the field of natural language processing . however, it has been shown that they lack systematic generalization, which allows to extrapolate the learned statistical regularities outside the training distribution.
Approach:	They propose to benchmark a LLM with two parameters to find out its performance . they compare it to a variant of the Transformer-Encoder architecture to find the same problem .
Outcome:	The proposed model outperforms the previous model on three algorithmic tasks with two parameters.