Papers by Enrico Bertino

1 papers
Evaluating Transformer Language Models on Arithmetic Operations Using Number Decomposition (2022.lrec-1)

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Challenge: Large Language Models such as GPT-3 have demonstrated on-the-fly reasoning capabilities in NLP tasks, but they struggle with arithmetic operations.
Approach: They propose a Transformer Language Model that decomposes numbers in units, tens, and so on . they introduce a pipeline that allows them to perform arithmetic operations between decomposed numbers .
Outcome: The proposed model improves accuracy in addition, subtractions and multiplication tasks by 63% . the model is fine-tuned to perform arithmetic operations between decomposed numbers .

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