Papers by Mohammadreza Tayaranian Hosseini

1 papers
Towards Fine-tuning Pre-trained Language Models with Integer Forward and Backward Propagation (2023.findings-eacl)

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Challenge: Previously, researchers focused on lower bit-width integer data types for forward propagation and backward propagation of language models to save memory and computation.
Approach: They use integer arithmetic for both forward and back propagation in the fine-tuning of BERT.
Outcome: The proposed method improves on the GLUE and SQUAD benchmarks.

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