Papers with FSAM

2 papers
Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models (2022.findings-emnlp)

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Challenge: Existing methods for fine-tuning pretrained language models suffer from poor generalization . however, they add a perturbation to each model parameter equally, which is sub-optimal .
Approach: They propose a sharpness-aware minimization optimization procedure that introduces a Fisher mask to improve the efficiency of SAM.
Outcome: The proposed method outperforms the vanilla sharpness-aware minimization method on GLUE and SuperGLUE benchmarks.
Finite State Machine Pattern-Root Arabic Morphological Generator, Analyzer and Diacritizer (2020.lrec-1)

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Challenge: Using a finite-state morphologizer, we generate and analyze undiacritized Modern Standard Arabic (MSA) words.
Approach: They propose to use a finite-state Arabic Morphologizer to generate and analyze undiacritized Arabic words and diacritize them.
Outcome: The proposed model generates and analyzes undiacritized Modern Standard Arabic (MSA) words and diacritizes them.

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