Papers with TyDiQA
Sharpness-Aware Minimization Improves Language Model Generalization (2022.acl-long)
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| Challenge: | Comparatively little work has been done to improve the generalization of language models . recent work shows that Sharpness-Aware Minimization (SAM) can improve generalization without much computational overhead. |
| Approach: | They propose a Sharpness-Aware Minimization procedure that encourages convergence to flatter minima to improve generalization of language models without much computational overhead. |
| Outcome: | The proposed Sharpness-Aware Minimization procedure can improve language models without much computational overhead. |