Papers with zero-shot application

1 papers
No Train but Gain: Language Arithmetic for training-free Language Adapters enhancement (2025.coling-main)

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Challenge: Modular deep learning is the most effective way to lift the curse of multilinguality.
Approach: They propose a method which enables training-free post-processing to address this limitation by adding learning to the language adapters and transitioning the framework from a multi-task to a multiple language setup.
Outcome: The proposed method consistently improves baselines with significant gains, especially in the most challenging case of zero-shot application.

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