Nov. 3, 2023, 6:32 p.m. | Allen Institute for AI

Allen Institute for AI www.youtube.com

Abstract: Cross-lingual semantic parsing transfers parsing capability from a high-resource language (e.g., English) to low-resource languages with scarce training data. Previous work has primarily considered silver-standard data augmentation or zero-shot methods, however, exploiting few-shot gold data is comparatively unexplored. We propose a new approach to cross-lingual semantic parsing by explicitly minimizing cross-lingual divergence between probabilistic latent variables using Optimal Transport. We demonstrate how this direct guidance improves parsing from natural languages using fewer examples and less training. We evaluate our …

beyond bio compute constraints cross-lingual data english languages meta meta-learning modeling optimization parsing phd prediction research robustness semantic strategies work

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