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Found 5 papers, 3 papers with code
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings
A popular natural language processing task decades ago, word alignment has been dominated until recently by GIZA++, a statistical method based on the 30-year-old IBM models.
An Alignment-Based Approach to Semi-Supervised Bilingual Lexicon Induction with Small Parallel Corpora
Aimed at generating a seed lexicon for use in downstream natural language tasks and unsupervised methods for bilingual lexicon induction have received much attention in the academic literature recently.
Knowledge Transfer via Multi-Head Feature Adaptation for Whole Slide Image Classification
Transferring prior knowledge from a source domain to the same or similar target domain can greatly enhance the performance of models on the target domain.
Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classification
Multiple Instance Learning (MIL) and transformers are increasingly popular in histopathology Whole Slide Image (WSI) classification.
Embedding-Enhanced Giza++: Improving Alignment in Low- and High- Resource Scenarios Using Embedding Space Geometry
In the lowest-resource setting, we outperform GIZA++ by 8. 5, 10. 9, and 12 AER for Ro-En, De-En, and En-Fr, respectively.
