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Found 5 papers, 2 papers with code
Could We Have Had Better Multilingual LLMs If English Was Not the Central Language?
Large Language Models (LLMs) demonstrate strong machine translation capabilities on languages they are trained on.
Explain-then-Translate: An Analysis on Improving Program Translation with Self-generated Explanations
This work explores the use of self-generated natural language explanations as an intermediate step for code-to-code translation with language models.
AugCSE: Contrastive Sentence Embedding with Diverse Augmentations
Data augmentation techniques have been proven useful in many applications in NLP fields.
Knowledge Based Template Machine Translation In Low-Resource Setting
Incorporating tagging into neural machine translation (NMT) systems has shown promising results in helping translate rare words such as named entities (NE).
Discrete Word Embedding for Logical Natural Language Understanding
We propose an unsupervised neural model for learning a discrete embedding of words.
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