Three beauties meet in this paper. Words in one language end up internally aligned by meaning. For languages with shared structure, that arrangement is shaped almost the same way across both. A GAN and an SVD recover the rotation between them, strongly for close pairs, weakly for distant ones, with no parallel text.
An interactive exploration of how Google’s Universal Sentence Encoder captures semantic context, visualized using graph databases. Read the full article on Medium → Originally published on Medium’s Data Science publication. This is one of my favorite articles showcasing the power of semantic embeddings through visual exploration.
Exploring how to improve DSPy optimizers using hard negative examples to enhance model performance. Read the full article on Medium → Originally published on Medium’s Data Science publication.
Learn how to create custom datasets in PyTorch for text and machine translation tasks with practical examples. Read the full article on Medium → Originally published on Medium’s Data Science publication.