Portfolio

GliZNet: Generalized Zero-Shot Text Classification

Published:

A novel zero-shot multi-label text classification architecture that embeds labels directly in the input sequence, achieving efficient classification through supervised contrastive learning and label repulsion.

Semi-Supervised Learning with few labels

Published:

Semi Self-Supervised Learning: improving the performance of self-supervised learning models, especially in scenarios where only a small amount of labeled data is available