Self-supervised speech representation learning: A review
Although supervised deep learning has revolutionized speech and audio processing, it has
necessitated the building of specialist models for individual tasks and application scenarios …
necessitated the building of specialist models for individual tasks and application scenarios …
Teaching matters: Investigating the role of supervision in vision transformers
Abstract Vision Transformers (ViTs) have gained significant popularity in recent years and
have proliferated into many applications. However, their behavior under different learning …
have proliferated into many applications. However, their behavior under different learning …
On the stepwise nature of self-supervised learning
We present a simple picture of the training process of self-supervised learning methods with
dual deep networks. In our picture, these methods learn their high-dimensional embeddings …
dual deep networks. In our picture, these methods learn their high-dimensional embeddings …
Understanding cross-domain few-shot learning based on domain similarity and few-shot difficulty
Cross-domain few-shot learning (CD-FSL) has drawn increasing attention for handling large
differences between the source and target domains--an important concern in real-world …
differences between the source and target domains--an important concern in real-world …
Convnet vs transformer, supervised vs clip: Beyond imagenet accuracy
K Vishniakov, Z Shen, Z Liu - ar**
The rise of self-supervised learning (SSL) methods in recent years presents an opportunity
to leverage unlabeled and domain-specific datasets generated by image-based plant …
to leverage unlabeled and domain-specific datasets generated by image-based plant …