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Found 6 papers, 2 papers with code
PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniques
Our study conducts extensive experiments to compare different PEFT methods and their layer-wise placement adapting Differentiable Architecture Search (DARTS).
How to Estimate Model Transferability of Pre-Trained Speech Models?
In this work, we introduce a "score-based assessment" framework for estimating the transferability of pre-trained speech models (PSMs) for fine-tuning target tasks.
CHAPTER: Exploiting Convolutional Neural Network Adapters for Self-supervised Speech Models
However, such efficient tuning techniques only provide adaptation at the transformer layer, but failed to perform adaptation at the feature extractor.
Exploring Efficient-tuning Methods in Self-supervised Speech Models
In downstream tasks, the parameters of SSL models are frozen, and only the adapters are trained.
Learning Facial Liveness Representation for Domain Generalized Face Anti-spoofing
Face anti-spoofing (FAS) aims at distinguishing face spoof attacks from the authentic ones, which is typically approached by learning proper models for performing the associated classification task.
AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks
Transformer-based pre-trained models with millions of parameters require large storage.
