Speech-FT applies drift-reduced fine-tuning followed by weight-space interpolation to improve both task performance and cross-task generalization in models such as HuBERT and WavLM.
Fine-Tuning Can Distort Pretrained Features and Underperform Out-of-Distribution
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization
Speech-FT applies drift-reduced fine-tuning followed by weight-space interpolation to improve both task performance and cross-task generalization in models such as HuBERT and WavLM.