2 papers
cs.CV2023
DeAR: Debiasing Vision-Language Models with Additive Residuals
Ashish Seth, Mayur Hemani, Chirag Agarwal
Large pre-trained vision-language models (VLMs) reduce the time for developing predictive models for various vision-grounded language downstream tasks by providing rich, adaptable…
eess.AS2023
UNFUSED: UNsupervised Finetuning Using SElf supervised Distillation
Ashish Seth, Sreyan Ghosh, S. Umesh +1
In this paper, we introduce UnFuSeD, a novel approach to leverage self-supervised learning and reduce the need for large amounts of labeled data for audio classification. Unlike pr…