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cs.LG2026
Finetune-Informed Pretraining Boosts Downstream Performance
Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan +2
Multimodal pretraining is effective for building general-purpose representations, but in many practical deployments, only one modality is heavily used during downstream fine-tuning…
cs.CV2026
Semi-Supervised Masked Autoencoders: Unlocking Vision Transformer Potential with Limited Data
Atik Faysal, Mohammad Rostami, Reihaneh Gh. Roshan +2
We address the challenge of training Vision Transformers (ViTs) when labeled data is scarce but unlabeled data is abundant. We propose Semi-Supervised Masked Autoencoder (SSMAE), a…