1 citations · 3 across the 6 of their papers we have counts for
3 papers · 1 filter
Growing to See: Efficient Pretraining of Self-Supervised Vision Transformers
Amir Mohammad Karimi Mamaghan, Ferdinand Kapl, Andrea Dittadi +4
Progressive depth growth builds large networks by starting with shallow models and inserting layers during training. Recent advances in large language models have renewed interest…
Are Object-Centric Representations Better At Compositional Generalization?
Ferdinand Kapl, Amir Mohammad Karimi Mamaghan, Maximilian Seitzer +4
Compositional generalization, the ability to reason about novel combinations of familiar concepts, is fundamental to human cognition and a critical challenge for machine learning.…
From Words to Amino Acids: Does the Curse of Depth Persist?
Aleena Siji, Amir Mohammad Karimi Mamaghan, Ferdinand Kapl +9
Protein language models (PLMs) have become widely adopted as general-purpose models, demonstrating strong performance in protein engineering and de novo design. Like large language…