Amir Mohammad Karimi Mamaghan

Protein language models, like LLMs, suffer from a "Curse of Depth," where deeper layers contribute surprisingly little to the final prediction, suggesting opportunities for more efficient architectures.

Object-centric representations win at compositional generalization when data is scarce, diverse, or compute-constrained, challenging the supremacy of dense representations in visually rich settings.