Search Results for author:
Found 2 papers, 2 papers with code
Memorization Capacity of Multi-Head Attention in Transformers
Transformers have become the go-to architecture for language and vision tasks, yet their theoretical properties, especially memorization capacity, remain elusive.
Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks
In this paper, we study the OOD generalization of neural algorithmic reasoning tasks, where the goal is to learn an algorithm (e. g., sorting, breadth-first search, and depth-first search) from input-output pairs using deep neural networks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
