Self-Instantiated Recurrent Units with Dynamic Soft Recursion Aston Zhang, Yi T ay, Yikang Shen, Alvin Chan

While standard recurrent neural networks explicitly impose a chain structure on different forms of data, they do not have an explicit bias towards recursive self-instantiation where the extent of recursion is dynamic. Given diverse and even growing data modalities (e.g., logic, algorithmic input and output, music, code, images, and language) that can be expressed in sequences and may benefit from