A PyTorch implementation of slot attention

In this work, we propose disentangled domain-slot attention for multi-domain dialogue state tracking The proposed approach disentangles the domain-slot

A PyTorch implementation of slot attention We empirically demonstrate that Slot Attention can extract object-centric representations that enable generalization to unseen compositions when trained on

In this work, we propose disentangled domain-slot attention for multi-domain dialogue state tracking The proposed approach disentangles the domain-slot

slot game cartoon png A widely adopted method within OCL is slot attention, which utilizes attention mechanisms to iteratively refine slot representations However, a major

Slot attention is a powerful method for object-centric modeling in images and videos However, its set-equivariance limits its ability to handle videos with

slot machine birthday Explainable artificial intelligence has been gaining attention in the past few years However, most existing methods are based on gradients or intermediate

We empirically demonstrate that Slot Attention can extract object-centric representations that enable generalization to unseen compositions when trained on