Slot attention vs Transformer

[MLDeS]

Question edited for clarity:

What are the conceptual and technical differences between Slot Attention and Transformer modules, particularly in terms of their architectural components like the use of a GRU cell in Slot Attention versus the absence of such in Transformers? How might these differences influence the outcomes and interpretations of results when applied to tasks such as object-centric learning? Would substituting Slot Attention with a Transformer module in a given architecture yield comparable performance, or are there theoretical considerations that would necessitate adjustments to maintain functionality?