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Asymmetric Looped Transformers: Fixed Global Representations for an Iterative Decoder
Looped Transformers increase effective depth by repeatedly applying shared layers, offering a way to scale computation without increasing parameter count. However, full-stack looping places context construction and iterative state refinement within the same recurrent computation, without explicitly
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