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Comment on DenseFormer: Enhancing Information Flow in Transformers

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This is a very interesting idea, with DenseNets there are oftentimes some terrible memory gotchas that have gotten me over the past 7-8 years or so, so a part of me is sorta leaning back waiting for some memory usage shoe to drop not specified in the paper (even with the activation patterns!)

However, maybe this is not the case. I have a bit of a history of messing with residuals in neural networks, seeing more work on it is good. Fast training networks of course are a very slightly mild obsession of mine as well, and very useful to the field. Here's hoping it pans out as a motif, curious to see where it goes.

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