[lkois]

My last job was centered around trying to reproduce the results of deep learning academic papers, and maybe porting them to other frameworks or platforms.

Even WITH code supplied by the authors, this was always a struggle. It'd usually take about a week or so just to get their github project out of dependency hell and actually run at all.

And if it needed to be reproduced in another framework, I'd really really want some kind of demo code just to clarify what exactly the authors were trying to describe. Especially if their descriptions had holes or discrepancies that only became clear when trying to fit the pieces together.

I remember trying to reproduce a couple of object tracking papers from the same authors, one with an overly complex and poorly defined feature set, the other with a glaring mistake/omission that forced my team to redesign the model because they described using a certain layer type in a way that made no sense.

There were a few good exceptions that provided nice code, but difficult reproduction seemed to be the norm.