[reaperman]

The architecture is described enough to re-implement it and train it on known datasets/benchmarks such as VQA2. A single man with a medical degree named Phil Wang ('lucidrains')[0] has the ability to reproduce most of these papers by himself. He has 246 GitHub repos[1], most of which appear to be reproductions of models which are only described in papers that had no associated code or models released, such as [2]. Often it appears he releases code within 2 weeks of a paper's publication on ArXiv.

0: https://lucidrains.github.io

1: https://github.com/lucidrains

2: https://paperswithcode.com/paper/coca-contrastive-captioners...

[anentropic]

Given that fact, why don't the paper authors just release the artefacts then?

If it's supposed to stay secret, what's the point of "here's instructions for how to reproduce our big secret"?

Presumably the societal purpose of papers is to share knowledge, and the individual purpose is to take credit and win prestige.

It seems like the first purpose would be better served by also publishing code etc, and the second purpose wouldn't be harmed by it?

[mirker]

Because the authors don’t get a large reward for open sourcing the work and they stand to lose future value by lowering the gate to competition. You may want the code, but Google will not care (or it might dislike it).

Look at GPT-3+, OpenAI gets fame and fortune while people struggle to reproduce their last-gen models.

[xiphias2]

Probably because the research code is not as nice as one rewritten from scratch anyways, and it's using internal data sets / APIs.

They just want to get onto the next research instead of taking time to publish a clean open-source implementation, which can (and will) be done by somebody else anyways.

[AdoHaha]

He indeed re-implemented the MaMMUT: https://github.com/lucidrains/MaMMUT-pytorch