Recurrent Looped Transformer (yifanzhang-pro.github.io)

14 points by MayCXC 3 hours ago

7 comments:

by vatsachak 21 minutes ago

Paper written by AI

by dankai an hour ago

Is this just a theory about an architecture or are there actually some benchmarks/results to substantiate it?

by jal278 an hour ago

appears it's just a theory, sort of surprised this lifted up so far on hn

by fc417fc802 22 minutes ago

A fairly obvious theory at that, unless I've critically misunderstood what's being described. As with so many obvious ideas I've always assumed that the reason I haven't come across it in the wild is because it doesn't work (or is comparatively inefficient, or tends to blow up during the training run, or etc).

> Realized reasoning gains, hardware efficiency, and RL scaling remain to be established.

Yeah so the first entry in that list is - if I may be so bold - typically what you'd start with at a small scale _before_ writing up and publishing your "genius" idea. This is the usual crank with delusions of grandeur presenting something straightforward that he hasn't tested as though it were a working breakthrough.

Ironically the cost of testing such theories has fallen to an all time low given the capabilities of coding models. I wouldn't be surprised if a frontier model could one shot a test of this.

by jal278 an hour ago

not sure w/o context why this is important -- no results/implementation & i believe there are prior combinations of transformers/RNNs. but perhaps I'm missing the relevance/insight

by lstodd 24 minutes ago
by fc417fc802 5 minutes ago

I can't believe that actually works? This is far more interesting than the half baked ML idea.

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