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Do transformers need three projections? Systematic study of QKV variants

arxiv.org

51–54 of 54 posts

Re: Do transformers need three projections? Systematic study of QKV variants

#51
post #5

Hint for authors: when discussing linear algebra (or really most other kinds of math), follow normal conventions. In this case, the convention would be that - (the minus sign) means subtraction. It does not mean "and also", especially when you sandwich it between two variables that represent matrices. I read the paper with much head scratching all the way through sections 1 and 2 and part of 3 before I figured out th…

I think the primary reason it works is because the difference between K and Q, which is not all that obvious is that it’s allowing the model to have an asymmetric relationship between tokens, so one token can attend to another without the reverse being true. It seems to me if you just have a single value that you’re representing symmetric relationship, which might degrade the quality of reasoning over a set of tokens, but also is probably possible.

Re: Do transformers need three projections? Systematic study of QKV variants

#52
post #5

Hint for authors: when discussing linear algebra (or really most other kinds of math), follow normal conventions. In this case, the convention would be that - (the minus sign) means subtraction. It does not mean "and also", especially when you sandwich it between two variables that represent matrices. I read the paper with much head scratching all the way through sections 1 and 2 and part of 3 before I figured out th…

I think the primary reason it works is because the difference between K and Q, which is not all that obvious is that it’s allowing the model to have an asymmetric relationship between tokens, so one token can attend to another without the reverse being true. It seems to me if you just have a single value that you’re representing symmetric relationship, which might degrade the quality of reasoning over a set of tokens…

it seems to be something that’s similar to the class of optimizations associated with with linear or state space attention when things models often do is once they figure out an optimization like this they create a ratio between full resolution blocks and blocks that have the optimization implemented.

Re: Do transformers need three projections? Systematic study of QKV variants

#53
post #32

Earlier quoted context omitted.

Its not a math paper

Definitely an applied maths paper given that it has been published under CS/ML and been accepted at ICML.

Its not even applied math

Re: Do transformers need three projections? Systematic study of QKV variants

#54
post #11

I can see why the QKV gets used but I can't help but think that thete's got to be a better mechanism with turning a pair of vectors into a new vector and a significance field. Geometrically I imagine the process of attention like picking up a bunch of vectots and spinning and squishing them in many-D until you can find a crack where you can see all the way through, then leveraging that crack to seperate what you want…

>I can't help but think that there's got to be a better mechanism

There is.

Transformers are basically autoencoders on the decode step - they take a compressed set of information and expand it into a 3 matrices which then get combined back into one matrix.

You can unroll the entire self attention step into fully connected layers, just with a lot of zeros for things that don't get multiplied together.

So it stands to reason that there is probably an optimal form of weights that does the same thing as current transformers.

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