Neurosymbolic AI Advances State of the Art on Math Word Problems (opens in new tab)

Is the peer-reviewed paper available anywhere yet?

This article doesn't tell us anything about the Neurosymbolic AI approach except that it performs well and "essentially combines two existing techniques: neural attention Transformers...and tensor product representation".

Searching for Nuerosymbolic I can only find this paper from 2017 at Microsoft Reasearch. It is from 2017 and uses an RNN to incrementally grows some input source code.

https://www.microsoft.com/en-us/research/publication/neuro-s...

>The first module, called the cross correlation I/O network, given a set of input-output examples, produces a continuous representation of the set of I/O examples. The second module, the RecursiveReverse-Recursive Neural Network (R3NN), given the continuous representation of the examples, synthesizes a program by incrementally expanding partial programs

I think stuff like this is very interesting and look forward to a future of old-hats complaining that new programmers let the intellisense write all their code for them.

This article seems pointless without detailing any of the results, why not give some numbers on their performance on benchmarks?

(I contributed to the PureAI article) The research article is still under peer review so that's why no detailed accuracy information or explanation of the technique can be published yet. If the PureAI article gave details, there'd be nothing to prevent an unscrupulous person from hijacking the content and establishing copyright/patent for the intellectual property. I have seen the research paper and it presents full information about the technique and the experimental results.

James M