Another blunder for simple neural nets, this time in language, _exactly_ as anticipated by Marcus 2001. Sure it can be remedied but casts clear lens on a serious underlying problem that @fchollet and I have been trying to call attention to. By @bprickethttps://scholarworks.umass.edu/ics_owplinguist/2/ …
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Thanks for sharing Brandon's work Gary! As you may know,
@_shrdlu_ and@ChrisKirov are getting impressive results with seq-to-seq modeling Albright and Hayes' past tense data. So as elsewhere, the solution is likely to modify NNs rather than abandon them.
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I know the work from a conference poster.
@ChrisKirov and@_shrdlu_ have a paper in progress - I assume they'll share it with you when it's ready.Thanks. Twitter will use this to make your timeline better. UndoUndo
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