
HL
Huayang Li, Richard Sproat
· 1 min read
ResearcharXiv cs.CL
LastWords: Boring Problems Revisited
arXiv:2610.24894v1 Announce Type: new
Abstract: In 2022, the second author published a Last Words piece in Computational Linguistics in which he pointed out that, despite the advances in AI up to that point, there were still some problems in natural language processing that on the one hand seemed trivial and perhaps boring, but on the other were hard to solve using purely neural methods. One such problem discussed in that context was text normalization, and a particular subproblem of that, namely number name reading. The piece came out just a few months before the first release of ChatGPT, and needless to say, a lot has happened since then. Indeed, as we document here, the problem (of number name reading) has practically been solved, at least by one of the latest frontier models. However, we believe that there are still open issues for such limited domain, constrained and limited resource problems, and that in some future machine learning approach, the massive resources of the latest frontier models would not be needed to solve them.
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This story was published by arXiv cs.CL and written by Huayang Li, Richard Sproat. SyncAI.news shows a preview; the complete article is on the publisher's site.
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