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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Evaluating Morphological Alignment of Tokenizers in 70 Languages · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2507.06378/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2507.06378/feed.xml" rel="self" type="application/rss+xml" /><item><title>Evaluating Morphological Alignment of Tokenizers in 70 Languages — mentioned by ipieter</title><link>https://news.ycombinator.com/item?id=47830894</link><guid isPermaLink="false">urn:hackerpapers:mention:2507.06378:47830894</guid><pubDate>Mon, 20 Apr 2026 06:04:35 GMT</pubDate><description>&lt;p&gt;There is currently very little evidence that morphological tokenizers help model performance [1]. For languages like German (where words get glued together) there is a bit more evidence (eg a paper I worked on [2]), but overall I start to suspect the bitter lesson is also true for tokenization. [1] https://arxiv.org/pdf/2507.06378 [2] https://pieter.ai/bpe-knockout/&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2507.06378/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
