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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adaptive Machine Translation with Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2301.13294/</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/2301.13294/feed.xml" rel="self" type="application/rss+xml" /><item><title>Adaptive Machine Translation with Large Language Models — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=37513531</link><guid isPermaLink="false">urn:hackerpapers:mention:2301.13294:37513531</guid><pubDate>Thu, 14 Sep 2023 19:20:04 GMT</pubDate><description>&lt;p&gt;&amp;gt;It&amp;#x27;s not under the radar because that&amp;#x27;s sadly not the case It is the case. Haven&amp;#x27;t seen anyone who uses both who thinks otherwise. also https://arxiv.org/abs/2301.13294. This benchmarks 3.5 which is quite a bit worse than 4 as it is against Google, NLLB, Deepl here https://arxiv.org/pdf/2304.02210.pdf, GPT wins overwhelmingly with human evaluations. Seems like the typically evaluation models aren&amp;#x27;t really cutting it anymore especially BLEU &amp;gt;Neural machine translation is just more consistent, doesn&amp;#x27;t hallucinate It&amp;#x27;s not more consistent. The 2nd bit is just wrong lol. One of the biggest…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2301.13294/"&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>
