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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Training Language Models on Synthetic Edit Sequences Improves Code Synthesis · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2410.02749/</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/2410.02749/feed.xml" rel="self" type="application/rss+xml" /><item><title>Training Language Models on Synthetic Edit Sequences Improves Code Synthesis — mentioned by twotwotwo</title><link>https://news.ycombinator.com/item?id=43853002</link><guid isPermaLink="false">urn:hackerpapers:mention:2410.02749:43853002</guid><pubDate>Thu, 01 May 2025 02:05:55 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s kind of weird to think that in a coding assistant, an LLM is regularly asked to produce a valid block of code top to bottom, or repeat a section of code with changes, when that&amp;#x27;s not what we do. (There are other intuitively odd things about this, like the amount of compute spent generating &amp;#x27;easy&amp;#x27; tokens, e.g. repeating unchanged code.) Some of that might be that models are just weird and intuition doesn&amp;#x27;t apply. But maybe the way we do it--jumping around, correcting as we go, etc.--is legitimately an efficient use of effort, and a model could do its job better, with less effort, or both…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2410.02749/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
