<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Repository-Level Prompt Generation for Large Language Models of Code · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2206.12839/</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/2206.12839/feed.xml" rel="self" type="application/rss+xml" /><item><title>Repository-Level Prompt Generation for Large Language Models of Code — mentioned by wsxiaoys</title><link>https://news.ycombinator.com/item?id=35350466</link><guid isPermaLink="false">urn:hackerpapers:mention:2206.12839:35350466</guid><pubDate>Wed, 29 Mar 2023 00:49:01 GMT</pubDate><description>&lt;p&gt;That‘ll be super interesting! Local context is definitely the key factor for small models achieving better quality than copilot (related: [1], [2]) . One things I’d really wanna have in Sourcegraph: A Search API supports custom retrieval / ranking. Research works (e.g [2]) show simple BoW fetched context is more efficient for code completion tasks. Disclaimer: I’m building https://github.com/TabbyML/tabby an open source alternative of copilot. [1]: https://arxiv.org/abs/2206.12839 [2]: https://arxiv.org/abs/2303.12570&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2206.12839/"&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>
