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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>syftr: Pareto-Optimal Generative AI · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2505.20266/</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/2505.20266/feed.xml" rel="self" type="application/rss+xml" /><item><title>syftr: Pareto-Optimal Generative AI — mentioned by djoldman</title><link>https://news.ycombinator.com/item?id=44146137</link><guid isPermaLink="false">urn:hackerpapers:mention:2505.20266:44146137</guid><pubDate>Sat, 31 May 2025 18:34:55 GMT</pubDate><description>&lt;p&gt;Given section A7 in your paper: https://arxiv.org/pdf/2505.20266 ...would it be accurate to say that syftr finds Pareto-optimal choices across cost, accuracy, and latency, where accuracy is decided by an LLM whose assessments are 90% correlated to that of human labelers? Are there 3 objectives: cost, accuracy, and latency or 2: cost and accuracy?&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2505.20266/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>syftr: Pareto-Optimal Generative AI — mentioned by roma_glushko</title><link>https://news.ycombinator.com/item?id=44116269</link><guid isPermaLink="false">urn:hackerpapers:mention:2505.20266:44116269</guid><pubDate>Wed, 28 May 2025 14:15:08 GMT</pubDate><description>&lt;p&gt;Useful links: Github: https://github.com/datarobot/syftr Paper: https://arxiv.org/abs/2505.20266&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2505.20266/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
