<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2403.02419/</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/2403.02419/feed.xml" rel="self" type="application/rss+xml" /><item><title>Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems — mentioned by mateiz</title><link>https://news.ycombinator.com/item?id=39965455</link><guid isPermaLink="false">urn:hackerpapers:mention:2403.02419:39965455</guid><pubDate>Mon, 08 Apr 2024 01:31:54 GMT</pubDate><description>&lt;p&gt;This is a cool paper showing there is value in using an LLM multiple times, but in recent research we showed that with majority voting, quality can decrease past some point as you make more calls. Check out https://arxiv.org/pdf/2403.02419.pdf. It raises the natural question of how to design the best inference algorithm given an LLM you can call multiple times.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2403.02419/"&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>
