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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sleep-time Compute: Beyond Inference Scaling at Test-time · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2504.13171/</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/2504.13171/feed.xml" rel="self" type="application/rss+xml" /><item><title>Sleep-time Compute: Beyond Inference Scaling at Test-time — mentioned by swyx</title><link>https://news.ycombinator.com/item?id=48282108</link><guid isPermaLink="false">urn:hackerpapers:mention:2504.13171:48282108</guid><pubDate>Tue, 26 May 2026 16:37:00 GMT</pubDate><description>&lt;p&gt;related preprint from the letta team https://arxiv.org/abs/2504.13171 Scaling test-time compute has emerged as a key ingredient for enabling large language models (LLMs) to solve difficult problems, but comes with high latency and inference cost. We introduce sleep-time compute, which allows models to &amp;quot;think&amp;quot; offline about contexts before queries are presented: by anticipating what queries users might ask and pre-computing useful quantities, we can significantly reduce the compute requirements at test-time. To demonstrate the efficacy of our method, we create modified versions of two…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&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>Sleep-time Compute: Beyond Inference Scaling at Test-time — mentioned by falcor84</title><link>https://news.ycombinator.com/item?id=44510568</link><guid isPermaLink="false">urn:hackerpapers:mention:2504.13171:44510568</guid><pubDate>Wed, 09 Jul 2025 14:37:25 GMT</pubDate><description>&lt;p&gt;An interesting idea, but I&amp;#x27;m surprised that they only mention MemGPT/Letta [0] in passing; from what I&amp;#x27;ve seen of Letta&amp;#x27;s work and e.g. their recent paper on &amp;quot;sleep-time compute&amp;quot;, they are really pushing this space forward. [0] https://www.letta.com/ [1] https://arxiv.org/abs/2504.13171&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&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>Sleep-time Compute: Beyond Inference Scaling at Test-time — mentioned by pacjam</title><link>https://news.ycombinator.com/item?id=43998967</link><guid isPermaLink="false">urn:hackerpapers:mention:2504.13171:43998967</guid><pubDate>Thu, 15 May 2025 20:26:28 GMT</pubDate><description>&lt;p&gt;check out Letta - the OSS codebase (https://github.com/letta-ai/letta) is basically focused on solving the memory/context problem in a generalized way (via &amp;quot;agentic context management&amp;quot;). if you&amp;#x27;re more interested in papers, we also worked on MemGPT and more recently sleep-time compute (https://arxiv.org/abs/2504.13171)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&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>Sleep-time Compute: Beyond Inference Scaling at Test-time — mentioned by x-complexity</title><link>https://news.ycombinator.com/item?id=43911623</link><guid isPermaLink="false">urn:hackerpapers:mention:2504.13171:43911623</guid><pubDate>Wed, 07 May 2025 02:19:10 GMT</pubDate><description>&lt;p&gt;Dummy calculations aren&amp;#x27;t even needed, if you allow the LLMs to pre-compute on the given context before inference: https://arxiv.org/abs/2504.13171 It should be noted that this type of inference is less useful on time-sensitive tasks, but most tasks truthfully don&amp;#x27;t require such time sensitivity (there exists slack time between when the task is given &amp;amp; when questions are asked).&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&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>Sleep-time Compute: Beyond Inference Scaling at Test-time — HN submission</title><link>https://news.ycombinator.com/item?id=43807925</link><guid isPermaLink="false">urn:hackerpapers:submission:2504.13171:43807925</guid><pubDate>Sat, 26 Apr 2025 22:48:12 GMT</pubDate><description>&lt;p&gt;Sleep-Time Compute: Beyond Inference Scaling at Test-Time&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Sleep-time Compute: Beyond Inference Scaling at Test-time — HN submission</title><link>https://news.ycombinator.com/item?id=43788594</link><guid isPermaLink="false">urn:hackerpapers:submission:2504.13171:43788594</guid><pubDate>Thu, 24 Apr 2025 23:20:52 GMT</pubDate><description>&lt;p&gt;Sleep-Time Compute: Beyond Inference Scaling at Test-Time&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Sleep-time Compute: Beyond Inference Scaling at Test-time — HN submission</title><link>https://news.ycombinator.com/item?id=43753878</link><guid isPermaLink="false">urn:hackerpapers:submission:2504.13171:43753878</guid><pubDate>Mon, 21 Apr 2025 16:41:43 GMT</pubDate><description>&lt;p&gt;Sleep-Time Compute: Beyond Inference Scaling at Test-Time&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2504.13171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
