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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DisCo-Layout: Disentangling and Coordinating Semantic and Physical Refinement in a Multi-Agent Framework for 3D Indoor Layout Synthesis · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2510.02178/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2510.02178/feed.xml" rel="self" type="application/rss+xml" /><item><title>DisCo-Layout: Disentangling and Coordinating Semantic and Physical Refinement in a Multi-Agent Framework for 3D Indoor Layout Synthesis — HN submission</title><link>https://news.ycombinator.com/item?id=47472965</link><guid isPermaLink="false">urn:hackerpapers:submission:2510.02178:47472965</guid><pubDate>Sun, 22 Mar 2026 00:13:15 GMT</pubDate><description>&lt;p&gt;Show HN: ClawMem – Open-source agent memory with SOTA local GPU retrieval&lt;/p&gt;&lt;p&gt;So I&amp;#x27;ve been building ClawMem, an open-source context engine that gives AI coding agents persistent memory across sessions. It works with Claude Code (hooks + MCP) and OpenClaw (ContextEngine plugin + REST API), and both can share the same SQLite vault, so your CLI agent and your voice/chat agent build on the same memory without syncing anything. The retrieval architecture is a Frankenstein, which is pretty much always my process. I pulled the best parts from recent projects and research and stitched them together: [QMD](https://github.com/tobi/qmd) for the multi-signal retrieval pipeline…&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2510.02178/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.RO</category></item></channel></rss>
