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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2411.18564/</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/2411.18564/feed.xml" rel="self" type="application/rss+xml" /><item><title>Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs — mentioned by alfonsodev</title><link>https://news.ycombinator.com/item?id=45925853</link><guid isPermaLink="false">urn:hackerpapers:mention:2411.18564:45925853</guid><pubDate>Fri, 14 Nov 2025 11:34:33 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;ve been thinking a lot about this, and I want to build the following experiment, in case anyone is interested: The experiment is about putting an LLM to play plman[0] with and without prolog help. plman is a pacman like game for learning prolog, it was written by profesor Francisco J. Gallego from Alicante University to teach logic subject in computer science. Basically you write solution in prolog for a map, and plman executes it step by step so you can see visually the pacman (plman) moving around the maze eating and avoiding ghost and other traps. There is an interesting dynamic about…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2411.18564/"&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>
