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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2602.02459/</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/2602.02459/feed.xml" rel="self" type="application/rss+xml" /><item><title>TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments — mentioned by movedx01</title><link>https://news.ycombinator.com/item?id=49764859</link><guid isPermaLink="false">urn:hackerpapers:mention:2602.02459:49764859</guid><pubDate>Sat, 19 Sep 2026 09:31:20 GMT</pubDate><description>&lt;p&gt;Kind of reminds me of this more recent paper: https://arxiv.org/html/2602.02459v1 Different use case and implementation, but a similar idea. In this case applied to sharing last state(not the whole KV cache) from big brain model running in the cloud with a smaller/dumber model running on-device in a robot, in a latancy-aware way.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2602.02459/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.RO</category></item></channel></rss>
