https://hackerpaper.kaipfister.de/p/2410.18982/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=42769087urn:hackerpapers:mention:2410.18982:42769087Mon, 20 Jan 2025 14:31:17 GMT<p>There are all sorts of ways that additional test time compute can be used to get better results, varying from things like sampling multiple CoT and choosing the best, to explicit tree search (e.g. rStar-Math), to things like &quot;journey learning&quot; as described here: https://arxiv.org/abs/2410.18982?utm_source=substack&amp;utm_med... Journey learning is doing something that is effectively close to depth-first tree search (see fig.4. on p.5), and does seem close to what OpenAI are claiming to be doing, as well as what DeepSeek-R1 is doing here... No special tree-search sampling infrastructure, but…</p><p><a href="https://hackerpaper.kaipfister.de/p/2410.18982/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.AIhttps://news.ycombinator.com/item?id=41973406urn:hackerpapers:submission:2410.18982:41973406Mon, 28 Oct 2024 17:00:11 GMT<p>O1 Replication Journey</p><p></p><p>1 point; 0 discussion replies on HN. <a href="https://hackerpaper.kaipfister.de/p/2410.18982/">Paper and source history</a>. A submission is not an endorsement.</p>cs.AI