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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2406.17557/</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/2406.17557/feed.xml" rel="self" type="application/rss+xml" /><item><title>The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale — mentioned by m_ke</title><link>https://news.ycombinator.com/item?id=42425059</link><guid isPermaLink="false">urn:hackerpapers:mention:2406.17557:42425059</guid><pubDate>Sun, 15 Dec 2024 18:34:53 GMT</pubDate><description>&lt;p&gt;There&amp;#x27;s a ton of recent work on data curation / synthetic data generation that shows that smaller high quality datasets go a lot further than scaling up on noisy web data. The scaling law plots are log scale so to get more juice with naive scaling we&amp;#x27;d need to invest exponentially more resources, and we&amp;#x27;re at a point where the juice is not worth the squeeze, so people will shift to moving the curve down with new architectures, better curated datasets and test time compute / RL. See: - FineWeb: https://arxiv.org/abs/2406.17557 - Phi-4: https://arxiv.org/abs/2412.08905 - DataComp…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2406.17557/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
