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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Selection for Language Models via Importance Resampling · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2302.03169/</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/2302.03169/feed.xml" rel="self" type="application/rss+xml" /><item><title>Data Selection for Language Models via Importance Resampling — mentioned by zhangce</title><link>https://news.ycombinator.com/item?id=38080701</link><guid isPermaLink="false">urn:hackerpapers:mention:2302.03169:38080701</guid><pubDate>Tue, 31 Oct 2023 05:33:36 GMT</pubDate><description>&lt;p&gt;There are actually a few ways to do this; and we have four: - `rps_doc_ml_wikiref_score`: a classifier that classifiers random webpage with Wiki references (used in Llama-1) - `ccnet_perplexity`: perplexity of an LM trained on Wikipedia (used in CCNet) - `rps_doc_ml_wikipedia_score`: classifier prediction for the document being a Wikipedia article - `rps_doc_wikipedia_importance`: Used in https://arxiv.org/abs/2302.03169 You can see the full table here: https://together.ai/blog/redpajama-data-v2&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2302.03169/"&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>
