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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2407.13998/</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/2407.13998/feed.xml" rel="self" type="application/rss+xml" /><item><title>RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering — mentioned by mskar</title><link>https://news.ycombinator.com/item?id=43268331</link><guid isPermaLink="false">urn:hackerpapers:mention:2407.13998:43268331</guid><pubDate>Wed, 05 Mar 2025 15:59:20 GMT</pubDate><description>&lt;p&gt;We measured PaperQA2 (https://github.com/Future-House/paper-qa) against the science portion of the RAG-Arena benchmark (https://arxiv.org/abs/2407.13998), it&amp;#x27;s the first time we&amp;#x27;ve compared PaperQA2 against other systems based on Cohere or Contextual.ai. PaperQA2 achieves a 12.4% higher score than Contextual.ai on the same dataset (1,404 questions and 1.7M documents). We&amp;#x27;re thrilled about this because it&amp;#x27;s open source, and getting better every day -- check out the code to reproduce this result in our cookbook here: https://futurehouse.gitbook.io/futurehouse-cookbook/paperqa/....&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2407.13998/"&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>
