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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2412.05430/</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/2412.05430/feed.xml" rel="self" type="application/rss+xml" /><item><title>DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA — mentioned by antichronology</title><link>https://news.ycombinator.com/item?id=44990390</link><guid isPermaLink="false">urn:hackerpapers:mention:2412.05430:44990390</guid><pubDate>Fri, 22 Aug 2025 22:02:08 GMT</pubDate><description>&lt;p&gt;I watched an interview with one of the co-founders of Anthropic where his point is that although benchmarks saturate they&amp;#x27;re still an important signal for model development. We think the situation is similar here - one the challenges is aligning the benchmark with the function of the models. Genomic benchmarks for gLMs and RNA foundation models have been very resistant to staturation. I think in NLP the problem is that they are victims of their own success where the models can be overfit to particular benchmarks really fast. In genomics we&amp;#x27;re a bit behind. A good paper on this is DartEval…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2412.05430/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
