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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>GReaTer: Gradients over Reasoning Makes Smaller Language Models Strong Prompt Optimizers · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2412.09722/</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/2412.09722/feed.xml" rel="self" type="application/rss+xml" /><item><title>GReaTer: Gradients over Reasoning Makes Smaller Language Models Strong Prompt Optimizers — mentioned by Xmd5a</title><link>https://news.ycombinator.com/item?id=44179464</link><guid isPermaLink="false">urn:hackerpapers:mention:2412.09722:44179464</guid><pubDate>Wed, 04 Jun 2025 11:20:27 GMT</pubDate><description>&lt;p&gt;This is exactly what I&amp;#x27;m doing. Some papers I&amp;#x27;m studying: TextGrad: Automatic &amp;quot;Differentiation&amp;quot; via Text: https://arxiv.org/abs/2406.07496 LLM-AutoDiff: Auto-Differentiate Any LLM Workflow : https://arxiv.org/abs/2501.16673 Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs: https://arxiv.org/abs/2406.16218 GReaTer: Gradients over Reasoning Makes Smaller Language Models Strong Prompt Optimizers: https://arxiv.org/abs/2412.09722 PromptWizard: Task-Aware Prompt Optimization Framework: https://arxiv.org/abs/2405.18369&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2412.09722/"&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>
