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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Framework for Lightweight Responsible Prompting Recommendation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2504.08757/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2504.08757/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Framework for Lightweight Responsible Prompting Recommendation — HN submission</title><link>https://news.ycombinator.com/item?id=44227347</link><guid isPermaLink="false">urn:hackerpapers:submission:2504.08757:44227347</guid><pubDate>Mon, 09 Jun 2025 18:11:13 GMT</pubDate><description>&lt;p&gt;Responsible Prompting API – open-source project – Feedback appreciated&lt;/p&gt;&lt;p&gt;Hi everyone! I work at IBM Research in the Responsible Tech team. We are working on an open-source project called the Responsible Prompting API. This is the Github - https://github.com/IBM/responsible-prompting-api It is a lightweight system that provides recommendations to tweak the prompt to an LLM so that the output is more responsible (less harmful, more productive, more accurate, etc...) and all of this is done pre-inference. This separates the system from the existing techniques like alignment fine-tuning (training time) and guardrails (post-inference). The team&amp;#x27;s vision is that it will…&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2504.08757/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.IR</category></item></channel></rss>
