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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ExpertPrompting: Instructing Large Language Models to be Distinguished Experts · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2305.14688/</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/2305.14688/feed.xml" rel="self" type="application/rss+xml" /><item><title>ExpertPrompting: Instructing Large Language Models to be Distinguished Experts — mentioned by AdieuToLogic</title><link>https://news.ycombinator.com/item?id=49593393</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.14688:49593393</guid><pubDate>Mon, 07 Sep 2026 03:03:14 GMT</pubDate><description>&lt;p&gt;&amp;gt; has anyone found a good way to improve code quality? just wondering ... - keep prompts focused on atomic tasks. - use expert prompting[0] when possible. - require coding agents to verify changes. - require coding agents to create/update unit tests with 100% coverage. - use git to commit/revert atomic tasks manually. - leverage planning capabilities to review instead of recover. - consider using something like Karpathy guidelines[1]. - leverage Constraint Programming[2] concepts when formulating prompts. 0 - https://arxiv.org/pdf/2305.14688 1…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.14688/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>ExpertPrompting: Instructing Large Language Models to be Distinguished Experts — mentioned by not_a_bot_4sho</title><link>https://news.ycombinator.com/item?id=48511524</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.14688:48511524</guid><pubDate>Sat, 13 Jun 2026 01:38:55 GMT</pubDate><description>&lt;p&gt;Back with some papers. (Apologies in advance; I typically don&amp;#x27;t edit/format comments much here, please bear with me.) Notable papers describing performance improvements with prescribed roles and personas: - ExpertPrompting: Instructing Large Language Models to be Distinguished Experts (2023) https://arxiv.org/abs/2305.14688 (if you&amp;#x27;re going to only read one paper here, maybe read this one but know there has been a lot of follow up with more modern models.) - Expert Personas Improve LLM Alignment but Damage Accuracy (2026) https://arxiv.org/abs/2603.18507 - When Does Persona Prompting Actually…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.14688/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>ExpertPrompting: Instructing Large Language Models to be Distinguished Experts — mentioned by jason_oster</title><link>https://news.ycombinator.com/item?id=46612503</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.14688:46612503</guid><pubDate>Wed, 14 Jan 2026 04:56:57 GMT</pubDate><description>&lt;p&gt;True, but nuanced. The model does not react to &amp;quot;you are an experienced programmer&amp;quot; kinds of prompts. It reacts to being given relevant information that needs to be reflected in the output. See examples in https://arxiv.org/abs/2305.14688; They certainly do say things like &amp;quot;You are a physicist specialized in atomic structure ...&amp;quot;, but the important point is that the rest of the &amp;quot;expert persona&amp;quot; prompt _calls attention to key details_ that improves the response. The hint about electromagnetic forces in the expert persona prompt is what tipped off the model to mention it in the output. Bringing…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.14688/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>ExpertPrompting: Instructing Large Language Models to be Distinguished Experts — mentioned by electroglyph</title><link>https://news.ycombinator.com/item?id=46548202</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.14688:46548202</guid><pubDate>Thu, 08 Jan 2026 23:51:22 GMT</pubDate><description>&lt;p&gt;there&amp;#x27;s actually quite a bit of research in this field, here&amp;#x27;s a couple: &amp;quot;ExpertPrompting: Instructing Large Language Models to be Distinguished Experts&amp;quot; https://arxiv.org/abs/2305.14688 &amp;quot;Persona is a Double-edged Sword: Mitigating the Negative Impact of Role-playing Prompts in Zero-shot Reasoning Tasks&amp;quot; https://arxiv.org/abs/2408.08631&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.14688/"&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>
