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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agent-as-a-Judge: Evaluate Agents with Agents · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2410.10934/</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/2410.10934/feed.xml" rel="self" type="application/rss+xml" /><item><title>Agent-as-a-Judge: Evaluate Agents with Agents — mentioned by nextos</title><link>https://news.ycombinator.com/item?id=45476005</link><guid isPermaLink="false">urn:hackerpapers:mention:2410.10934:45476005</guid><pubDate>Sat, 04 Oct 2025 19:35:29 GMT</pubDate><description>&lt;p&gt;This is a very interesting area of research. I did something similar a couple of years ago using logic and probabilistic logic inference engines to make sure conclusions followed from premises. I also used agents to synthesize, formalize, and criticize domain knowledge. Obviously, it is not a silver bullet, but it does ensure some degree of correctness. I think introducing some degree of symbolism and agents-as-a-judge is a promising way ahead, see e.g.: https://arxiv.org/abs/2410.10934&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2410.10934/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Agent-as-a-Judge: Evaluate Agents with Agents — HN submission</title><link>https://news.ycombinator.com/item?id=42195858</link><guid isPermaLink="false">urn:hackerpapers:submission:2410.10934:42195858</guid><pubDate>Wed, 20 Nov 2024 16:57:00 GMT</pubDate><description>&lt;p&gt;Show HN: Agentic Evaluators for Agentic Workflows (Starting with RAG)&lt;/p&gt;&lt;p&gt;Hey all! Thought this group might find this interesting - new approach to evaluating RAG pipelines using &amp;#x27;agents as a judge&amp;#x27;. We got excited by the findings in this paper (https://arxiv.org/abs/2410.10934), about agents producing evaluations closer to human-evaluators, especially for multi-step workflows. Our first use case was RAG pipelines, specifically evaluating if your agent MISSED pulling any important chunks from the source document. While many RAG evaluators determine if your model USED its chunk in the output, there&amp;#x27;s no visibility on if your model grabbed all the right chunks in the…&lt;/p&gt;&lt;p&gt;4 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2410.10934/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
