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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Steering Llama 2 via Contrastive Activation Addition · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2312.06681/</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/2312.06681/feed.xml" rel="self" type="application/rss+xml" /><item><title>Steering Llama 2 via Contrastive Activation Addition — mentioned by ruby314</title><link>https://news.ycombinator.com/item?id=41295833</link><guid isPermaLink="false">urn:hackerpapers:mention:2312.06681:41295833</guid><pubDate>Tue, 20 Aug 2024 00:58:16 GMT</pubDate><description>&lt;p&gt;Ty! - We generate contrast pairs (for this post, using gpt-4o) and do some post processing for quality (synthetic data). The impact of different types of contrast pairs is a continuing area of research for us. - We treat the evaluator model layers as hyper parameters, similar to the steering research (some of which we cite in our “non-comprehensive list of references”). We also see that the middle layers tend to be most effective. - For base model, we use both Llama-3-8b-Instruct and Llama-3.1-8b-Instruct to show LSR taking advantage of the improved base model (maybe I misunderstood the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2312.06681/"&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>
