<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: giang_at_glai</title><link>https://news.ycombinator.com/user?id=giang_at_glai</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Wed, 05 Aug 2026 13:20:09 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=giang_at_glai" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by giang_at_glai in "Show HN: Steerling-8B, a language model that can explain any token it generates"]]></title><description><![CDATA[
<p>Actually, the model is forcing the response to be generated <i>inside</i> the attribution modules.</p>
]]></description><pubDate>Thu, 26 Feb 2026 21:44:16 +0000</pubDate><link>https://news.ycombinator.com/item?id=47172380</link><dc:creator>giang_at_glai</dc:creator><comments>https://news.ycombinator.com/item?id=47172380</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47172380</guid></item><item><title><![CDATA[New comment by giang_at_glai in "Steering interpretable language models with concept algebra"]]></title><description><![CDATA[
<p>We will share a technical write-up soon that addresses both of your questions: (1) steering vs. prompt engineering, and (2) how effectively our steering suppresses undesired generations.<p>If you have joined our waitlist, we will notify you as soon as it is available.</p>
]]></description><pubDate>Thu, 26 Feb 2026 21:22:26 +0000</pubDate><link>https://news.ycombinator.com/item?id=47172169</link><dc:creator>giang_at_glai</dc:creator><comments>https://news.ycombinator.com/item?id=47172169</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47172169</guid></item><item><title><![CDATA[New comment by giang_at_glai in "Steering interpretable language models with concept algebra"]]></title><description><![CDATA[
<p>Author here.<p>This post shows “concept algebra” on language model: inject, suppress, and compose human-understandable concepts at inference time (no retraining, no prompt engineering).<p>There’s an interactive demo on the post.<p>Would love feedback on: 
(1) what steering tasks you’d benchmark, 
(2) failure cases you’d want to see, 
(3) whether this kind of compositional control is useful in real products.<p>Related: <a href="https://news.ycombinator.com/item?id=47131225">https://news.ycombinator.com/item?id=47131225</a></p>
]]></description><pubDate>Thu, 26 Feb 2026 06:11:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=47162492</link><dc:creator>giang_at_glai</dc:creator><comments>https://news.ycombinator.com/item?id=47162492</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47162492</guid></item></channel></rss>