<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Grad-CAM | Jay Polra</title><link>https://jaypolra.github.io/tags/grad-cam/</link><atom:link href="https://jaypolra.github.io/tags/grad-cam/index.xml" rel="self" type="application/rss+xml"/><description>Grad-CAM</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://jaypolra.github.io/media/icon_hu_3943bc2ea2cd9fa1.png</url><title>Grad-CAM</title><link>https://jaypolra.github.io/tags/grad-cam/</link></image><item><title>VLM Explainer: From Patches to Phrases</title><link>https://jaypolra.github.io/project/vlm-explainer/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://jaypolra.github.io/project/vlm-explainer/</guid><description>&lt;p>BLIP generates fluent captions but gives no account of why. The question this project answers: do the image regions the model highlights actually cause the caption, or do they just correlate with it?&lt;/p>
&lt;p>Built Grad-CAM token attribution to identify which image regions influenced specific caption words. Validated through perturbation testing: masking the dog region changed &amp;ldquo;a family walking with their dog&amp;rdquo; to &amp;ldquo;a family walking on the beach.&amp;rdquo; Causal influence, not correlation, is the standard.&lt;/p>
&lt;p>Added CLIP alignment scoring to cross-verify image-text grounding. Interactive Streamlit interface with 2-click region masking and layer-evolution visualization across shallow-to-deep BLIP representations.&lt;/p></description></item></channel></rss>