<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Vision-Language Models | Jay Polra</title><link>https://jaypolra.github.io/tags/vision-language-models/</link><atom:link href="https://jaypolra.github.io/tags/vision-language-models/index.xml" rel="self" type="application/rss+xml"/><description>Vision-Language Models</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>Vision-Language Models</title><link>https://jaypolra.github.io/tags/vision-language-models/</link></image><item><title>VLM-Based Hazard Reasoning</title><link>https://jaypolra.github.io/project/vlm-hazard-reasoning/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://jaypolra.github.io/project/vlm-hazard-reasoning/</guid><description>&lt;p>YOLO can flag a red zone but cannot explain why the scene is dangerous. This project tests whether general-purpose VLMs can fill that explainability gap using structured domain-aware prompting.&lt;/p>
&lt;p>Prompts give models physical context about melt shop environments: what pot haulers are, what molten metal implies, what worker corridors mean for safety. Two-stage reasoning pipeline: first describe the scene neutrally, then evaluate against safety conditions.&lt;/p>
&lt;p>Output covers scene description, detected entities, spatial relationships, hazard assessment, risk level, and recommended action.&lt;/p></description></item></channel></rss>