<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multimodal Models | Vedaant Jain</title><link>https://vedaantjain.netlify.app/tags/multimodal-models/</link><atom:link href="https://vedaantjain.netlify.app/tags/multimodal-models/index.xml" rel="self" type="application/rss+xml"/><description>Multimodal Models</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 12 Jun 2024 00:00:00 +0000</lastBuildDate><image><url>https://vedaantjain.netlify.app/media/icon_hu68170e94a17a2a43d6dcb45cf0e8e589_3079_512x512_fill_lanczos_center_3.png</url><title>Multimodal Models</title><link>https://vedaantjain.netlify.app/tags/multimodal-models/</link></image><item><title>HumorDB</title><link>https://vedaantjain.netlify.app/project/humordb/</link><pubDate>Wed, 12 Jun 2024 00:00:00 +0000</pubDate><guid>https://vedaantjain.netlify.app/project/humordb/</guid><description>&lt;p>HumorDB is a novel image-only dataset designed to advance visual humor understanding in AI systems. It consists of carefully curated image pairs with contrasting humor ratings, emphasizing subtle visual cues that trigger humor while mitigating potential biases. The dataset enables evaluation through binary classification, range regression, and pairwise comparison tasks.&lt;/p>
&lt;p>Authors: Vedaant Jain, Felipe Feitosa, Gabriel Kreiman&lt;/p></description></item></channel></rss>