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This post is a quick guide to setting up LaTeX on your own computer, so you can write papers, resumes, or dazzling “class notes” using LaTeX locally—without relying on Internet connectivity. In other words, you won’t be tied to Overleaf: you can bring your laptop anywhere and keep working on your next big ideas.
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Abstract: Vision-language models like CLIP struggle with multi-object scenes, often favoring prominent objects or those mentioned first in captions. Using real-world COCO images, we show that CLIP’s caption-matching accuracy drops from 91.23% to 87.45% when object order is reversed. To address this, we explore a post-hoc mitigation: a permutation ensemble that averages scores across all object orders, boosting robustness and recovering accuracy to 90.04%. Our findings reveal persistent order biases and offer a simple, effective strategy to improve CLIP’s reliability in complex scenes.
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Ben Maltbie, Junru Ren, Sloane Sambuco