Papers with rasterized representations

1 papers
VGBench: A Comprehensive Benchmark of Vector Graphics Understanding and Generation for Large Language Models (2024.emnlp-main)

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Challenge: Current vision models use pixels to rasterize the visual world, but vector graphics are not the best or unique way to represent visual content.
Approach: They propose a benchmark for vector graphics processing with capable Large Language Models . they use a set of questions to evaluate vector graphics formats and a wide range of prompting techniques .
Outcome: The proposed benchmark compares LLMs on rasterized representations with vector graphics . it shows that LLM models show strong capability on both aspects .

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