GENFIG1 is a new benchmark that tests whether vision-language models can create effective Figure 1 visuals capturing the central scientific idea from paper text.
Rodríguez, David Vázquez, Issam H
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S1-Omni-Image unifies scientific image understanding, generation and editing via a think-before-generate paradigm on top of S1-VL-32B, trained on a 314K-sample SciGenEdit dataset, and reports SOTA results on multiple generation and editing benchmarks.
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GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models
GENFIG1 is a new benchmark that tests whether vision-language models can create effective Figure 1 visuals capturing the central scientific idea from paper text.
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S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing
S1-Omni-Image unifies scientific image understanding, generation and editing via a think-before-generate paradigm on top of S1-VL-32B, trained on a 314K-sample SciGenEdit dataset, and reports SOTA results on multiple generation and editing benchmarks.