mEOL creates aligned embeddings for text, images, and SVGs using instruction-guided MLLM one-word summaries and semantic SVG rewriting, outperforming baselines on a new text-to-SVG retrieval benchmark.
Svgenius: Benchmarking llms in svg understanding, editing and generation
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GeoSVG-RL uses RL with six geometric reward dimensions from rendered SVGs to improve structural accuracy over standard language model training for diagram generation.
citing papers explorer
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mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval
mEOL creates aligned embeddings for text, images, and SVGs using instruction-guided MLLM one-word summaries and semantic SVG rewriting, outperforming baselines on a new text-to-SVG retrieval benchmark.
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GeoSVG-RL: Geometry-Aware Reinforcement Learning for Layout-Constrained Text-to-SVG Diagram Generation
GeoSVG-RL uses RL with six geometric reward dimensions from rendered SVGs to improve structural accuracy over standard language model training for diagram generation.