Stroke of Surprise is a framework that generates vector sketches undergoing semantic transformation from one concept to another by adding strokes, using dual-branch SDS and overlay loss for optimization.
Neuralsvg: An implicit repre- sentation for text-to-vector generation
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MultiMat shows multimodal large models plus constrained search produce higher-quality procedural material graphs than text-only baselines on a new production dataset.
Reason-SVG adds a Drawing-with-Thought reasoning stage and GRPO-based reinforcement learning with a hybrid reward to improve LLM and VLM performance on accurate SVG generation.
A structured survey of multimodal code intelligence that formulates the field by code roles and organizes work into four domains while proposing verification-centered research directions.
citing papers explorer
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Stroke of Surprise: Progressive Semantic Illusions in Vector Sketching
Stroke of Surprise is a framework that generates vector sketches undergoing semantic transformation from one concept to another by adding strokes, using dual-branch SDS and overlay loss for optimization.
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MultiMat: Multimodal Program Synthesis for Procedural Materials using Large Multimodal Models
MultiMat shows multimodal large models plus constrained search produce higher-quality procedural material graphs than text-only baselines on a new production dataset.
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Reason-SVG: Enhancing Structured Reasoning for Vector Graphics Generation with Reinforcement Learning
Reason-SVG adds a Drawing-with-Thought reasoning stage and GRPO-based reinforcement learning with a hybrid reward to improve LLM and VLM performance on accurate SVG generation.
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Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence
A structured survey of multimodal code intelligence that formulates the field by code roles and organizes work into four domains while proposing verification-centered research directions.