DiagramRAG is a retrieval-augmented framework that represents diagrams as knowledge graphs, synthesizes sketch variants, trains an embedding model for structure-aware retrieval, and uses retrieved references to guide sketch-based scientific diagram generation.
Computer Vision -- ECCV 2016 , pages =
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F^3A is a training-free visual token pruning router that treats pruning as task-conditioned evidence search and allocates a fixed vision token budget using question cues and frozen sparse heads without extra LLM passes.
citing papers explorer
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DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation
DiagramRAG is a retrieval-augmented framework that represents diagrams as knowledge graphs, synthesizes sketch variants, trains an embedding model for structure-aware retrieval, and uses retrieved references to guide sketch-based scientific diagram generation.
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How Many Visual Tokens Do Multimodal Language Models Need? Scaling Visual Token Pruning with F^3A
F^3A is a training-free visual token pruning router that treats pruning as task-conditioned evidence search and allocates a fixed vision token budget using question cues and frozen sparse heads without extra LLM passes.