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.
Empowering llms to understand and generate complex vector graphics
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A data-driven adaptive policy for KV-cache bit-width selection based on token importance features reduces decoding latency by ~18% and improves accuracy over static quantization while staying near FP16 levels on SmolLM models.
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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Don't Waste Bits! Adaptive KV-Cache Quantization for Lightweight On-Device LLMs
A data-driven adaptive policy for KV-cache bit-width selection based on token importance features reduces decoding latency by ~18% and improves accuracy over static quantization while staying near FP16 levels on SmolLM models.