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cs.HC2026
AnnoSketch: Evaluating and Collecting Human Sketches for MLLM-assisted Chart Annotation
Yoonjae Oh, Seon Gyeom Kim, Jae Young Choi +4
As multimodal large language models (MLLMs) support a growing range of input modalities, increasing work explores how to incorporate rough sketches to convey user intent. For annot…
cs.HC2026
Surprise2Refine: Axis-Centered Exploration-To-Refinement for Agent-Assisted Creative Scaffolding
Yuzhe You, Gromit Yeuk-Yin Chan, Shunan Guo +4
Designers require different design spaces across creative stages: broad during exploration, and targeted during refinement. Yet existing agent-driven tools assume a fixed or contin…