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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.AI2026
Bridging Natural Language and Interactive What-If Interfaces via LLM-Generated Declarative Specifications
Sneha Gathani, Sirui Zeng, Diya Patel +5
What-if analysis (WIA) lets users explore hypothetical scenarios by adjusting parameters, applying constraints, and scoping data through interactive interfaces. Current tools fall…
cs.HC2026
Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognition
Jae Young Choi, Seon Gyeom Kim, Hyungjun Yoon +7
Large Language Models (LLMs) have emerged as foundation models for IoT applications such as human activity recognition (HAR). However, directly applying high-frequency and multi-di…