3 papers
cs.RO2026
Material Driven HRI Design: Aesthetics as Explainability
Natalie Friedman, Kevin Weatherwax, Chengchao Zhu
Aesthetics - often treated as secondary to function-guides how people interpret robots' roles. A great deal of robot designs - both real and fictitious - use sleek industrial aesth…
cs.AI2026
Not Too Short, Not Too Long: How LLM Response Length Shapes People's Critical Thinking in Error Detection
Natalie Friedman, Adelaide Nyanyo, Kevin Weatherwax +4
Large language models (LLMs) have become common decision-support tools across educational and professional contexts, raising questions about how their outputs shape human critical…
cs.HC2025
Evaluating Node-tree Interfaces for AI Explainability
Lifei Wang, Natalie Friedman, Chengchao Zhu +2
As large language models (LLMs) become ubiquitous in workplace tools and decision-making processes, ensuring explainability and fostering user trust are critical. Although advancem…