most cited2nd Workshop on Cognitive Architectures for Social Human-Robot Interaction 2016 (CogArch4sHRI 2016)

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Vision language models have difficulty recognizing virtual objects

Tyler Tran, Sangeet Khemlani, J. G. Trafton

Vision language models (VLMs) are AI systems paired with both language and vision encoders to process multimodal input. They are capable of performing complex semantic tasks such a…

cs.CV2025

Vision language models are unreliable at trivial spatial cognition

Sangeet Khemlani, Tyler Tran, Nathaniel Gyory +6

Vision language models (VLMs) are designed to extract relevant visuospatial information from images. Some research suggests that VLMs can exhibit humanlike scene understanding, whi…

cs.RO2025

The Perceived Danger (PD) Scale: Development and Validation

Jaclyn Molan, Laura Saad, Eileen Roesler +3

There are currently no psychometrically valid tools to measure the perceived danger of robots. To fill this gap, we provided a definition of perceived danger and developed and vali…

cs.RO2025★ 2 cited

Connection-Coordination Rapport (CCR) Scale: A Dual-Factor Scale to Measure Human-Robot Rapport

Ting-Han Lin, Hannah Dinner, Tsz Long Leung +3

Robots, particularly in service and companionship roles, must develop positive relationships with people they interact with regularly to be successful. These positive human-robot r…

cs.RO2016★ 2 cited

2nd Workshop on Cognitive Architectures for Social Human-Robot Interaction 2016 (CogArch4sHRI 2016)

Paul Baxter, J. Gregory Trafton, Severin Lemaignan

This volume is the proceedings of the 2nd workshop on Cognitive Architectures for Social Human-Robot Interaction, held at the ACM/IEEE HRI 2016 conference, which took place on Mond…