8 papers
TeamLLM: Exploring the Capabilities of LLMs for Multimodal Group Interaction Prediction
Diana Romero, Xin Gao, Daniel Khalkhali +1
Predicting group behavior, how individuals coordinate, communicate, and interact during collaborative tasks, is essential for designing systems that can support team performance th…
Follow My Eyes: Backdoor Attacks on Goal-Directed Scanpath Prediction
Diana Romero, Mutahar Ali, Momin Ahmad Khan +3
Scanpath prediction models forecast the sequence of fixations a person makes while searching a scene, and increasingly serve as the upstream perception layer for foveated rendering…
M-CALLM: Multi-level Context Aware LLM Framework for Group Interaction Prediction
Diana Romero, Xin Gao, Daniel Khalkhali +1
This paper explores how large language models can leverage multi-level contextual information to predict group coordination patterns in collaborative mixed reality environments. We…
MURMR: A Multimodal Sensing Framework for Automated Group Behavior Analysis in Mixed Reality
Diana Romero, Yasra Chandio, Fatima Anwar +1
When teams coordinate in immersive environments, collaboration breakdowns can go undetected without automated analysis, directly affecting task performance. Yet existing methods re…
What Sensors See, What People Feel: An Exploratory Study of Subjective Collaboration Perception in Mixed Reality
Yasra Chandio, Diana Romero, Salma Elmalaki +1
Mixed Reality (MR) enables rich, embodied collaboration; however, it is uncertain whether sensor- and system-logged behavioral signals capture how users experience that collaborati…
MoCoMR: A Collaborative MR Simulator with Individual Behavior Modeling
Diana Romero, Fatima Anwar, Salma Elmalaki
Studying collaborative behavior in Mixed Reality (MR) often requires extensive, challenging data collection. This paper introduces MoCoMR, a novel simulator designed to address thi…