Publications

@article{west_improving_2025,

title = {Improving social connection with weak ties and strangers: effects of a new micro-intervention on interaction quality and social behavior},

author = {Taylor N. West and Michael M. Prinzing and Catherine Garton and Catherine J. Berman and Jieni Zhou and James Hale and Jonathan Gratch and Barbara L. Fredrickson},

url = {https://www.tandfonline.com/doi/full/10.1080/17439760.2024.2394451},

doi = {10.1080/17439760.2024.2394451},

issn = {1743-9760, 1743-9779},

year  = {2025},

date = {2025-07-01},

urldate = {2025-06-25},

journal = {The Journal of Positive Psychology},

volume = {20},

number = {4},

pages = {652–662},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_exploring_2025,

title = {Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices},

author = {Nikolos Gurney and John H. Miller and David V. Pynadath},

url = {https://linkinghub.elsevier.com/retrieve/pii/S1755534525000120},

doi = {10.1016/j.jocm.2025.100549},

issn = {17555345},

year  = {2025},

date = {2025-06-01},

urldate = {2025-04-15},

journal = {Journal of Choice Modelling},

volume = {55},

pages = {100549},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{klumpe_social_2025,

title = {Social bonding between humans, animals, and robots: Dogs outperform AIBOs, their robotic replicas, as social companions},

author = {Stella Klumpe and Kelsey C. Mitchell and Emma Cox and Jeffrey S. Katz and Lucia Lazarowski and Gopikrishna Deshpande and Jonathan Gratch and Ewart J. De Visser and Hasan Ayaz and Xingnan Li and Adrian A. Franke and Frank Krueger},

editor = {Casey R. Lynch},

url = {https://dx.plos.org/10.1371/journal.pone.0324312},

doi = {10.1371/journal.pone.0324312},

issn = {1932-6203},

year  = {2025},

date = {2025-06-01},

urldate = {2025-06-12},

journal = {PLoS One},

volume = {20},

number = {6},

pages = {e0324312},

abstract = {In the evolving landscape of technology, robots have emerged as social companions, prompting an investigation into social bonding between humans and robots. While human-animal interactions are well-studied, human-robot interactions (HRI) remain comparatively underexplored. Ethorobotics, a field of social robotic engineering based on ecology and ethology, suggests designing companion robots modeled on animal companions, which are simpler to emulate than humans. However, it is unclear whether these robots can match the social companionship provided by their original models. This study examined social bonding between humans and AIBOs, dog-inspired companion robots, compared to real dogs. Nineteen female participants engaged in 12 affiliative interactions with dogs and AIBOs across two counter-balanced, one-month bonding phases. Social bonding was assessed through urinary oxytocin (OXT) level change over an interaction, self-reported attachment using an adapted version of the Lexington Attachment to Pets Scale, and social companionship evaluations administering the Robot-Dog Questionnaire. To examine OXT level changes and self-reported attachment by comparing the two social companions, we conducted mixed-effects model analyses and planned follow-up comparisons. Frequency comparison, binary logistic regression, and thematic analysis were performed to analyze social companionship evaluations. Results revealed significant differences between dogs and AIBOs in fostering social bonds. OXT level change increased during interactions with dogs but decreased with AIBOs. Participants reported stronger attachment to dogs and rated them as better social companions. These findings highlight the current limitations of AIBOs in fostering social bonding immediately compared to dogs. Our study contributes to the growing HRI research by demonstrating an existing gap between AIBOs and dogs as social companions. It highlights the need for further investigation to understand the complexities of social bonding with companion robots, which is essential to implement successful applications for social robots in diverse domains such as the elderly and health care, education, and entertainment.},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{hale_provably_2025,

title = {“Provably fair” algorithms may perpetuate racial and gender bias: a study of salary dispute resolution},

author = {James Hale and Peter H. Kim and Jonathan Gratch},

url = {https://link.springer.com/10.1007/s10458-025-09703-x},

doi = {10.1007/s10458-025-09703-x},

issn = {1387-2532, 1573-7454},

year  = {2025},

date = {2025-06-01},

urldate = {2025-03-18},

journal = {Auton Agent Multi-Agent Syst},

volume = {39},

number = {1},

pages = {20},

abstract = {Abstract 

 Prior work suggests automated dispute resolution tools using “provably fair” algorithms can address disparities between demographic groups. These methods use multi-criteria elicited preferences from all disputants and satisfy constraints to generate “fair” solutions. However, we analyze the potential for inequity to permeate proposals through the preference elicitation stage. This possibility arises if differences in dispositional attitudes differ between demographics, and those dispositions affect elicited preferences. Specifically, risk aversion plays a prominent role in predicting preferences. Risk aversion predicts a weaker relative preference for 

 salary 

 and a softer within-issue utility for each issue; this leads to worse compensation packages for risk-averse groups. These results raise important questions in AI-value alignment about whether an AI mediator should take explicit preferences at face value.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{brixey-traum-2025-code,

title = {Does a code-switching dialogue system help users learn conversational fluency in Choctaw?},

author = {David Traum and Jacqueline Brixey},

url = {https://aclanthology.org/2025.americasnlp-1.2/},

doi = {10.18653/v1/2025.americasnlp-1.2},

isbn = {979-8-89176-236-7},

year  = {2025},

date = {2025-05-05},

urldate = {2025-05-05},

journal = {Proceedings of the Fifth Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)},

pages = {8-17},

publisher = {Association for Computational Linguistics},

address = {Albuquerque, New Mexico},

abstract = {We investigate the learning outcomes and user response to a chatbot for practicing conversational Choctaw, an endangered American Indigenous language. Conversational fluency is a goal for many language learners, however, for learners of endangered languages in North America, access to fluent speakers may be limited. Chatbots are potentially ideal dialogue partners as this kind of dialogue system fulfills a non-authoritative role by focusing on carrying on a conversation as an equal conversational partner. The goal of the chatbot investigated in this work is to serve as a conversational partner in the absence of a fluent Choctaw-speaking human interlocutor. We investigate the impact of code-switching in the interaction, comparing a bilingual chatbot against a monolingual Choctaw version. We evaluate the systems for user engagement and enjoyment, as well as gains in conversational fluency from interacting with the system.},

keywords = {Learning Sciences, LLM},

pubstate = {published},

tppubtype = {article}

}

@article{okado_how_2025,

title = {How Can Virtual Agents Scale Up Mentoring?: Insights from College Students’ Experiences Using the CareerFair.ai Platform at an American Hispanic-Serving Institution},

author = {Yuko Okado and Benjamin D. Nye and Angelica Aguirre and William Swartout},

url = {https://link.springer.com/10.1007/s40593-025-00482-w},

doi = {10.1007/s40593-025-00482-w},

issn = {1560-4292, 1560-4306},

year  = {2025},

date = {2025-05-01},

urldate = {2025-06-24},

journal = {Int J Artif Intell Educ},

keywords = {DTIC, Learning Sciences},

pubstate = {published},

tppubtype = {article}

}

@article{core_usability_2025,

title = {Usability and Preferences for a Personalized Adaptive Learning System for AI Upskilling},

author = {Mark Core and Benjamin Nye and Kayla Carr and Shirley Li and Aaron Shiel and Daniel Auerbach and Andrew Leeds and William Swartout},

url = {https://journals.flvc.org/FLAIRS/article/view/138996},

doi = {10.32473/flairs.38.1.138996},

issn = {2334-0762, 2334-0754},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-20},

journal = {FLAIRS},

volume = {38},

abstract = {As AI tools become common across jobs and industries, it is critical to broaden education about AI beyond teaching computer scientists how to build AI systems. To expand AI education, we are researching AI for AI learning: a personalized and adaptive learning system that integrates dialog-based tutoring and gamified programming activities. To study this problem, we adapted and expanded an existing smartphone adaptive coach to develop the Game-if-AI system. Using a design-based research approach, Game-if-AI was iteratively tested and improved across four semesters of optional use in a course designed for technician-level understanding of AI: mastering programming skills to apply AI libraries and established models. In this study, we measured the interests and needs of these technical learners, based on both survey data and on how they engaged with topics in the system. Based on this data, new topics were added and the system was refined. In this paper, we report students' usability ratings for system components and student preferences based on completion rates of AI topics available each semester. Students rated the adaptive system positively overall (93% rated as a "good idea"), but more complex learning activities (tutoring dialogs, programming) were rated lower than traditional ones (e.g., multiple choice, reading). Students were most likely to master topics highly aligned to the course materials, as well as self-directed learning toward easier high-interest topics (e.g., LLM Prompting).},

keywords = {AI, DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{awada_impact_2025,

title = {The Impact of Color Correlated Temperature and Illuminance Levels of Office Lighting on Stress and Cognitive Restoration},

author = {Mohamad Awada and Burcin Becerik Gerber and Gale M. Lucas and Shawn C. Roll},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0272494425001112},

doi = {10.1016/j.jenvp.2025.102628},

issn = {02724944},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-20},

journal = {Journal of Environmental Psychology},

pages = {102628},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{liu_egocentric_2025,

title = {Egocentric camera-based method for detecting static hazardous objects on construction sites},

author = {Ziming Liu and Jiuyi Xu and Christine Wun Ki Suen and Meida Chen and Zhengbo Zou and Yangming Shi},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0926580525000883},

doi = {10.1016/j.autcon.2025.106048},

issn = {09265805},

year  = {2025},

date = {2025-04-01},

urldate = {2025-03-18},

journal = {Automation in Construction},

volume = {172},

pages = {106048},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_willingness_2025,

title = {Willingness to work as a predictor of human-agent team success},

author = {Nikolos Gurney and David V. Pynadath and John H. Miller},

url = {https://www.frontiersin.org/articles/10.3389/fcomp.2025.1405436/full},

doi = {10.3389/fcomp.2025.1405436},

issn = {2624-9898},

year  = {2025},

date = {2025-03-01},

urldate = {2025-04-15},

journal = {Front. Comput. Sci.},

volume = {7},

pages = {1405436},

abstract = {Research shows that the effectiveness of human-agent teams depends heavily on human team members' prior experiences, whether from direct teaming activities or relevant domain knowledge. While researchers have proposed various mechanisms to explain this relationship, we present a simpler alternative explanation: experience serves primarily as an indicator of a person's fundamental willingness to engage in teaming tasks. We introduce a measure called “willingness to work” that quantifies this underlying disposition. Our empirical analysis demonstrates that this straightforward metric robustly predicts human-agent team performance. Beyond its practical value as a predictive tool, this reconceptualization of the experience-performance relationship necessitates a fresh examination of existing findings in the field. The results suggest that a team member's basic willingness to invest effort may be more fundamental to success than previously recognized mechanisms.},

keywords = {DTIC, Virtual Agents},

pubstate = {published},

tppubtype = {article}

}

@article{liu_elicitation_2025,

title = {Elicitation and verification of learning via experts (EVOLVE) for creating a theoretical framework for active shooter incidents},

author = {Ruying Liu and Burcin Becerik-Gerber and David V. Pynadath and Deniz Marti and Gale M. Lucas},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2666165925000353},

doi = {10.1016/j.dibe.2025.100635},

issn = {26661659},

year  = {2025},

date = {2025-03-01},

urldate = {2025-03-18},

journal = {Developments in the Built Environment},

volume = {21},

pages = {100635},

keywords = {DTIC, Social Simulation},

pubstate = {published},

tppubtype = {article}

}

@article{correia_da_fonseca_evolution_2025,

title = {Evolution of indirect reciprocity under emotion expression},

author = {Henrique Correia Da Fonseca and Celso M. De Melo and Kazunori Terada and Jonathan Gratch and Ana S. Paiva and Francisco C. Santos},

url = {https://www.nature.com/articles/s41598-025-89588-8},

doi = {10.1038/s41598-025-89588-8},

issn = {2045-2322},

year  = {2025},

date = {2025-03-01},

urldate = {2025-03-20},

journal = {Sci Rep},

volume = {15},

number = {1},

pages = {9151},

abstract = {Abstract 

 Do emotion expressions impact the evolution of cooperation? Indirect Reciprocity offers a solution to the cooperation dilemma with prior work focusing on the role of social norms in propagating others’ reputations and contributing to evolutionarily stable cooperation. Recent experimental studies, however, show that emotion expressions shape pro-social behaviour, communicate one’s intentions to others, and serve an error-correcting function; yet, the role of emotion signals in the evolution of cooperation remains unexplored. We present the first model of IR based on evolutionary game theory that exposes how emotion expressions positively influence the evolution of cooperation, particularly in scenarios of frequent errors. Our findings provide evolutionary support for the existence of emotion-based social norms, which help foster cooperation among unrelated individuals.},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{roth_overview_2025,

title = {Overview of real-world applications of federated learning with NVIDIA FLARE},

author = {Holger R. Roth and Ziyue Xu and Chester Chen and Daguang Xu and Prerna Dogra and Mona Flores and Yan Cheng and Andrew Feng},

url = {https://www.tandfonline.com/doi/full/10.1080/10543406.2025.2456174},

doi = {10.1080/10543406.2025.2456174},

issn = {1054-3406, 1520-5711},

year  = {2025},

date = {2025-02-01},

urldate = {2025-03-20},

journal = {Journal of Biopharmaceutical Statistics},

pages = {1–11},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{liu_impact_2025,

title = {Impact of behavior-based virtual training on active shooter incident preparedness in healthcare facilities},

author = {Ruying Liu and Burcin Becerik-Gerber and Gale M. Lucas and Kelly Busta},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2212420925000494},

doi = {10.1016/j.ijdrr.2025.105225},

issn = {22124209},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-20},

journal = {International Journal of Disaster Risk Reduction},

volume = {118},

pages = {105225},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{kang_how_2025,

title = {How Collaboration Context and Personality Traits Shape the Social Norms of Human-to-Avatar Identity Representation},

author = {Seoyoung Kang and Boram Yoon and Kangsoo Kim and Jonathan Gratch and Woontack Woo},

url = {https://ieeexplore.ieee.org/document/10935702/},

doi = {10.1109/TVCG.2025.3549904},

issn = {1077-2626, 1941-0506, 2160-9306},

year  = {2025},

date = {2025-01-01},

urldate = {2025-04-17},

journal = {IEEE Trans. Visual. Comput. Graphics},

pages = {1–10},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tran_setpeer_2025,

title = {SetPeER: Set-Based Personalized Emotion Recognition With Weak Supervision},

author = {Minh Tran and Yufeng Yin and Mohammad Soleymani},

url = {https://ieeexplore.ieee.org/document/10993348/},

doi = {10.1109/TAFFC.2025.3568024},

issn = {1949-3045, 2371-9850},

year  = {2025},

date = {2025-01-01},

urldate = {2025-05-20},

journal = {IEEE Trans. Affective Comput.},

pages = {1–15},

keywords = {DTIC, Emotion},

pubstate = {published},

tppubtype = {article}

}

@article{rodrigues_impact_2025,

title = {Impact of selective environmental sound attenuation on operator performance, stress, attention, and task engagement in teleoperated demolition},

author = {Patrick Borges Rodrigues and Burcin Becerik-Gerber and Lucio Soibelman and Gale M. Lucas and Shawn C. Roll},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0926580524006125},

doi = {10.1016/j.autcon.2024.105876},

issn = {09265805},

year  = {2025},

date = {2025-01-01},

urldate = {2024-12-20},

journal = {Automation in Construction},

volume = {169},

pages = {105876},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{murray_lazy_2024,

title = {Lazy Resampling: Fast and information preserving preprocessing for deep learning},

author = {Benjamin Murray and Richard Brown and Pengcheng Ma and Eric Kerfoot and Daguang Xu and Andrew Feng and Jorge Cardoso and Sebastien Ourselin and Marc Modat},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0169260724004152},

doi = {10.1016/j.cmpb.2024.108422},

issn = {01692607},

year  = {2024},

date = {2024-12-01},

urldate = {2025-01-16},

journal = {Computer Methods and Programs in Biomedicine},

volume = {257},

pages = {108422},

keywords = {Narrative},

pubstate = {published},

tppubtype = {article}

}

@article{xu_open-vocabulary_2024,

title = {Open-Vocabulary High-Resolution 3D (OVHR3D) Data Segmentation and Annotation Framework},

author = {Jiuyi Xu and Meida Chen and Andrew Feng and Zifan Yu and Yangming Shi},

url = {https://arxiv.org/abs/2412.06268},

doi = {10.48550/ARXIV.2412.06268},

year  = {2024},

date = {2024-12-01},

urldate = {2024-12-20},

abstract = {In the domain of the U.S. Army modeling and simulation, the availability of high quality annotated 3D data is pivotal to creating virtual environments for training and simulations. Traditional methodologies for 3D semantic and instance segmentation, such as KpConv, RandLA, Mask3D, etc., are designed to train on extensive labeled datasets to obtain satisfactory performance in practical tasks. This requirement presents a significant challenge, given the inherent scarcity of manually annotated 3D datasets, particularly for the military use cases. Recognizing this gap, our previous research leverages the One World Terrain data repository manually annotated databases, as showcased at IITSEC 2019 and 2021, to enrich the training dataset for deep learning models. However, collecting and annotating large scale 3D data for specific tasks remains costly and inefficient. To this end, the objective of this research is to design and develop a comprehensive and efficient framework for 3D segmentation tasks to assist in 3D data annotation. This framework integrates Grounding DINO and Segment anything Model, augmented by an enhancement in 2D image rendering via 3D mesh. Furthermore, the authors have also developed a user friendly interface that facilitates the 3D annotation process, offering intuitive visualization of rendered images and the 3D point cloud.},

note = {Publisher: arXiv 

Version Number: 2},

keywords = {DTIC, Narrative},

pubstate = {published},

tppubtype = {article}

}

@article{loucks_virtual_2024,

title = {Virtual Reality Exposure for Treating PTSD Due to Military Sexual Trauma},

author = {Laura Loucks and Albert Rizzo and Barbara O. Rothbaum},

url = {https://onlinelibrary.wiley.com/doi/10.1002/jclp.23750},

doi = {10.1002/jclp.23750},

issn = {0021-9762, 1097-4679},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {J Clin Psychol},

pages = {jclp.23750},

abstract = {ABSTRACT 

 Virtual reality exposure therapy (VRE) has been used in the treatment of combat‐related PTSD since the late 1990s and was recently adapted to treat PTSD due to military sexual trauma (MST). With content specifically tailored to MST‐related contexts, we present the case study of a military veteran who participated in the open clinical trial examining the feasibility of VRE in the treatment of MST‐related PTSD (Loucks et al. 2019). We illustrate VRE's use in activating the trauma memory to facilitate therapeutic emotional processing across sessions and overall symptom reduction. The case study includes common challenges that may occur during VRE and relevant recommendations. The discussion will include lessons learned from the case study and the open clinical trial, recommendations for the flexible application of VRE, and the ongoing developments in the latest version of the VRE system, informed by feedback acquired from the clinicians and patients who experienced it in the initial clinical trial.},

keywords = {DTIC, MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{hills_insights_2024,

title = {Insights for Direct-to-Patient Clinical Trial Recruitment Strategies From the Heartline Study},

author = {Mellanie Hills and Serge Korjian and Gerald Chi and Andrea Natale and Leslie Saxon and Keith Ferdinand and Kevin Kwaku and Scott Brancato and Katie Baca-Motes and Steve Steinhubl and Jeff Wessler and Nieca Goldberg and Anisha Asthana and Kate Shute and Jill Applebaum and Kathleen Doran and Janeta Nikolovski and Simrati Kaul and Dereck Wentworth and Cv Damaraju and Frank DeFalco and Cammie Tavakoli and Mithun Patel and Anne Curtis and John Spertus and Charles Gibson},

url = {https://www.ahajournals.org/doi/10.1161/circ.150.suppl_1.4143017},

doi = {10.1161/circ.150.suppl_1.4143017},

issn = {0009-7322, 1524-4539},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {Circulation},

volume = {150},

number = {Suppl_1},

abstract = {Background: 

 Decentralized clinical trials using direct-to-participant recruitment can potentially engage large, representative participant pools. 

 Research Question: 

 Can a decentralized clinical trial use a multichannel approach to recruit patients >65 years old across the United States? 

 Goals/Aims: 

 To share insights on multichannel strategies for participant recruitment in the decentralized, app-based Heartline study. 

 Methods: 

 Heartline is a randomized trial testing the impact of a mobile app-based heart health program with the electrocardiogram (ECG) and Irregular Rhythm Notification (IRN) features on Apple Watch for early diagnosis, treatment, and outcomes of atrial fibrillation. Eligible participants were US adults aged ≥65 years with an iPhone and Medicare coverage. Multiple pathways for broad outreach were explored, including digital (eg, email, social media) and traditional channels (eg, direct mail, community outreach). Recruitment efforts were assessed and refined to reach a large eligible population. 

 Results: 

 A multichannel approach led to textasciitilde300,000 Heartline study app installations. In total, 34,244 participants completed enrollment (Feb 2020-Dec 2022), of whom 28,155 completed baseline demographic assessments. Participants were widely distributed geographically, with notable representation of outlying and rural areas ( 

 Figure 1 

 ). Women accounted for 54% of the participants. Overall, most participants were White (93.0%), with Asian, Black, and Hispanic participants representing 2.8%, 2.7%, and 2.5%, respectively. 

 Conclusion: 

 The Heartline study demonstrated the ability to recruit large numbers of participants aged ≥65 years using a direct-to-participant approach. Broad outreach strategies ensured gender and geographic diversity, enrolling a higher percentage of women than typical cardiology trials, and participation from rural areas. However, underrepresentation across racial/ethnic groups persisted and strategies to increase enrollment are needed. For similar trials, a strategic multichannel approach, with strong data and analytics capabilities may be beneficial to effectively target and enroll eligible participants.},

keywords = {CBC},

pubstate = {published},

tppubtype = {article}

}

@article{chen_aerial_2024,

title = {An Aerial Photogrammetry Benchmark Dataset for Point Cloud Segmentation and Style Translation},

author = {Meida Chen and Kangle Han and Zifan Yu and Andrew Feng and Yu Hou and Suya You and Lucio Soibelman},

url = {https://www.mdpi.com/2072-4292/16/22/4240},

doi = {10.3390/rs16224240},

issn = {2072-4292},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {Remote Sensing},

volume = {16},

number = {22},

pages = {4240},

abstract = {The recent surge in diverse 3D datasets spanning various scales and applications marks a significant advancement in the field. However, the comprehensive process of data acquisition, refinement, and annotation at a large scale poses a formidable challenge, particularly for individual researchers and small teams. To this end, we present a novel synthetic 3D point cloud generation framework that can produce detailed outdoor aerial photogrammetric 3D datasets with accurate ground truth annotations without the labor-intensive and time-consuming data collection/annotation processes. Our pipeline procedurally generates synthetic environments, mirroring real-world data collection and 3D reconstruction processes. A key feature of our framework is its ability to replicate consistent quality, noise patterns, and diversity similar to real-world datasets. This is achieved by adopting UAV flight patterns that resemble those used in real-world data collection processes (e.g., the cross-hatch flight pattern) across various synthetic terrains that are procedurally generated, thereby ensuring data consistency akin to real-world scenarios. Moreover, the generated datasets are enriched with precise semantic and instance annotations, eliminating the need for manual labeling. Our approach has led to the development and release of the Semantic Terrain Points Labeling—Synthetic 3D (STPLS3D) benchmark, an extensive outdoor 3D dataset encompassing over 16 km2, featuring up to 19 semantic labels. We also collected, reconstructed, and annotated four real-world datasets for validation purposes. Extensive experiments on these datasets demonstrate our synthetic datasets’ effectiveness, superior quality, and their value as a benchmark dataset for further point cloud research.},

keywords = {DTIC, VGL},

pubstate = {published},

tppubtype = {article}

}

@article{bonial_humanrobot_2024,

title = {Human–robot dialogue annotation for multi-modal common ground},

author = {Claire Bonial and Stephanie M. Lukin and Mitchell Abrams and Anthony Baker and Lucia Donatelli and Ashley Foots and Cory J. Hayes and Cassidy Henry and Taylor Hudson and Matthew Marge and Kimberly A. Pollard and Ron Artstein and David Traum and Clare R. Voss},

url = {https://link.springer.com/10.1007/s10579-024-09784-2},

doi = {10.1007/s10579-024-09784-2},

issn = {1574-020X, 1574-0218},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {Lang Resources & Evaluation},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{marti_how_2024,

title = {How Does Acknowledging Users’ Preferences Impact AI’s Ability to Make Conflicting Recommendations?},

author = {Deniz Marti and Anjila Budathoki and Yi Ding and Gale Lucas and David Nelson},

url = {https://www.tandfonline.com/doi/full/10.1080/10447318.2024.2426035},

doi = {10.1080/10447318.2024.2426035},

issn = {1044-7318, 1532-7590},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {International Journal of Human–Computer Interaction},

pages = {1–12},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{vlake_reporting_2024,

title = {Reporting Guidelines for the Early-Phase Clinical Evaluation of Applications Using Extended Reality: RATE-XR Qualitative Study Guideline},

author = {Johan H Vlake and Denzel L Q Drop and Jasper Van Bommel and Giuseppe Riva and Brenda K Wiederhold and Pietro Cipresso and Albert S Rizzo and Barbara O Rothbaum and Cristina Botella and Lotty Hooft and Oscar J Bienvenu and Christian Jung and Bart Geerts and Evert-Jan Wils and Diederik Gommers and Michel E Van Genderen and RATE-XR Expert Group},

url = {https://www.jmir.org/2024/1/e56790},

doi = {10.2196/56790},

issn = {1438-8871},

year  = {2024},

date = {2024-11-01},

urldate = {2024-12-05},

journal = {J Med Internet Res},

volume = {26},

pages = {e56790},

abstract = {Background 

 Extended reality (XR), encompassing technologies such as virtual reality, augmented reality, and mixed reality, has rapidly gained prominence in health care. However, existing XR research often lacks rigor, proper controls, and standardization. 

 Objective 

 To address this and to enhance the transparency and quality of reporting in early-phase clinical evaluations of XR applications, we present the “Reporting for the early-phase clinical evaluation of applications using extended reality” (RATE-XR) guideline. 

 Methods 

 We conducted a 2-round modified Delphi process involving experts from diverse stakeholder categories, and the RATE-XR is therefore the result of a consensus-based, multistakeholder effort. 

 Results 

 The guideline comprises 17 XR-specific (composed of 18 subitems) and 14 generic reporting items, each with a complementary Explanation & Elaboration section. 

 Conclusions 

 The items encompass critical aspects of XR research, from clinical utility and safety to human factors and ethics. By offering a comprehensive checklist for reporting, the RATE-XR guideline facilitates robust assessment and replication of early-stage clinical XR studies. It underscores the need for transparency, patient-centeredness, and balanced evaluation of the applications of XR in health care. By providing an actionable checklist of minimal reporting items, this guideline will facilitate the responsible development and integration of XR technologies into health care and related fields.},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{wang_writing_2024,

title = {Writing with AI: What College Students Learned from Utilizing ChatGPT for a Writing Assignment},

author = {Changzhao Wang and Stephen J. Aguilar and Jennifer S. Bankard and Eric Bui and Benjamin Nye},

url = {https://www.mdpi.com/2227-7102/14/9/976},

doi = {10.3390/educsci14090976},

issn = {2227-7102},

year  = {2024},

date = {2024-09-01},

urldate = {2024-09-17},

journal = {Education Sciences},

volume = {14},

number = {9},

pages = {976},

abstract = {To support the integration of AI in education, this empirical study investigated what lessons college students learned from using Generative AI for writing. We recruited 47 students in the United States from a university writing course. Students completed an assignment in which they used Generative AI tools (e.g., ChatGPT) to draft an application letter or personal statement. Data were collected using a survey of five open-ended questions about their writing process, what worked, what did not work, how to better write with AI, and general lessons learned. We applied thematic analysis and sentiment analysis methods to analyze students’ responses. Results show that (1) students went through multiple rounds of prompting; (2) students identified strengths of AI, such as connection to topic, template generation, and sentence quality; (3) the weaknesses of AI included general language, robotic tone and lacking emotion, lacking personal voice, and lacking critical thinking; (4) students wished to improve AI-generated writing by adding personal stories, connections to posting, feelings and thoughts, and deleting repetitive language; and (5) their overall attitudes toward AI tool were positive. We believe our findings can help relieve some concerns about cheating with AI. We also suggested strategies to regulate the use of AI.},

note = {Publisher: MDPI AG},

keywords = {Learning Sciences},

pubstate = {published},

tppubtype = {article}

}

@article{lucas_calibrating_2024,

title = {Calibrating workers’ trust in intelligent automated systems},

author = {Gale M. Lucas and Burcin Becerik-Gerber and Shawn C. Roll},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2666389924001879},

doi = {10.1016/j.patter.2024.101045},

issn = {2666-3899},

year  = {2024},

date = {2024-09-01},

urldate = {2024-09-17},

journal = {Patterns},

volume = {5},

number = {9},

pages = {101045},

note = {Publisher: Elsevier BV},

keywords = {DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{zaizar_exploration_2024,

title = {Exploration of the impact of baseline clinician learner characteristics on motivational interviewing skill improvement following training with a virtual standardized patient.},

author = {Eric D. Zaizar and Michael A. Gramlich and Albert “Skip” Rizzo and Greg M. Reger and Aaron M. Norr},

url = {https://doi.apa.org/doi/10.1037/tep0000490},

doi = {10.1037/tep0000490},

issn = {1931-3926, 1931-3918},

year  = {2024},

date = {2024-08-01},

urldate = {2024-08-13},

journal = {Training and Education in Professional Psychology},

keywords = {Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{bodner_reviving_2024,

title = {Reviving life that has ceased on October the 7th: an attachment perspective on a virtual reality intervention},

author = {Ehud Bodner and Mario Mikulincer and Elizabeth McMahon and Albert Rizzo},

url = {https://www.frontiersin.org/articles/10.3389/frvir.2024.1438663/full},

doi = {10.3389/frvir.2024.1438663},

issn = {2673-4192},

year  = {2024},

date = {2024-08-01},

urldate = {2024-08-15},

journal = {Front. Virtual Real.},

volume = {5},

pages = {1438663},

abstract = {Unfortunately, in recent years, wars have forced many civilians to evacuate their homes and move to safe zones. The event of October the seventh that took place in many Kibbutzim near the Gaza strip, exposed families who were on a Jewish holiday, to the murder of family and community members. They had to leave their burned houses and move to hotels and apartment buildings in other parts of Israel. Many people, also from the Northen parts of the country, are still in new safe zones, and have huge difficulties in returning to their houses (and not only because of objective security reasons). In this “perspective” article we propose a Virtual Reality (VR) application, which is based on past and current research in the fields of attachment theory and traumatic grief. We propose that in addition to the use of exposure therapy, a VR simulation which will activate the attachment system, can reorganize the evacuees’ figure and place attachment representations. We suggest that such a simulation will revive the evacuees’ sense of safe-haven and secure base and enable them to return to their home place, or to adjust to a new place, thereby leading to optimal adjustment. We start with a presentation of the theory of attachment, place attachment, attachment and loss and the two-track model of bereavement. Then, we describe the design of our VR intervention that aims to address this challenge from the attachment theory perspective with the evacuees. Finally, we discuss the challenges that need to be dealt with to implement the VR interventions through resilience centers in Israel.},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{parga_differences_2024,

title = {Differences in Self-Rated Worker Outcomes Across Stress States: An Interim Analysis of Hybrid Worker Data},

author = {Madeline R. Parga and Shawn C. Roll and Gale M. Lucas and Burcin Becerik-Gerber and Shrikanth Naranayan},

url = {https://journals.sagepub.com/doi/10.1177/10711813241275500},

doi = {10.1177/10711813241275500},

issn = {1071-1813, 2169-5067},

year  = {2024},

date = {2024-08-01},

urldate = {2024-09-17},

journal = {Proceedings of the Human Factors and Ergonomics Society Annual Meeting},

abstract = {Stress experiences can have dire consequences for worker performance and well-being, and the social environment of the workplace is a key contributor to worker experience. This study investigated the relationship between hybrid workers’ self-ratings of productivity, mood, and stress with perceptions of positive (eustress) and negative (distress) stress states. We hypothesized that self-ratings would vary across combinations of eustress and distress experiences and that these differences would differ based on the social context. Ecological momentary assessments (EMA) were used to obtain ecologically valid data at four data points each workday across a 4-month study period in a cohort of seven office workers. Findings aligned with the Yerkes–Dodson law, such that higher states of arousal were associated with greater self-perceived productivity, and higher stress magnitudes were found when distress existed. Compared to other states, eustress was associated with higher productivity in work-related activities and better mood across all activity types.},

note = {Publisher: SAGE Publications},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{diaz-pinto_monai_2024,

title = {MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images},

author = {Andres Diaz-Pinto and Sachidanand Alle and Vishwesh Nath and Yucheng Tang and Alvin Ihsani and Muhammad Asad and Fernando Pérez-García and Pritesh Mehta and Wenqi Li and Mona Flores and Holger R. Roth and Tom Vercauteren and Daguang Xu and Prerna Dogra and Sebastien Ourselin and Andrew Feng and M. Jorge Cardoso},

url = {https://linkinghub.elsevier.com/retrieve/pii/S1361841524001324},

doi = {10.1016/j.media.2024.103207},

issn = {13618415},

year  = {2024},

date = {2024-07-01},

urldate = {2025-01-16},

journal = {Medical Image Analysis},

volume = {95},

pages = {103207},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{al_owayyed_agent-based_2024,

title = {Agent-based social skills training systems: the ARTES architecture, interaction characteristics, learning theories and future outlooks},

author = {Mohammed Al Owayyed and Myrthe Tielman and Arno Hartholt and Marcus Specht and Willem-Paul Brinkman},

url = {https://www.tandfonline.com/doi/full/10.1080/0144929X.2024.2374891},

doi = {10.1080/0144929X.2024.2374891},

issn = {0144-929X, 1362-3001},

year  = {2024},

date = {2024-07-01},

urldate = {2024-08-15},

journal = {Behaviour & Information Technology},

pages = {1–28},

keywords = {Virtual Agents, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{bell_advances_2024,

title = {Advances in the use of virtual reality to treat mental health conditions},

author = {Imogen H. Bell and Roos Pot-Kolder and Albert Rizzo and Mar Rus-Calafell and Valentina Cardi and Matteo Cella and Thomas Ward and Simon Riches and Martin Reinoso and Andrew Thompson and Mario Alvarez-Jimenez and Lucia Valmaggia},

url = {https://www.nature.com/articles/s44159-024-00334-9},

doi = {10.1038/s44159-024-00334-9},

issn = {2731-0574},

year  = {2024},

date = {2024-07-01},

urldate = {2024-07-11},

journal = {Nat Rev Psychol},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{gunasekara_overview_2024,

title = {Overview of the Ninth Dialog System Technology Challenge: DSTC9},

author = {Chulaka Gunasekara and Seokhwan Kim and Luis Fernando D'Haro and Abhinav Rastogi and Yun-Nung Chen and Mihail Eric and Behnam Hedayatnia and Karthik Gopalakrishnan and Yang Liu and Chao-Wei Huang and Dilek Hakkani-Tür and Jinchao Li and Qi Zhu and Lingxiao Luo and Lars Liden and Kaili Huang and Shahin Shayandeh and Runze Liang and Baolin Peng and Zheng Zhang and Swadheen Shukla and Minlie Huang and Jianfeng Gao and Shikib Mehri and Yulan Feng and Carla Gordon and Seyed Hossein Alavi and David Traum and Maxine Eskenazi and Ahmad Beirami and Eunjoon Cho and Paul A. Crook and Ankita De and Alborz Geramifard and Satwik Kottur and Seungwhan Moon and Shivani Poddar and Rajen Subba},

url = {https://ieeexplore.ieee.org/document/10595468/},

doi = {10.1109/TASLP.2024.3426331},

issn = {2329-9290, 2329-9304},

year  = {2024},

date = {2024-07-01},

urldate = {2024-08-15},

journal = {IEEE/ACM Trans. Audio Speech Lang. Process.},

pages = {1–10},

keywords = {Natural Language},

pubstate = {published},

tppubtype = {article}

}

@article{nurunnabi_development_2024,

title = {Development of a Precise Tree Structure from LiDAR Point Clouds},

author = {Abdul Nurunnabi and Felicia Teferle and Debra F. Laefer and Meida Chen and Mir Masoom Ali},

url = {https://isprs-archives.copernicus.org/articles/XLVIII-2-2024/301/2024/},

doi = {10.5194/isprs-archives-XLVIII-2-2024-301-2024},

issn = {2194-9034},

year  = {2024},

date = {2024-06-01},

urldate = {2024-07-11},

journal = {Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.},

volume = {XLVIII-2-2024},

pages = {301–308},

abstract = {Abstract. A precise tree structure that represents the distribution of tree stem, branches, and leaves is crucial for accurately capturing the full representation of a tree. Light Detection and Ranging (LiDAR)-based three-dimensional (3D) point clouds (PCs) capture the geometry of scanned objects including forests stands and individual trees. PCs are irregular, unstructured, often noisy, and contaminated by outliers. Researchers have struggled to develop methods to separate leaves and wood without losing the tree geometry. This paper proposes a solution that employs only the spatial coordinates (x, y, z) of the PC. The new algorithm works as a filtering approach, utilizing multi-scale neighborhood-based geometric features (GFs) e.g., linearity, planarity, and verticality to classify linear (wood) and non-linear (leaf) points. This involves finding potential wood points and coupling them with an octree-based segmentation to develop a tree architecture. The main contributions of this paper are (i) investigating the potential of different GFs to split linear and non-linear points, (ii) introducing a novel method that pointwise classifies leaf and wood points, and (iii) developing a precise 3D tree structure. The performance of the new algorithm has been demonstrated through terrestrial laser scanning PCs. For a Scots pine tree, the new method classifies leaf and wood points with an overall accuracy of 97.9%.},

keywords = {Narrative, VGL},

pubstate = {published},

tppubtype = {article}

}

@article{zhang_motiondiffuse_2024,

title = {MotionDiffuse: Text-Driven Human Motion Generation With Diffusion Model},

author = {Mingyuan Zhang and Zhongang Cai and Liang Pan and Fangzhou Hong and Xinying Guo and Lei Yang and Ziwei Liu},

url = {https://ieeexplore.ieee.org/document/10416192/},

doi = {10.1109/TPAMI.2024.3355414},

issn = {0162-8828, 2160-9292, 1939-3539},

year  = {2024},

date = {2024-06-01},

urldate = {2024-07-18},

journal = {IEEE Trans. Pattern Anal. Mach. Intell.},

volume = {46},

number = {6},

pages = {4115–4128},

keywords = {VGL},

pubstate = {published},

tppubtype = {article}

}

@article{saxon_continuous_2024,

title = {Continuous Assessment of Active-Duty Army Special Operations and Reconnaissance Marines Using Digital Devices and Custom Software: The Digital Comprehensive Operator Readiness Assessment (DcORA) Study},

author = {Leslie Saxon and Robert T Faulk and Jill Boberg and Trevor Barrett and Steve McLelland},

url = {https://www.jsomonline.org/Citations/PXKK-I23D.php},

doi = {10.55460/PXKK-I23D},

issn = {1553-9768},

year  = {2024},

date = {2024-06-01},

urldate = {2024-06-25},

journal = {J. Spec. Oper. Med.},

keywords = {CBC, DTIC},

pubstate = {published},

tppubtype = {article}

}

@article{chen_large-scale_2024,

title = {Large-Scale 3D Terrain Reconstruction Using 3D Gaussian Splatting for Visualization and Simulation},

author = {Meida Chen and Devashish Lal and Zifan Yu and Jiuyi Xu and Andrew Feng and Suya You and Abdul Nurunnabi and Yangming Shi},

url = {https://isprs-archives.copernicus.org/articles/XLVIII-2-2024/49/2024/},

doi = {10.5194/isprs-archives-XLVIII-2-2024-49-2024},

issn = {2194-9034},

year  = {2024},

date = {2024-06-01},

urldate = {2024-06-20},

journal = {Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.},

volume = {XLVIII-2-2024},

pages = {49–54},

abstract = {Abstract. The fusion of low-cost unmanned aerial systems (UAS) with advanced photogrammetric techniques has revolutionized 3D terrain reconstruction, enabling the automated creation of detailed models. Concurrently, the advent of 3D Gaussian Splatting has introduced a paradigm shift in 3D data representation, offering visually realistic renditions distinct from traditional polygon-based models. Our research builds upon this foundation, aiming to integrate Gaussian Splatting into interactive simulations for immersive virtual environments. We address challenges such as collision detection by adopting a hybrid approach, combining Gaussian Splatting with photogrammetry-derived meshes. Through comprehensive experimentation covering varying terrain sizes and Gaussian densities, we evaluate scalability, performance, and limitations. Our findings contribute to advancing the use of advanced computer graphics techniques for enhanced 3D terrain visualization and simulation.},

keywords = {DTIC, Graphics, VGL},

pubstate = {published},

tppubtype = {article}

}

@article{koresh_improving_2024,

title = {Improving Reinforcement Learning Experiments in Unity through Waypoint Utilization},

author = {Caleb Koresh and Volkan Ustun and Rajay Kumar and Tim Aris},

url = {https://journals.flvc.org/FLAIRS/article/view/135571},

doi = {10.32473/flairs.37.1.135571},

issn = {2334-0762},

year  = {2024},

date = {2024-05-01},

urldate = {2024-08-13},

journal = {FLAIRS},

volume = {37},

abstract = {Multi-agent Reinforcement Learning (MARL) models teams of agents that learn by dynamically interacting with an environment and each other, presenting opportunities to train adaptive models for team-based scenarios. However, MARL algorithms pose substantial challenges due to their immense computational requirements. This paper introduces an automatically generated waypoint-based movement system to abstract and simplify complex environments in Unity while allowing agents to learn strategic cooperation. To demonstrate the effectiveness of our approach, we utilized a simple scenario with heterogeneous roles in each team. We trained this scenario on variations of realistic terrains and compared learning between fine-grained (almost) continuous and waypoint-based movement systems. Our results indicate efficiency in learning and improved performance with waypoint-based navigation. Furthermore, our results show that waypoint-based movement systems can effectively learn differentiated behavior policies for heterogeneous roles in these experiments. These early exploratory results point out the potential of waypoint-based navigation for reducing the computational costs of developing and training MARL models in complex environments. The complete project with all scenarios and results is available on GitHub: https://github.com/HATS-ICT/ml-agents-dodgeball-env-ICT.},

keywords = {Machine Learning},

pubstate = {published},

tppubtype = {article}

}

@article{aris_training_2024,

title = {Training Reinforcement Learning Agents to React to an Ambush for Military Simulations},

author = {Timothy Aris and Volkan Ustun and Rajay Kumar},

url = {https://journals.flvc.org/FLAIRS/article/view/135578},

doi = {10.32473/flairs.37.1.135578},

issn = {2334-0762},

year  = {2024},

date = {2024-05-01},

urldate = {2024-08-13},

journal = {FLAIRS},

volume = {37},

abstract = {There is a need for realistic Opposing Forces (OPFOR)behavior in military training simulations. Current trainingsimulations generally only have simple, non-adaptivebehaviors, requiring human instructors to play the role ofOPFOR in any complicated scenario. This poster addressesthis need by focusing on a specific scenario: trainingreinforcement learning agents to react to an ambush. Itproposes a novel way to check for occlusion algorithmically.It shows vector fields showing the agent’s actions throughthe course of a training run. It shows that a single agentswitching between multiple goals is possible, at least in asimplified environment. Such an approach could reduce theneed to develop different agents for different scenarios.Finally, it shows a competent agent trained on a simplifiedReact to Ambush scenario, demonstrating the plausibility ofa scaled-up version.},

keywords = {Simulation, VR},

pubstate = {published},

tppubtype = {article}

}

@article{liu_leveraging_2024,

title = {Leveraging Organizational Hierarchy to Simplify Reward Design in Cooperative Multi-agent Reinforcement Learning},

author = {Lixing Liu and Volkan Ustun and Rajay Kumar},

url = {https://journals.flvc.org/FLAIRS/article/view/135588},

doi = {10.32473/flairs.37.1.135588},

issn = {2334-0762},

year  = {2024},

date = {2024-05-01},

urldate = {2024-08-13},

journal = {FLAIRS},

volume = {37},

abstract = {The effectiveness of multi-agent reinforcement learning (MARL) hinges largely on the meticulous arrangement of objectives. Yet, conventional MARL methods might not completely harness the inherent structures present in environmental states and agent relationships for goal organization. This study is conducted within the domain of military training simulations, which are typically characterized by complexity, heterogeneity, non-stationary and doctrine-driven environments with a clear organizational hierarchy and a top-down chain of command. This research investigates the approximation and integration of the organizational hierarchy into MARL for cooperative training scenarios, with the goal of streamlining the processes of reward engineering and enhancing team coordination. In the preliminary experiments, we employed two-tiered commander-subordinate feudal hierarchical (CSFH) networks to separate the prioritized team goal and individual goals. The empirical results demonstrate that the proposed framework enhances learning efficiency. It guarantees the learning of a prioritized policy for the commander agent and encourages subordinate agents to explore areas of interest more frequently, guided by appropriate soft constraints imposed by the commander.},

keywords = {Machine Learning},

pubstate = {published},

tppubtype = {article}

}

@article{lukin-etal-2024-scout-situated,

title = {SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus},

author = {Stephanie M Lukin and Claire Bonial and Matthew Marge and Taylor Hudson and Cory J. Hayes and Kimberly Pollard and Anthony L. Baker and Ashley Foots and Ron Artstein and Felix Gervits and Mitchell Abrams and Henry Cassidy and Lucia Donatelli and Anton Leuski and Susan G. Hill and David Traum and Clare Voss},

url = {https://aclanthology.org/2024.lrec-main.1259},

year  = {2024},

date = {2024-05-01},

pages = {14445 - 144458},

abstract = {We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus was constructed from multiple Wizard-of-Oz experiments where human participants gave verbal instructions to a remotely-located robot to move and gather information about its surroundings. SCOUT contains 89,056 utterances and 310,095 words from 278 dialogues averaging 320 utterances per dialogue. The dialogues are aligned with the multi-modal data streams available during the experiments: 5,785 images and 30 maps. The corpus has been annotated with Abstract Meaning Representation and Dialogue-AMR to identify the speaker’s intent and meaning within an utterance, and with Transactional Units and Relations to track relationships between utterances to reveal patterns of the Dialogue Structure. We describe how the corpus and its annotations have been used to develop autonomous human-robot systems and enable research in open questions of how humans speak to robots. We release this corpus to accelerate progress in autonomous, situated, human-robot dialogue, especially in the context of navigation tasks where details about the environment need to be discovered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chemburkar_evaluating_2024,

title = {Evaluating Vision-Language Models on the TriangleCOPA Benchmark},

author = {Ankur Chemburkar and Andrew Gordon and Andrew Feng},

year  = {2024},

date = {2024-05-01},

journal = {FLAIRS-37},

volume = {37},

abstract = {The TriangleCOPA benchmark consists of 100 textual questions with videos depicting the movements of simple shapes in the style of the classic social-psychology film created by Fritz Heider and Marianne Simmel in 1944. In our experiments, we investigate the performance of current vision-language models on this challenging benchmark, assessing the capability of these models for visual anthropomorphism and abstract interpretation.},

keywords = {DTIC, Narrative},

pubstate = {published},

tppubtype = {article}

}

@article{murawski_span_2024,

title = {<span style="font-variant:small-caps;">NegotiAge</span> : Development and pilot testing of an artificial intelligence‐based family caregiver negotiation program},

author = {Alaine Murawski and Vanessa Ramirez‐Zohfeld and Johnathan Mell and Marianne Tschoe and Allison Schierer and Charles Olvera and Jeanne Brett and Jonathan Gratch and Lee A. Lindquist},

url = {https://agsjournals.onlinelibrary.wiley.com/doi/10.1111/jgs.18775},

doi = {10.1111/jgs.18775},

issn = {0002-8614, 1532-5415},

year  = {2024},

date = {2024-04-01},

urldate = {2024-12-05},

journal = {J American Geriatrics Society},

volume = {72},

number = {4},

pages = {1112–1121},

abstract = {Abstract 

 Background 

 Family caregivers of people with Alzheimer's disease experience conflicts as they navigate health care but lack training to resolve these disputes. We sought to develop and pilot test an artificial‐intelligence negotiation training program, NegotiAge, for family caregivers. 

 Methods 

 We convened negotiation experts, a geriatrician, a social worker, and community‐based family caregivers. Content matter experts created short videos to teach negotiation skills. Caregivers generated dialogue surrounding conflicts. Computer scientists utilized the dialogue with the Interactive Arbitration Guide Online (IAGO) platform to develop avatar‐based agents (e.g., sibling, older adult, physician) for caregivers to practice negotiating. Pilot testing was conducted with family caregivers to assess usability (USE) and satisfaction (open‐ended questions with thematic analysis). 

 Results 

 Development: With NegotiAge, caregivers progress through didactic material, then receive scenarios to negotiate (e.g., physician recommends gastric tube, sibling disagrees with home support, older adult refusing support). Caregivers negotiate in real‐time with avatars who are designed to act like humans, including emotional tactics and irrational behaviors. Caregivers send/receive offers, using tactics until either mutual agreement or time expires. Immediate feedback is generated for the user to improve skills training. Pilot testing: Family caregivers ( 

 n = 12) completed the program and survey. USE questionnaire (Likert scale 1–7) subset scores revealed: (1) Useful—Mean 5.69 (SD 0.76); (2) Ease—Mean 5.24 (SD 0.96); (3) Learn—Mean 5.69 (SD 0.74); (4) Satisfy—Mean 5.62 (SD 1.10). Items that received over 80% agreements were: It helps me be more effective; It helps me be more productive; It is useful; It gives me more control over the activities in my life; It makes the things I want to accomplish easier to get done. Participants were highly satisfied and found NegotiAge fun to use (91.7%), with 100% who would recommend it to a friend. 

 Conclusion 

 NegotiAge is an Artificial‐Intelligent Caregiver Negotiation Program, that is usable and feasible for family caregivers to become familiar with negotiating conflicts commonly seen in health care.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{soleymani_guest_2024,

title = {Guest Editorial Best of ACII 2021},

author = {Mohammad Soleymani and Shiro Kumano and Emily Mower Provost and Nadia Bianchi-Berthouze and Akane Sano and Kenji Suzuki},

url = {https://ieeexplore.ieee.org/document/10542496/},

doi = {10.1109/TAFFC.2024.3389249},

issn = {1949-3045, 2371-9850},

year  = {2024},

date = {2024-04-01},

urldate = {2024-06-25},

journal = {IEEE Trans. Affective Comput.},

volume = {15},

number = {2},

pages = {376–379},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{goh_normative_2024,

title = {Normative performance data on visual attention in neurotypical children: virtual reality assessment of cognitive and psychomotor development},

author = {Crystal Goh and Yu Ma and Albert Rizzo},

url = {https://www.frontiersin.org/articles/10.3389/frvir.2024.1309176/full},

doi = {10.3389/frvir.2024.1309176},

issn = {2673-4192},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-16},

journal = {Front. Virtual Real.},

volume = {5},

pages = {1309176},

abstract = {Introduction: 

 Virtual Reality (VR) is revolutionizing healthcare research and practice by offering innovative methodologies across various clinical conditions. Advances in VR technology enable the creation of controllable, multisensory 3D environments, making it an appealing tool for capturing and quantifying behavior in realistic scenarios. This paper details the application of VR as a tool for neurocognitive evaluation, specifically in attention process assessment, an area of relevance for informing the diagnosis of childhood health conditions such as Attention Deficit Hyperactivity Disorder (ADHD). 

 Methods: 

 The data presented focuses on attention performance results from a large sample ( 

 n = 837) of neurotypical male and female children (ages 6–13) tested on a visual continuous performance task, administered within an immersive VR classroom environment. This data was collected to create a normative baseline database for use to inform comparisons with the performances of children with ADHD to support diagnostic decision-making in this area. 

 Results: 

 Results indicate systematic improvements on most metrics across the age span, and sex differences are noted on key variables thought to reflect differential measures of hyperactivity and inattention in children with ADHD. Results support VR technology as a safe and viable option for testing attention processes in children, under stimulus conditions that closely mimic ecologically relevant challenges found in everyday life. 

 Discussion: 

 In response to these stimulus conditions, VR can support advanced methods for capturing and quantifying users’ behavioral responses. VR offers a more systematic and objective approach for clinical assessment and intervention and provides conceptual support for its use in a wide variety of healthcare contexts.},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{soleymani_robust_2024,

title = {Robust Tube-Based Reference Tracking Nonlinear Model Predictive Control for Wind Turbines},

author = {Mohammad Soleymani and Mehdi Rahmani and Nooshin Bigdeli},

url = {https://ieeexplore.ieee.org/document/10495787/},

doi = {10.1109/TASE.2024.3385714},

issn = {1545-5955, 1558-3783},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-16},

journal = {IEEE Trans. Automat. Sci. Eng.},

pages = {1–13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_conversational_2024,

title = {Conversational technology and reactions to withheld information},

author = {Nikolos Gurney and George Loewenstein and Nick Chater},

editor = {Petre Caraiani},

url = {https://dx.plos.org/10.1371/journal.pone.0301382},

doi = {10.1371/journal.pone.0301382},

issn = {1932-6203},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-16},

journal = {PLoS ONE},

volume = {19},

number = {4},

pages = {e0301382},

abstract = {People frequently face decisions that require making inferences about withheld information. The advent of large language models coupled with conversational technology, e.g., Alexa, Siri, Cortana, and the Google Assistant, is changing the mode in which people make these inferences. We demonstrate that conversational modes of information provision, relative to traditional digital media, result in more critical responses to withheld information, including: (1) a reduction in evaluations of a product or service for which information is withheld and (2) an increased likelihood of recalling that information was withheld. These effects are robust across multiple conversational modes: a recorded phone conversation, an unfolding chat conversation, and a conversation script. We provide further evidence that these effects hold for conversations with the Google Assistant, a prominent conversational technology. The experimental results point to participants’ intuitions about why the information was withheld as the driver of the effect.},

keywords = {DTIC, Social Simulation, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{detore_artificial_2024,

title = {An Artificial Intelligence-Based Virtual Human Avatar Application to Assess the Mental Health of Health Care Professionals: A Validation Study},

author = {Nicole R. DeTore and Oyenike Balogun-Mwangi and Elizabeth S. Eberlin and Katherine N. Dokholyan and Albert Rizzo and Daphne J. Holt},

url = {https://www.liebertpub.com/doi/10.1089/jmxr.2024.0016},

doi = {10.1089/jmxr.2024.0016},

issn = {2994-1520},

year  = {2024},

date = {2024-03-01},

urldate = {2024-11-01},

journal = {Journal of Medical Extended Reality},

volume = {1},

number = {1},

pages = {215–226},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{frummet_cooking_2024,

title = {Cooking with Conversation: Enhancing User Engagement and Learning with a Knowledge-Enhancing Assistant},

author = {Alexander Frummet and Alessandro Speggiorin and David Elsweiler and Anton Leuski and Jeff Dalton},

url = {https://dl.acm.org/doi/10.1145/3649500},

doi = {10.1145/3649500},

issn = {1046-8188, 1558-2868},

year  = {2024},

date = {2024-03-01},

urldate = {2024-04-16},

journal = {ACM Trans. Inf. Syst.},

pages = {3649500},

abstract = {We present two empirical studies to investigate users’ expectations and behaviours when using digital assistants, such as Alexa and Google Home, in a kitchen context: First, a survey (N=200) queries participants on their expectations for the kinds of information that such systems should be able to provide. While consensus exists on expecting information about cooking steps and processes, younger participants who enjoy cooking express a higher likelihood of expecting details on food history or the science of cooking. In a follow-up Wizard-of-Oz study (N = 48), users were guided through the steps of a recipe either by an 

 active 

 wizard that alerted participants to information it could provide or a 

 passive 

 wizard who only answered questions that were provided by the user. The 

 active 

 policy led to almost double the number of conversational utterances and 1.5 times more knowledge-related user questions compared to the 

 passive 

 policy. Also, it resulted in 1.7 times more knowledge communicated than the 

 passive 

 policy. We discuss the findings in the context of related work and reveal implications for the design and use of such assistants for cooking and other purposes such as DIY and craft tasks, as well as the lessons we learned for evaluating such systems.},

keywords = {DTIC, Natural Language, UARC},

pubstate = {published},

tppubtype = {article}

}