28 citations · 167 across the 50 of their papers we have counts for
55 papers
Exploring Object Recall in an Object-Rich AR Office Scene
Sangita Kunapuli, Shane Dirksen, Radha Kumaran +4
Augmented reality (AR) changes how users perceive and attend to their surroundings. Prior work suggests AR can reduce attention to the physical world, but it remains unclear whethe…
Reward Hacking Challenges Oversight of Autonomous Research Agents
Yue Huang, Zhangchen Xu, Yuchen Ma +12
Autonomous research agents can design experiments, evaluate results, and write reports, giving them control over both a scientific result and the evidence used to support it. This…
FenceXR: AR Movement Replay for Error-Detection Training and Spatially Grounded Feedback
Avinash Ajit Nargund, Amelia Haruka Harrison, Timothy Robinson +2
Recognizing technical errors in movement is a perceptual skill important to motor learning, but it is challenging for beginners in fast, complex sports like fencing to develop it.…
The Missing Link of XR: Empathy-Driven Reality for XR and Beyond
Yun Suen Pai, Tamil Selvan Gunasekaran, Jiashuo Cao +23
Extended reality (XR) for socialising is becoming increasingly popular. However, unlike conventional social platforms, XR prioritises embodiment and immersion, factors that strongl…
AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?
Zhangchen Xu, Junda Chen, Yue Huang +16
Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and continuously refining artifac…
MiXR: Harvesting and Recomposing Geometry from Real-World Objects for In-Situ 3D Design
Faraz Faruqi, Demircan Tas, Arthur Caetano +6
Recent developments in 3D generative AI enable users to create bespoke 3D models from text or image prompts. However, these approaches provide limited control over spatial structur…
Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?
Yichen Feng, Yuetai Li, Chunjiang Liu +14
Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of these applications require an expl…
Grand Challenges around Designing Computers' Control Over Our Bodies
Florian 'Floyd' Mueller, Nadia Bianchi-Berthouze, Misha Sra +21
Advances in emerging technologies, such as on-body mechanical actuators and electrical muscle stimulation, have allowed computers to take control over our bodies. This presents opp…
How Users Perceive Mixed-Initiative AI: Attitudes Toward Assistance in Problem Solving
Yunhao Luo, Arthur Caetano, Avinash Ajit Nargund +2
In mixed-initiative systems, the mode of AI assistance delivery can be as consequential as the assistance itself. We investigated two assistance delivery modes: on-demand help (use…
Embedded vs. Situated: An Evaluation of AR Facial Training Feedback
Avinash Ajit Nargund, Andrea M. Park, Tobias Höllerer +1
While augmented reality (AR) research demonstrates benefits of embedded visualizations for gross motor training, its applicability to facial exercises remains under-explored. Provi…
Exploration of Radar-based Obstacle Visualizations to Support Safety and Presence in Camera-Free Outdoor VR
Avinash Ajit Nargund, Andrew L. Huard, Tobias Höllerer +1
Outdoor virtual reality (VR) places users in dynamic physical environments where they must remain aware of real-world obstacles, including static structures and moving bystanders,…
AlignUI: A Method for Designing LLM-Generated UIs Aligned with User Preferences
Yimeng Liu, Misha Sra, Chang Xiao
Designing user interfaces that align with user preferences is a time-consuming process, which requires iterative cycles of prototyping, user testing, and refinement. Recent advance…
Audience Amplified: Virtual Audiences in Asynchronously Performed AR Theater
You-Jin Kim, Misha Sra, Tobias Höllerer
Audience reactions can considerably enhance live experiences; conversely, in anytime-anywhere augmented reality (AR) experiences, large crowds of people might not always be availab…
TaskLens: Generating Task-Conditioned Scaffolded Interfaces for Learning Professional Creative Software
Yimeng Liu, Misha Sra
Professional creative software has steep learning curves for novices due to complex interfaces, limited guidance, and unfamiliar terminology. To support educators and tool creators…
CoDA: Agentic Systems for Collaborative Data Visualization
Zichen Chen, Jiefeng Chen, Sercan Ö. Arik +3
Deep research has revolutionized data analysis, yet data scientists still devote substantial time to manually crafting visualizations, highlighting the need for robust automation f…
ReUseIt: Synthesizing Reusable AI Agent Workflows for Web Automation
Yimeng Liu, Misha Sra, Jeevana Priya Inala +1
AI-powered web agents have the potential to automate repetitive tasks, such as form filling, information retrieval, and scheduling, but they struggle to reliably execute these task…
Understanding Role Switching in Human-AI Collaboration through Multimodal Behavioral Signals
Avinash Ajit Nargund, Arthur Caetano, Kevin Yang +7
Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which subtasks they perform and which their AI…
XARP Tools: An Extended Reality Platform for Humans and AI Agents
Arthur Caetano, Radha Kumaran, Kelvin Jou +2
Building XR-AI research prototypes requires navigating two largely separate ecosystems. Mainstream XR development relies on C#/C++ and game engines, while AI development is centere…
Designing Scaffolded Interfaces for Enhanced Learning and Performance in Professional Software
Yimeng Liu, Misha Sra
Professional software offers immense power but also presents significant learning challenges. Its complex interfaces, as well as insufficient built-in structured guidance and unfam…
Instruct-CLIP: Improving Instruction-Guided Image Editing with Automated Data Refinement Using Contrastive Learning
Sherry X. Chen, Misha Sra, Pradeep Sen
Although natural language instructions offer an intuitive way to guide automated image editing, deep-learning models often struggle to achieve high-quality results, largely due to…
Standard Benchmarks Fail -- Auditing LLM Agents in Finance Must Prioritize Risk
Zichen Chen, Jiaao Chen, Jianda Chen +1
Standard benchmarks fixate on how well large language model (LLM) agents perform in finance, yet say little about whether they are safe to deploy. We argue that accuracy metrics an…
Agentic Workflows for Conversational Human-AI Interaction Design
Arthur Caetano, Kavya Verma, Atieh Taheri +5
Conversational human-AI interaction (CHAI) have recently driven mainstream adoption of AI. However, CHAI poses two key challenges for designers and researchers: users frequently ha…
Engaging with AI: How Interface Design Shapes Human-AI Collaboration in High-Stakes Decision-Making
Zichen Chen, Yunhao Luo, Misha Sra
As reliance on AI systems for decision-making grows, it becomes critical to ensure that human users can appropriately balance trust in AI suggestions with their own judgment, espec…
GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design
Arthur Caetano, Yunhao Luo, Adwait Sharma +1
Grasp User Interfaces (grasp UIs) enable dual-tasking in XR by allowing interaction with digital content while holding physical objects. However, current grasp UI design practices…