Understanding Users' Perceptions and Expectations toward a Social Balloon Robot via an Exploratory StudyWe are witnessing a new epoch in embodied social agents. Most of the work has focused on ground or desktop robots that enjoy technical maturity and rich social channels but are often limited by terrain. Drones, which enable spatial mobility, currently face issues with safety and proximity. This paper explores a social balloon robot as a viable alternative that combines these advantages and alleviates limitations. To this end, we developed a hardware prototype named BalloonBot that integrates various devices for social functioning and a helium balloon. We conducted an exploratory lab study on users’ perceptions and expectations about its demonstrated interactions and functions. Our results show promise in using such a robot as another form of socially embodied agent. We highlight its unique mobile and approachable characteristics that harvest novel user experiences and outline factors that should be considered before its broad applications.2025CWChongyang Wang et al.Social Robot InteractionUIST
Enhancing Smartphone Eye Tracking with Cursor-Based Interactive Implicit CalibrationThe limited accuracy of eye-tracking on smartphones restricts its use. Existing RGB-camera-based eye-tracking relies on extensive datasets, which could be enhanced by continuous fine-tuning using calibration data implicitly collected from the interaction. In this context, we propose COMETIC (Cursor Operation Mediated Eye-Tracking Implicit Calibration), which introduces a cursor-based interaction and utilizes the inherent correlation between cursor and eye movement. By filtering valid cursor coordinates as proxies for the ground truth of gaze and fine-tuning the eye-tracking model with corresponding images, COMETIC enhances accuracy during the interaction. Both filtering and fine-tuning use pre-trained models and could be facilitated using personalized, dynamically updated data. Results show COMETIC achieves an average eye-tracking er- ror of 278.3 px (1.60 cm, 2.29◦), representing a 27.2% improvement compared to that without fine-tuning. We found that filtering cursor points whose actual distance to gaze is 150.0 px (0.86 cm) yields the best eye-tracking results.2025CLChang Liu et al.Tsinghua University, Department of Computer Science and TechnologyEye Tracking & Gaze InteractionHuman-LLM CollaborationVisualization Perception & CognitionCHI
OutlineSpark: Igniting AI-powered Presentation Slides Creation from Computational Notebooks through OutlinesComputational notebooks are widely utilized for exploration and analysis. However, creating slides to communicate analysis results from these notebooks is quite tedious and time-consuming. Researchers have proposed automatic systems for generating slides from notebooks, which, however, often do not consider the process of users conceiving and organizing their messages from massive code cells. Those systems ask users to go directly into the slide creation process, which causes potentially ill-structured slides and burdens in further refinement. Inspired by the common and widely recommended slide creation practice: drafting outlines first and then adding concrete content, we introduce OutlineSpark, an AI-powered slide creation tool that generates slides from a slide outline written by the user. The tool automatically retrieves relevant notebook cells based on the outlines and converts them into slide content. We evaluated OutlineSpark with 12 users. Both the quantitative and qualitative feedback from the participants verify its effectiveness and usability.2024FWFengjie Wang et al.Sichuan University, The Hong Kong University of Science and TechnologyHuman-LLM CollaborationData StorytellingCHI
"It Must Be Gesturing Towards Me": Gesture-Based Interaction between Autonomous Vehicles and PedestriansInteracting with pedestrians understandably and efficiently is one of the toughest challenges faced by autonomous vehicles (AVs) due to the limitations of current algorithms and external human-machine interfaces (eHMIs). In this paper, we design eHMIs based on gestures inspired by the most popular method of interaction between pedestrians and human drivers. Eight common gestures were selected to convey AVs' yielding or non-yielding intentions at uncontrolled crosswalks from previous literature. Through a VR experiment (N1 = 31) and a following online survey (N2 = 394), we discovered significant differences in the usability of gesture-based eHMIs compared to current eHMIs. Good gesture-based eHMIs increase the efficiency of pedestrian-AV interaction while ensuring safety. Poor gestures, however, cause misinterpretation. The underlying reasons were explored: ambiguity regarding the recipient of the signal and whether the gestures are precise, polite, and familiar to pedestrians. Based on this empirical evidence, we discuss potential opportunities and provide valuable insights into developing comprehensible gesture-based eHMIs in the future to support better interaction between AVs and other road users.2024XCXiang Chang et al.Tsinghua University, Sichuan UniversityExternal HMI (eHMI) — Communication with Pedestrians & CyclistsHand Gesture RecognitionCHI
NFTDisk: Visual Detection of Wash Trading in NFT MarketsWith the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with a disk metaphor to overview NFT transactions and a flow-based visualization module to reveal detailed NFT flows at multiple levels. We conduct two case studies and an in-depth user interview with 14 NFT investors to evaluate NFTDisk. The results demonstrate its effectiveness in exploring wash trading activities in NFT markets.2023XWXiaolin Wen et al.Sichuan University, Singapore Management UniversityInteractive Data VisualizationUncertainty VisualizationCHI
Slide4N: Creating Presentation Slides from Computational Notebooks with Human-AI CollaborationData scientists often have to use other presentation tools (e.g., Microsoft PowerPoint) to create slides to communicate their analysis obtained using computational notebooks. Much tedious and repetitive work is needed to transfer the routines of notebooks (e.g., code, plots) to the presentable contents on slides (e.g., bullet points, figures). We propose a human-AI collaborative approach and operationalize it within Slide4N, an interactive AI assistant for data scientists to create slides from computational notebooks. Slide4N leverages advanced natural language processing techniques to distill key information from user-selected notebook cells and then renders them in appropriate slide layouts. The tool also provides intuitive interactions that allow further refinement and customization of the generated slides. We evaluated Slide4N with a two-part user study, where participants appreciated this human-AI collaborative approach compared to fully-manual or fully-automatic methods. The results also indicate the usefulness and effectiveness of Slide4N in slide creation tasks from notebooks.2023FWFengjie Wang et al.Sichuan UniversityGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationCHI
Community-Driven Information Accessibility: Online Sign Language Content Creation within d/Deaf CommunitiesInformation access is one of the most significant challenges faced by d/Deaf signers due to a lack of sign language information. As machine-driven solutions face challenges, we seek to understand how d/Deaf communities can create, share, and support the growth of sign language content. Based on interviews with 12 d/Deaf people in China, we found that d/Deaf videos, i.e., sign language videos created by and for d/Deaf people, can be crucial information sources and educational materials. Combining a content analysis of 360 d/Deaf videos, we reveal how d/Deaf communities co-create information accessibility through collaboration in online content creation. We uncover two major challenges that creators encounter, i.e., difficulties in translation and inconsistent content qualities. We propose potential opportunities and future research directions to support d/Deaf people's needs for sign language information through collaboration within d/Deaf communities.2023XTShiliang Tang et al.University of California, IrvineDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)Augmentative & Alternative Communication (AAC)Universal & Inclusive DesignCHI