人机交互
Deep Neural Networks (DNNs) are often considered black boxes due to their opaque decision-making processes. To reduce their opacity Concept Models (CMs), such as Concept Bottleneck Models (CBMs), were introduced to predict human-defined…
Large Language Model (LLM)-based conversational agents offer promising solutions for mental health support, but lack cultural responsiveness for diverse populations. This study evaluated the effectiveness of cultural prompting in improving…
Reducing wealth inequality and resource waste is a global challenge. A fundamental problem within the capitalist economy, put simply, lies in the enslavement of labor and the colonization of resources. To address these issues, movements…
This paper presents a web-based JavaScript editor designed to help children aged 8-10 transition from block-based to text-based programming. The system introduces a simplified domain-specific language (DSL) focused on visual art, combining…
The creative potential of computers has intrigued researchers for decades. Since the emergence of Generative AI (Gen AI), computer creativity has found many new dimensions and applications. As Gen AI permeates mainstream discourse and…
In the Virtual Reality (VR) gaming industry, maintaining immersion during real-world interruptions remains a challenge, particularly during transitions along the reality-virtuality continuum (RVC). Existing methods tend to rely on digital…
People today are overwhelmed by massive amounts of information, leading to cognitive overload and memory burden. Traditional visual memory augmentation methods are either effortful and disruptive or fail to align with user intent. To…
Amid the growing prevalence of human-AI interaction, large language models and other AI-based entities increasingly provide forms of companionship to human users. Such AI companionship -- i.e., bonded relationships between humans and AI…
Reinforcement Learning from Human Feedback (RLHF) relies on preference modeling to align machine learning systems with human values, yet the popular approach of random pair sampling with Bradley-Terry modeling is statistically limited and…
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Interaction (NLI) for visual analytics in immersive environments,…
As video games continue to evolve, understanding what drives player enjoyment remains a key challenge. Player reviews provide valuable insights, but their unstructured nature makes large-scale analysis difficult. This study applies…
Human cognitive biases in software engineering can lead to costly errors. While general-purpose AI (GPAI) systems may help mitigate these biases due to their non-human nature, their training on human-generated data raises a critical…
Executable QR codes, or sQRy, is a technology dated 2022 that permits to include a runnable program inside a QR code, enabling interaction with the user even in the absence of an Internet connection. sQRy are enablers for different…
Standardized surveys scale efficiently but sacrifice depth, while conversational interviews improve response quality at the cost of scalability and consistency. This study bridges the gap between these methods by introducing a framework for…
Visual storytelling combines visuals and narratives to communicate important insights. While web-based visual storytelling is well-established, leveraging the next generation of digital technologies for visual storytelling, specifically…
Conventional methods for diagnosing Social Anxiety Disorder (SAD), such as clinical interviews and self-reported questionnaires, often face accessibility barriers and subjective biases, underscoring the need for objective physiological…
EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative spatiotemporal features from electroencephalogram (EEG) signals. Existing studies often…
There is a growing interest in designing tools to support interactivity specification and authoring in data visualization. To develop expressive and flexible tools, we need theories and models that describe the task space of interaction…
Human-swarm interaction (HSI) is an active research challenge in the realms of swarm robotics and human-factors engineering. Here we apply a cognitive systems engineering perspective and introduce a neuro-inspired joint systems theory of…
Novice and expert users have different systematic preferences in task-oriented dialogues. However, whether catering to these preferences actually improves user experience and task performance remains understudied. To investigate the effects…