Multimodal scene search of conversations is essential for unlocking valuable insights into social dynamics and enhancing our communication. While experts in conversational analysis have their own knowledge and skills to find key scenes, a lack of ...

Querying structured databases with natural language (NL2SQL) has remained a difficult problem for years. Recently, the advancement of machine learning (ML), natural language processing (NLP), and large language models (LLM) have led to significant ...

Storytelling is an integral part of human culture and significantly impacts cognitive and socio-emotional development and connection. Despite the importance of interactive visual storytelling, the process of creating such content requires specialized ...

This article aims to develop a semi-formal representation for Human-AI (HAI) interactions, by building a set of interaction primitives which can specify the information exchanges between users and AI systems during their interaction. We show how these ...

Computational methods can potentially facilitate user interface design by complementing designer intuition, prior experience, and personal preference. Framing a user interface design task as a multi-objective optimization problem can help with ...

We introduce a spatial constraint model to characterize the positioning and interactions in visualizations, thereby facilitating the activation of static visualizations. Our model provides users with the capability to manipulate visualizations through ...

Whereas most research in AI system explanation for healthcare applications looks at developing algorithmic explanations targeted at AI experts or medical professionals, the question we raise is: How do we build meaningful explanations for laypeople? And ...

eXplainable AI (XAI) involves two intertwined but separate challenges: the development of techniques to extract explanations from black-box AI models and the way such explanations are presented to users, i.e., the explanation user interface. Despite its ...

When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and guide their exploration into the unknown. ...

The emergence of the micro-moment concept highlights the influence of context; recommender system design should reflect this trend. In response to different contexts, a micro-moment recommender system (MMRS) requires an effective interaction mechanism ...

Online research is a frequent and important activity people perform on the Internet, yet current support for this task is basic, fragmented and not well integrated into web browser experiences. Guided by sensemaking theory, we present ForSense, a browser ...

Conversational agents (CAs) are increasingly ubiquitous and are now commonly used to access medical information. However, we lack systematic data about the quality of advice such agents provide. This paper evaluates CA advice for mental health (MH) ...

A key objective in the design of graphical user interfaces (GUIs) is to ensure consistency across screens of the same product. However, designing a compliant layout is time-consuming and can distract designers from creative thinking. This paper studies ...

Our research aims to develop intelligent collaborative agents that are human-aware: They can model, learn, and reason about their human partner’s physiological, cognitive, and affective states. In this article, we study how adaptive coaching interactions ...

Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this article, we focus on coaching sedentary, overweight individuals (i.e., “trainees”) to exercise regularly. We employ adaptive ...

In domains where users are exposed to large variations in visuo-spatial features among designs, they often spend excess time searching for common elements (features) on an interface. This article contributes individualised predictive models of visual ...

Document clustering is a necessary step in various analytical and automated activities. When guided by the user, algorithms are tailored to imprint a perspective on the clustering process that reflects the user’s understanding of the dataset. More than ...

Graphical Adaptive Menus are Graphical User Interface menus whose predicted items of immediate use can be automatically rendered in a prediction window. Rendering this prediction window is a key question for adaptivity to enable the end-user to ...

Deep learning has emerged as a powerful tool for feature-driven labeling of datasets. However, for it to be effective, it requires a large and finely labeled training dataset. Precisely labeling a large training dataset is expensive, time-consuming, and ...

Technologies for sensing movement are expanding toward everyday use in virtual reality, gaming, and artistic practices. In this context, there is a need for methodologies to help designers and users create meaningful movement experiences. This article ...