ABSTRACT
Large language models (LLMs) have recently soared in popularity due to their ease of access and the unprecedented ability to synthesize text responses to diverse user questions. However, LLMs like ChatGPT present significant limitations in supporting complex information tasks due to the insufficient affordances of the text-based medium and linear conversational structure. Through a formative study with ten participants, we found that LLM interfaces often present long-winded responses, making it difficult for people to quickly comprehend and interact flexibly with various pieces of information, particularly during more complex tasks. We present Graphologue, an interactive system that converts text-based responses from LLMs into graphical diagrams to facilitate information-seeking and question-answering tasks. Graphologue employs novel prompting strategies and interface designs to extract entities and relationships from LLM responses and constructs node-link diagrams in real-time. Further, users can interact with the diagrams to flexibly adjust the graphical presentation and to submit context-specific prompts to obtain more information. Utilizing diagrams, Graphologue enables graphical, non-linear dialogues between humans and LLMs, facilitating information exploration, organization, and comprehension.
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Index Terms
- Graphologue: Exploring Large Language Model Responses with Interactive Diagrams
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CHI EA '24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing SystemsThe integration of Large Language Models (LLMs) with Conversational User Interfaces (CUIs) has significantly transformed health information seeking, offering interactive access to health resources. Despite the importance of trust in adopting health ...
Effective Non-visual Access to Diagrams via an Augmented Natural Language Interface
Computers Helping People with Special NeedsAbstractThis paper describes the design and validation of a number of HCI techniques that enable more effective non-visual access to diagrammatically displayed data through an adapted Natural Language Interface (NLI). These techniques have been ...
Towards seamless semantic zooming techniques for UML diagrams
SoftVis '08: Proceedings of the 4th ACM symposium on Software visualizationModels become increasingly important for software development processes. Though there is a multitude of software modeling tools available, the handling of complex UML diagrams is still difficult. In particular, the visualization of a global overview and ...
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