A Deep User Interface for Exploring LLaMa
This work addresses the problem of improving user interactions with LLMs for researchers and practitioners, though it is incremental as it builds on existing visual analytics approaches.
The paper tackles the challenge of understanding large language models by developing a visual analytics tool with interactive controls for hyperparameters like top-p and frequency penalty, which received favorable feedback in a user study for its design and ease of navigation.
The growing popularity and widespread adoption of large language models (LLMs) necessitates the development of tools that enhance the effectiveness of user interactions with these models. Understanding the structures and functions of these models poses a significant challenge for users. Visual analytics-driven tools enables users to explore and compare, facilitating better decision-making. This paper presents a visual analytics-driven tool equipped with interactive controls for key hyperparameters, including top-p, frequency and presence penalty, enabling users to explore, examine and compare the outputs of LLMs. In a user study, we assessed the tool's effectiveness, which received favorable feedback for its visual design, with particular commendation for the interface layout and ease of navigation. Additionally, the feedback provided valuable insights for enhancing the effectiveness of Human-LLM interaction tools.