YAC: Bridging Natural Language and Interactive Visual Exploration with Generative AI for Biomedical Data Discovery
Incorporating natural language input has the potential to improve the capabilities of biomedical data discovery interfaces. However, user interface elements and visualizations are still powerful tools for interacting with data. In our prototype system, YAC, Yet Another Chatbot, we integrate natural language and interactive visualizations. YAC uses a tool-calling multi-agent system to generate declarative output, which is interpreted to render linked interactive visualizations and apply data filters. We also include adjustment widgets, which allow users to directly modify the structured output. Structured text is also generated to clarify user intent, notify users of system boundaries, and explain aspects of the data with live data element links. We conducted a user study with domain experts to surface areas where YAC can be improved. Furthermore we reflect on the capabilities and design of this system with an analysis of its technical dimensions.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Interactive Narrative Analytics: Bridging Computational Narrative Extraction and Human Sensemaking
Information overload and misinformation create significant challenges in extracting meaningful narratives from large news collections. This paper defines the nascent field of Interactive Narrative Analytics (INA), which …
Bridging Natural Language and Interactive What-If Interfaces via LLM-Generated Declarative Specification
What-if analysis (WIA) is an iterative, multi-step process where users explore and compare hypothetical scenarios by adjusting parameters, applying constraints, and scoping data through interactive interfaces. Current to…
NOVAID: Natural-language Observability Visualization Assistant for ITOps Dashboard Widget Generation
Manual creation of IT monitoring dashboard widgets is slow, error-prone, and a barrier for both novice and expert users. We present NOVAID, an interactive chatbot that leverages Large Language Models (LLMs) to generate I…
Natural Language QueriesIntelliProof: An Argumentation Network-based Conversational Helper for Organized Reflection
We present IntelliProof, an interactive system for analyzing argumentative essays through LLMs. IntelliProof structures an essay as an argumentation graph, where claims are represented as nodes, supporting evidence is at…
Automated Essay ScoringVizGenie: Toward Self-Refining, Domain-Aware Workflows for Next-Generation Scientific Visualization
We present VizGenie, a self-improving, agentic framework that advances scientific visualization through large language model (LLM) by orchestrating of a collection of domain-specific and dynamically generated modules. Us…
Visual Question Answering