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20232026
most citedChartGPT: Leveraging LLMs to Generate Charts from Abstract Natural Language

107 citations · 127 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.HC2025★ 3 cited

ReSpark: Leveraging Previous Data Reports as References to Generate New Reports with LLMs

Yuan Tian, Chuhan Zhang, Xiaotong Wang +5

Creating data reports is a labor-intensive task involving iterative data exploration, insight extraction, and narrative construction. A key challenge lies in composing the analysis…

cs.HC2024

RCInvestigator: Towards Better Investigation of Anomaly Root Causes in Cloud Computing Systems

Shuhan Liu, Yunfan Zhou, Lu Ying +9

Finding the root causes of anomalies in cloud computing systems quickly is crucial to ensure availability and efficiency since accurate root causes can guide engineers to take appr…

cs.HC2024★ 3 cited

Understanding Nonlinear Collaboration between Human and AI Agents: A Co-design Framework for Creative Design

Jiayi Zhou, Renzhong Li, Junxiu Tang +4

Creative design is a nonlinear process where designers generate diverse ideas in the pursuit of an open-ended goal and converge towards consensus through iterative remixing. In con…

cs.HC2023★ 107 cited

ChartGPT: Leveraging LLMs to Generate Charts from Abstract Natural Language

Yuan Tian, Weiwei Cui, Dazhen Deng +4

The use of natural language interfaces (NLIs) to create charts is becoming increasingly popular due to the intuitiveness of natural language interactions. One key challenge in this…

cs.HC2023★ 6 cited

Relation-driven Query of Multiple Time Series

Shuhan Liu, Yuan Tian, Zikun Deng +4

Querying time series based on their relations is a crucial part of multiple time series analysis. By retrieving and understanding time series relations, analysts can easily detect…