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

107 citations · 140 across the 16 of their papers we have counts for

collaborators

18 papers

cs.HC2026

DashAct: A Progressive Diagnostic Benchmark for GUI Agents in Interactive Dashboard Analysis

Chuhan Zhang, Qi Xie, Ziyue Wang +4

Interactive dashboards require users to reveal and connect evidence across stateful interactions. Although graphical user interface (GUI) agents could automate this process, existi…

cs.AI2026

BIRD-History: A Benchmark for History-Driven Text-to-SQL with Fine-Grained Knowledge Annotations

Yunfan Zhou, Qiming Shi, Yizhou Yang +2

While recent Large Language Model (LLM)-based text-to-SQL systems achieve impressive performance on standard benchmarks, they struggle when user queries implicitly rely on domain-s…

cs.HC2026

AdaLens: Interactive Storyline for Monitoring and Steering Long-Running Agentic Data Analysis

Yangtian Liu, Yan Miao, Shuhan Liu +4

Large language models are pushing data science toward increasingly autonomous and agentic workflows, with recent systems already supporting multi-step and long-running analyses. As…

cs.HC2026★ 1 cited

Making Multimodal LLMs Reliable Chart Data Extractors: A Benchmark and Training Framework

Yuchen He, Peizhi Ying, Liqi Cheng +4

Chart data extraction, which reverse-engineers data tables from chart images, is essential for reproducibility, analysis, retrieval, and redesign. Existing interactive tools are re…

cs.AI2026

Crystalis: Progressive Nucleation and Semantic Annealing for Coordinated Multi-View Visualization Generation

Dazhen Deng, Zhaoping He, Xin Qian +3

Large language models (LLMs) can generate individual charts, but coordinated multi-view visualizations (CMVs), where views share data flows and cross-view interactions, remain out…

cs.CL2026

ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL

Zhaorui Yang, Huawei Zheng, Sen Yang +14

Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world databases often contain large…

cs.HC2026

GraphTide: Augmenting Knowledge-Intensive Text with Progressive Nested Graph

Xin Qian, Dazhen Deng, Zhaoping He +3

Knowledge-intensive text usually contains fruitful entities and complex relationships, such as academic articles and scientific exposition. Reading and comprehending such texts oft…

cs.HC2026

KEditVis: A Visual Analytics System for Knowledge Editing of Large Language Models

Zhenning Chen, Hanbei Zhan, Yanwei Huang +4

Large Language Models (LLMs) demonstrate exceptional capabilities in factual question answering, yet they sometimes provide incorrect responses. To address this issue, knowledge ed…

cs.HC2026

Cerebra: Aligning Implicit Knowledge in Interactive SQL Authoring

Yunfan Zhou, Qiming Shi, Zhongsu Luo +5

LLM-driven tools have significantly lowered barriers to writing SQL queries. However, user instructions are often underspecified, assuming the model understands implicit knowledge,…

cs.AI2026

Do LLM-Driven Agents Exhibit Engagement Mechanisms? Controlled Tests of Information Load, Descriptive Norms, and Popularity Cues

Tai-Quan Peng, Yuan Tian, Songsong Liang +2

Large language models make agent-based simulation more behaviorally expressive, but they also sharpen a basic methodological tension: fluent, human-like output is not, by itself, e…

cs.CL2025

CycleChart: A Unified Consistency-Based Learning Framework for Bidirectional Chart Understanding and Generation

Dazhen Deng, Sen Yang, Yuchen He +2

Current chart-related tasks, such as chart generation (NL2Chart), chart schema parsing, chart data parsing, and chart question answering (ChartQA), are typically studied in isolati…

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.HC2025★ 1 cited

NoteFlow: Leveraging Charts as Sight Glasses for Consistent and Continuous Data Flow Tracing

Yuan Tian, Dazhen Deng, Sen Yang +5

Computational notebooks offer a flexible environment for exploratory data analysis (EDA), but this flexibility often leads to disorganized and iterative execution of notebook cells…

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…

cs.HC2023★ 19 cited

Reviving Static Charts into Live Charts

Lu Ying, Yun Wang, Haotian Li +5

Data charts are prevalent across various fields due to their efficacy in conveying complex data relationships. However, static charts may sometimes struggle to engage readers and e…