107 citations · 140 across the 16 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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,…
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…