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

1 citations · 1 across the 2 of their papers we have counts for

collaborators

15 papers

cs.AI2026

DashArena: Benchmarking LLMs on Interactive Analytic Dashboard Generation

Xiaotong Wang, Dazhen Deng

Analytic dashboards combine coordinated views and interactions for data exploration and decision-making. Recent models can generate them from data and natural-language goals, but e…

cs.HC20261 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.CL2026

EviLink: Multi-Path Schema Linking with Uncertainty-Guided Evidence Acquisition for Large-Scale Text-to-SQL

Huawei Zheng, Sen Yang, Zhaorui Yang +12

Schema linking is a difficult and important step in large-scale Text-to-SQL, where systems must identify a compact yet sufficient schema context from large and ambiguous databases.…

cs.CL2026

StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation

Huawei Zheng, Xinqi Jiang, Sen Yang +3

Large language models (LLMs) are increasingly applied in specialized domains such as finance and healthcare, where they introduce unique safety risks. Domain-specific datasets of h…