Papers by Fang Niu

2 papers
Adaptive Text2GQL: Integrating Structural Twig Linking and Evolutionary In-Context Learning (2026.acl-long)

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Challenge: Existing approaches struggle with structural hallucinations and lack adaptability in cold-start scenarios.
Approach: They propose a unified, training-free framework for translating natural language into Graph Query Languages.
Outcome: The proposed framework improves accuracy and executability over baselines in Graph2GQLs.
Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards (2026.acl-long)

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Challenge: Existing efforts to generate static visualizations focus on static charts and interactive dashboards.
Approach: They propose a dashboard2code task that requires a model to explore an interactive dashboard, acquire feedback from its own interactions and generate code that reproduces the target dashboard.
Outcome: The proposed task is based on 180 carefully designed and manually verified dashboard–code pairs spanning three difficulty levels and covering eight common real-world interaction patterns.

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