Papers by Jianke Zhang

2 papers
RealChart2Code: Bridging the Gap in Real-World Chart-to-Code Generation via Multi-Task Evaluation (2026.acl-long)

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Challenge: Vision-Language Models (VLMs) have demonstrated impressive capabilities in code generation across various domains, but their ability to replicate complex, multi-panel visualizations remains largely unassessed.
Approach: They propose a large-scale benchmark to evaluate chart generation from large- scale raw data and assess iterative code refinement in a multi-turn conversational setting.
Outcome: The new benchmark evaluates 14 leading VLMs on real-world data and shows they struggle with complex plot structures and authentic data.
DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Models (2025.naacl-long)

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Challenge: Multimodal Large Language Models (MLLMs) pose unique safety challenges due to their integration of visual and textual data.
Approach: They propose a method to disentangle risks through step-by-step reasoning within multimodal inputs.
Outcome: The proposed approach improves safety alignment in MLLMs by fine-tuning and iterative Reinforcement Learning from AI feedback.

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