Papers by Alex Jinpeng Wang
From Charts to Code: A Hierarchical Benchmark for Multimodal Models (2026.acl-long)
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Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu, Zijian Zhang, Yifei Tao, Dongxing Mao, Yang Wan, Jingru Tan, Min Zeng, Min Li, Alex Jinpeng Wang
| Challenge: | Chart2Code is a new benchmark for evaluating the natural language to chart code generation capabilities of large multimodal models. |
| Approach: | They introduce Chart2Code, a new benchmark for evaluating the natural language to chart code generation capabilities of large multimodal models. |
| Outcome: | The proposed benchmark is the first to scale task complexity while capturing diverse scenarios. |
V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models (2026.findings-acl)
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Xiangxi Zheng, Linjie Li, Zhengyuan Yang, Ping Yu, Alex Jinpeng Wang, Rui Yan, Yuan Yao, Lijuan Wang
| Challenge: | Existing static image-text benchmarks are insufficient for evaluating multimodal large language models’ dynamic perception and interactive reasoning abilities. |
| Approach: | They propose a game-based evaluation framework to assess multimodal large language models’ visual reasoning in dynamic, continuous-space environments. |
| Outcome: | The proposed framework systematically assesses MLLMs’ visual reasoning in dynamic, continuous-space environments. |
CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution (2026.acl-long)
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Xiangxi Zheng, Kuang He, Jiayi Hu, Ping Yu, Rui Yan, Yuan Yao, Peng Hou, Anxiang Zeng, Alex Jinpeng Wang
| Challenge: | Existing approaches to chart-to-code generation are constrained by data-centric limitations . authors present a new framework that redesigns both training and alignment data . |
| Approach: | They propose a data-centric framework that redesigns both training and alignment data for chart-to-code generation. |
| Outcome: | The proposed framework outperforms open-source baselines and is competitive with GPT-5. |