Qinnan Cai
Author directory2026
APEX: Academic Poster Editing Agentic Expert
Chengxin Shi | Qinnan Cai | Zeyuan Chen | Long Zeng | Yibo Zhao | Jing Yu | Jianxiang Yu | Xiang Li
Findings of the Association for Computational Linguistics: EMNLP 2026
Chengxin Shi | Qinnan Cai | Zeyuan Chen | Long Zeng | Yibo Zhao | Jing Yu | Jianxiang Yu | Xiang Li
Findings of the Association for Computational Linguistics: EMNLP 2026
Designing academic posters is a labor-intensive process requiring the precise balance of high-density content and sophisticated layout. While existing paper-to-poster generation methods automate initial drafting, they are typically single-pass and non-interactive, often fail to align with complex, subjective user intent. To bridge this gap, we propose APEX (**A**cademic **P**oster **E**diting agentic e**X**pert), the first agentic framework for interactive academic poster editing, supporting fine-grained control with robust multi-level API-based editing and a review-and-adjustment mechanism. In addition, we introduce APEX-Bench, the first systematic benchmark comprising 514 academic poster editing instructions, categorized by a multi-dimensional taxonomy including operation type, difficulty, and abstraction level, constructed via reference-guided and reference-free strategies to ensure realism and diversity. We further establish a multi-dimensional VLM-as-a-judge evaluation protocol to assess instruction fulfillment, modification scope, and visual consistency harmony. Experimental results demonstrate that APEX significantly outperforms baseline methods. Our implementation is available at https://github.com/Breesiu/APEX.