AIJan 8

APEX: Academic Poster Editing Agentic Expert

arXiv:2601.04794v1h-index: 7Has Code
Originality Incremental advance
AI Analysis

This addresses the need for interactive and user-aligned poster editing tools for researchers, though it is incremental as it builds on existing automation methods.

The authors tackled the problem of labor-intensive academic poster design by proposing APEX, an interactive agentic framework for fine-grained editing, which significantly outperforms baseline methods in experiments.

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 (Academic Poster Editing agentic eXpert), 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.

Foundations

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