[2603.00155] EfficientPosterGen: Semantic-aware Efficient Poster Generation via Token Compression and Accurate Violation Detection

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.00155 (cs) [Submitted on 25 Feb 2026] Title:EfficientPosterGen: Semantic-aware Efficient Poster Generation via Token Compression and Accurate Violation Detection Authors:Wenxin Tang, Jingyu Xiao, Yanpei Gong, Fengyuan Ran, Tongchuan Xia, Junliang Liu, Man Ho Lam, Wenxuan Wang, Michael R. Lyu View a PDF of the paper titled EfficientPosterGen: Semantic-aware Efficient Poster Generation via Token Compression and Accurate Violation Detection, by Wenxin Tang and 7 other authors View PDF Abstract:Automated academic poster generation aims to distill lengthy research papers into concise, visually coherent presentations. Existing Multimodal Large Language Models (MLLMs) based approaches, however, suffer from three critical limitations: low information density in full-paper inputs, excessive token consumption, and unreliable layout verification. We present EfficientPosterGen, an end-to-end framework that addresses these challenges through semantic-aware retrieval and token-efficient multimodal generation. EfficientPosterGen introduces three core innovations: (1) Semantic-aware Key Information Retrieval (SKIR), which constructs a semantic contribution graph to model inter-segment relationships and selectively preserves important content; (2) Visual-based Context Compression (VCC), which renders selected text segments into images to shift textual information into the visual modality, significantly reducing token usa...