21 citations · 36 across the 5 of their papers we have counts for
8 papers
Seeing is Improving: Visual Feedback for Iterative Text Layout Refinement
Junrong Guo, Shancheng Fang, Yadong Qu +1
Recent advances in Multimodal Large Language Models (MLLMs) have enabled automated generation of structured layouts from natural language descriptions. Existing methods typically f…
FineRef: Fine-Grained Error Reflection and Correction for Long-Form Generation with Citations
Yixing Peng, Licheng Zhang, Shancheng Fang +3
Generating with citations is crucial for trustworthy Large Language Models (LLMs), yet even advanced LLMs often produce mismatched or irrelevant citations. Existing methods over-op…
IGD: Instructional Graphic Design with Multimodal Layer Generation
Yadong Qu, Shancheng Fang, Yuxin Wang +4
Graphic design visually conveys information and data by creating and combining text, images and graphics. Two-stage methods that rely primarily on layout generation lack creativity…
MaskDiT: Dual Mask-based Diffusion Transformer for Multi-Scene Long Video Generation
Tianhao Qi, Jianlong Yuan, Wanquan Feng +6
Sora has unveiled the immense potential of the Diffusion Transformer (DiT) architecture in single-scene video generation. However, the more challenging task of multi-scene video ge…
GRIP: A Graph-Based Reasoning Instruction Producer
Jiankang Wang, Jianjun Xu, Xiaorui Wang +4
Large-scale, high-quality data is essential for advancing the reasoning capabilities of large language models (LLMs). As publicly available Internet data becomes increasingly scarc…
From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network
Yuxin Wang, Hongtao Xie, Shancheng Fang +3
In this paper, we abandon the dominant complex language model and rethink the linguistic learning process in the scene text recognition. Different from previous methods considering…