6 papers
DeltaV: Thinking with Visual State Updates in Unified Large Multimodal Models
Pengjie Wang, Linger Deng, Zujia Zhang +6
Current Unified Large Multimodal Models (ULMMs) support interleaved multimodal reasoning through textual reasoning and intermediate visual states, but typically generate each visua…
PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling
Xudong Xie, Hao Yan, Liang Yin +6
Multimodal document understanding is a challenging task to process and comprehend large amounts of textual and visual information. Recent advances in Large Language Models (LLMs) h…
GeoFocus: Blending Efficient Global-to-Local Perception for Multimodal Geometry Problem-Solving
Linger Deng, Yuliang Liu, Wenwen Yu +4
Geometry problem-solving remains a significant challenge for Large Multimodal Models (LMMs), requiring not only global shape recognition but also attention to intricate local relat…
MSTAR: Box-free Multi-query Scene Text Retrieval with Attention Recycling
Liang Yin, Xudong Xie, Zhang Li +2
Scene text retrieval has made significant progress with the assistance of accurate text localization. However, existing approaches typically require costly bounding box annotations…
TokBench: Evaluating Your Visual Tokenizer before Visual Generation
Junfeng Wu, Dongliang Luo, Weizhi Zhao +6
In this work, we reveal the limitations of visual tokenizers and VAEs in preserving fine-grained features, and propose a benchmark to evaluate reconstruction performance for two ch…
SemiETS: Integrating Spatial and Content Consistencies for Semi-Supervised End-to-end Text Spotting
Dongliang Luo, Hanshen Zhu, Ziyang Zhang +4
Most previous scene text spotting methods rely on high-quality manual annotations to achieve promising performance. To reduce their expensive costs, we study semi-supervised text s…