12 citations · 33 across the 15 of their papers we have counts for
16 papers
ThinkOmni: Lifting Textual Reasoning to Omni-modal Scenarios via Guidance Decoding
Yiran Guan, Sifan Tu, Dingkang Liang +6
Omni-modal reasoning is essential for intelligent systems to understand and draw inferences from diverse data sources. While existing omni-modal large language models (OLLM) excel…
The Trinity of Consistency as a Defining Principle for General World Models
Jingxuan Wei, Siyuan Li, Yuhang Xu +21
The construction of World Models capable of learning, simulating, and reasoning about objective physical laws constitutes a foundational challenge in the pursuit of Artificial Gene…
TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Rendering
Hanshen Zhu, Yuliang Liu, Xuecheng Wu +7
Visual Text Rendering (VTR) remains a critical challenge in text-to-image generation, where even advanced models frequently produce text with structural anomalies such as distortio…
OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning
Ling Fu, Zhebin Kuang, Jiajun Song +21
Scoring the Optical Character Recognition (OCR) capabilities of Large Multimodal Models (LMMs) has witnessed growing interest. Existing benchmarks have highlighted the impressive p…
MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark
Bin Shan, Xiang Fei, Wei Shi +6
The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchma…
Theorem-Validated Reverse Chain-of-Thought Problem Generation for Geometric Reasoning
Linger Deng, Linghao Zhu, Yuliang Liu +6
Large Multimodal Models (LMMs) face limitations in geometric reasoning due to insufficient Chain of Thought (CoT) image-text training data. While existing approaches leverage templ…
Dataset and Benchmark for Urdu Natural Scenes Text Detection, Recognition and Visual Question Answering
Hiba Maryam, Ling Fu, Jiajun Song +4
The development of Urdu scene text detection, recognition, and Visual Question Answering (VQA) technologies is crucial for advancing accessibility, information retrieval, and lingu…
The First Swahili Language Scene Text Detection and Recognition Dataset
Fadila Wendigoundi Douamba, Jianjun Song, Ling Fu +2
Scene text recognition is essential in many applications, including automated translation, information retrieval, driving assistance, and enhancing accessibility for individuals wi…
Exploring the Capabilities of Large Multimodal Models on Dense Text
Shuo Zhang, Biao Yang, Zhang Li +3
While large multi-modal models (LMM) have shown notable progress in multi-modal tasks, their capabilities in tasks involving dense textual content remains to be fully explored. Den…
MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering
Jingqun Tang, Qi Liu, Yongjie Ye +14
Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de fac…
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Jingqun Tang, Chunhui Lin, Zhen Zhao +15
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of lea…
SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
Zijie Wu, Chaohui Yu, Yanqin Jiang +3
Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video. Existing approaches utilize score distillation sampling to form the…
TextMonkey: An OCR-Free Large Multimodal Model for Understanding Document
Yuliang Liu, Biao Yang, Qiang Liu +4
We present TextMonkey, a large multimodal model (LMM) tailored for text-centric tasks. Our approach introduces enhancement across several dimensions: By adopting Shifted Window Att…
Enhancing Scene Text Detectors with Realistic Text Image Synthesis Using Diffusion Models
Ling Fu, Zijie Wu, Yingying Zhu +2
Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obta…
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models
Zhang Li, Biao Yang, Qiang Liu +6
Large Multimodal Models (LMMs) have shown promise in vision-language tasks but struggle with high-resolution input and detailed scene understanding. Addressing these challenges, we…
SingleInsert: Inserting New Concepts from a Single Image into Text-to-Image Models for Flexible Editing
Zijie Wu, Chaohui Yu, Zhen Zhu +2
Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I mo…