7 citations · 12 across the 18 of their papers we have counts for
12 papers · 1 filter
AeSlides: Incentivizing Aesthetic Layout in LLM-Based Slide Generation via Verifiable Rewards
Yiming Pan, Chengwei Hu, Xuancheng Huang +6
Large language models (LLMs) have demonstrated strong potential in agentic tasks, particularly in slide generation. However, slide generation poses a fundamental challenge: the gen…
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…
Dolphin-v2: Universal Document Parsing via Scalable Anchor Prompting
Hao Feng, Wei Shi, Ke Zhang +9
Document parsing has garnered widespread attention as vision-language models (VLMs) advance OCR capabilities. However, the field remains fragmented across dozens of specialized mod…
UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters
Yongkun Du, Zhineng Chen, Yazhen Xie +6
Text and formulas constitute the core informational components of many documents. Accurately and efficiently recognizing both is crucial for developing robust and generalizable doc…
Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting
Hao Feng, Shu Wei, Xiang Fei +10
Document image parsing is challenging due to its complexly intertwined elements such as text paragraphs, figures, formulas, and tables. Current approaches either assemble specializ…
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
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…
ParGo: Bridging Vision-Language with Partial and Global Views
An-Lan Wang, Bin Shan, Wei Shi +7
This work presents ParGo, a novel Partial-Global projector designed to connect the vision and language modalities for Multimodal Large Language Models (MLLMs). Unlike previous work…
Harmonizing Visual Text Comprehension and Generation
Zhen Zhao, Jingqun Tang, Binghong Wu +7
In this work, we present TextHarmony, a unified and versatile multimodal generative model proficient in comprehending and generating visual text. Simultaneously generating images a…
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
Weichao Zhao, Hao Feng, Qi Liu +9
Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-s…
Multi-modal In-Context Learning Makes an Ego-evolving Scene Text Recognizer
Zhen Zhao, Jingqun Tang, Chunhui Lin +6
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is…
DocPedia: Unleashing the Power of Large Multimodal Model in the Frequency Domain for Versatile Document Understanding
Hao Feng, Qi Liu, Hao Liu +4
This work presents DocPedia, a novel large multimodal model (LMM) for versatile OCR-free document understanding, capable of parsing images up to 2,5602,560 resolution. Unli…