82 citations · 98 across the 7 of their papers we have counts for
9 papers
BlenderWorld: Benchmarking Visual Agents for 3D Creation from Real-World References
Xinyu Fang, Yuchi Wang, Weihao Yu +12
Recent advances in multimodal large language models (MLLMs) have enabled them to act as autonomous agents, creating and editing 3D models via code or direct software manipulation.…
Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving
Xin Zhou, Zongchuang Zhao, Zhibo Yang +13
We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of the pretrained vision-langu…
Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis
Zhipeng Xu, Zulong Chen, Qing Liu +6
Key Information Extraction (KIE) converts visually rich documents into structured data, but practical deployment remains challenging: strong performance often relies on costly on-s…
Multi-domain Multi-modal Document Classification Benchmark with a Multi-level Taxonomy
Denghao Ma, Qing Liu, Zulong Chen +5
Document classification forms the backbone of modern enterprise content management, yet existing benchmarks remain trapped in oversimplified paradigms -- single domain settings wit…
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
Qwen2.5-VL Technical Report
Shuai Bai, Keqin Chen, Xuejing Liu +24
We introduce Qwen2.5-VL, the latest flagship model of Qwen vision-language series, which demonstrates significant advancements in both foundational capabilities and innovative func…
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy
Zhibo Yang, Jun Tang, Zhaohai Li +9
Large Multimodal Models (LMMs) have demonstrated impressive performance in recognizing document images with natural language instructions. However, it remains unclear to what exten…
VL-Reader: Vision and Language Reconstructor is an Effective Scene Text Recognizer
Humen Zhong, Zhibo Yang, Zhaohai Li +4
Text recognition is an inherent integration of vision and language, encompassing the visual texture in stroke patterns and the semantic context among the character sequences. Towar…
Platypus: A Generalized Specialist Model for Reading Text in Various Forms
Peng Wang, Zhaohai Li, Jun Tang +4
Reading text from images (either natural scenes or documents) has been a long-standing research topic for decades, due to the high technical challenge and wide application range. P…