19 citations · 52 across the 16 of their papers we have counts for
17 papers
OmniCaptioner: One Captioner to Rule Them All
Yiting Lu, Jiakang Yuan, Zhen Li +17
We propose OmniCaptioner, a versatile visual captioning framework for generating fine-grained textual descriptions across a wide variety of visual domains. Unlike prior methods lim…
GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling
Siqi Li, Yufan Shen, Xiangnan Chen +13
The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application scenarios. This progress highlig…
InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
Jinguo Zhu, Weiyun Wang, Zhe Chen +48
We introduce InternVL3, a significant advancement in the InternVL series featuring a native multimodal pre-training paradigm. Rather than adapting a text-only large language model…
MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Fanqing Meng, Lingxiao Du, Zongkai Liu +12
DeepSeek R1, and o1 have demonstrated powerful reasoning capabilities in the text domain through stable large-scale reinforcement learning. To enable broader applications, some wor…
TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
Daocheng Fu, Jianlong Chen, Renqiu Xia +12
Geometric problem solving (GPS) requires precise multimodal understanding and rigorous, step-by-step logical reasoning. However, developing capable Multimodal Large Language Models…
GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training
Renqiu Xia, Mingsheng Li, Hancheng Ye +12
Despite their proficiency in general tasks, Multi-modal Large Language Models (MLLMs) struggle with automatic Geometry Problem Solving (GPS), which demands understanding diagrams,…
Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback
Jiakang Yuan, Xiangchao Yan, Shiyang Feng +7
The scientific research paradigm is undergoing a profound transformation owing to the development of Artificial Intelligence (AI). Recent works demonstrate that various AI-assisted…
OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations
Linke Ouyang, Yuan Qu, Hongbin Zhou +17
Document content extraction is a critical task in computer vision, underpinning the data needs of large language models (LLMs) and retrieval-augmented generation (RAG) systems. Des…
Chimera: Improving Generalist Model with Domain-Specific Experts
Tianshuo Peng, Mingsheng Li, Jiakang Yuan +11
Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks.…
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Zhe Chen, Weiyun Wang, Yue Cao +39
We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving
Tao Ma, Hongbin Zhou, Qiusheng Huang +7
Offboard perception aims to automatically generate high-quality 3D labels for autonomous driving (AD) scenes. Existing offboard methods focus on 3D object detection with closed-set…
Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy
Hancheng Ye, Jiakang Yuan, Renqiu Xia +5
Diffusion models have recently achieved great success in the synthesis of high-quality images and videos. However, the existing denoising techniques in diffusion models are commonl…
MinerU: An Open-Source Solution for Precise Document Content Extraction
Bin Wang, Chao Xu, Xiaomeng Zhao +15
Document content analysis has been a crucial research area in computer vision. Despite significant advancements in methods such as OCR, layout detection, and formula recognition, e…
DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models
Renqiu Xia, Song Mao, Xiangchao Yan +19
Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these docum…
UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition
Bin Wang, Zhuangcheng Gu, Guang Liang +4
The paper introduces the UniMER dataset, marking the first study on Mathematical Expression Recognition (MER) targeting complex real-world scenarios. The UniMER dataset includes a…
StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
Renqiu Xia, Haoyang Peng, Hancheng Ye +7
Charts are common in literature across various scientific fields, conveying rich information easily accessible to readers. Current chart-related tasks focus on either chart percept…
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations
Xiangchao Yan, Runjian Chen, Bo Zhang +11
Annotating 3D LiDAR point clouds for perception tasks is fundamental for many applications e.g., autonomous driving, yet it still remains notoriously labor-intensive. Pretraining-f…