13 citations · 30 across the 23 of their papers we have counts for
10 papers · 1 filter
VLM-R: Region Recognition, Reasoning, and Refinement for Enhanced Multimodal Chain-of-Thought
Chaoya Jiang, Yongrui Heng, Wei Ye +6
Recently, reasoning-based MLLMs have achieved a degree of success in generating long-form textual reasoning chains. However, they still struggle with complex tasks that necessitate…
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Haowei Liu, Xi Zhang, Haiyang Xu +8
In the field of MLLM-based GUI agents, compared to smartphones, the PC scenario not only features a more complex interactive environment, but also involves more intricate intra- an…
SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization
Hongrui Jia, Chaoya Jiang, Haiyang Xu +6
As language models continue to scale, Large Language Models (LLMs) have exhibited emerging capabilities in In-Context Learning (ICL), enabling them to solve language tasks by prefi…
mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding
Anwen Hu, Haiyang Xu, Liang Zhang +6
Multimodel Large Language Models(MLLMs) have achieved promising OCR-free Document Understanding performance by increasing the supported resolution of document images. However, this…
mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models
Jiabo Ye, Haiyang Xu, Haowei Liu +6
Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in executing instructions for a variety of single-image tasks. Despite this progress, significan…
MIBench: Evaluating Multimodal Large Language Models over Multiple Images
Haowei Liu, Xi Zhang, Haiyang Xu +8
Built on the power of LLMs, numerous multimodal large language models (MLLMs) have recently achieved remarkable performance on various vision-language tasks. However, most existing…
TinyChart: Efficient Chart Understanding with Visual Token Merging and Program-of-Thoughts Learning
Liang Zhang, Anwen Hu, Haiyang Xu +5
Charts are important for presenting and explaining complex data relationships. Recently, multimodal large language models (MLLMs) have shown remarkable capabilities in various char…
mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding
Anwen Hu, Haiyang Xu, Jiabo Ye +8
Structure information is critical for understanding the semantics of text-rich images, such as documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for…
Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training
Haowei Liu, Yaya Shi, Haiyang Xu +8
In vision-language pre-training (VLP), masked image modeling (MIM) has recently been introduced for fine-grained cross-modal alignment. However, in most existing methods, the recon…
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval
Haowei Liu, Yaya Shi, Haiyang Xu +8
In video-text retrieval, most existing methods adopt the dual-encoder architecture for fast retrieval, which employs two individual encoders to extract global latent representation…