168 citations · 346 across the 22 of their papers we have counts for
14 papers · 1 filter
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…
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…
Think-Program-reCtify: 3D Situated Reasoning with Large Language Models
Qingrong He, Kejun Lin, Shizhe Chen +2
This work addresses the 3D situated reasoning task which aims to answer questions given egocentric observations in a 3D environment. The task remains challenging as it requires com…
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…
UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model
Jiabo Ye, Anwen Hu, Haiyang Xu +11
Text is ubiquitous in our visual world, conveying crucial information, such as in documents, websites, and everyday photographs. In this work, we propose UReader, a first explorati…
Explore and Tell: Embodied Visual Captioning in 3D Environments
Anwen Hu, Shizhe Chen, Liang Zhang +1
While current visual captioning models have achieved impressive performance, they often assume that the image is well-captured and provides a complete view of the scene. In real-wo…
Movie101: A New Movie Understanding Benchmark
Zihao Yue, Qi Zhang, Anwen Hu +3
To help the visually impaired enjoy movies, automatic movie narrating systems are expected to narrate accurate, coherent, and role-aware plots when there are no speaking lines of a…
Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Dataset for Pre-training and Benchmarks
Haiyang Xu, Qinghao Ye, Xuan Wu +13
To promote the development of Vision-Language Pre-training (VLP) and multimodal Large Language Model (LLM) in the Chinese community, we firstly release the largest public Chinese h…
InfoMetIC: An Informative Metric for Reference-free Image Caption Evaluation
Anwen Hu, Shizhe Chen, Liang Zhang +1
Automatic image captioning evaluation is critical for benchmarking and promoting advances in image captioning research. Existing metrics only provide a single score to measure capt…
Accommodating Audio Modality in CLIP for Multimodal Processing
Ludan Ruan, Anwen Hu, Yuqing Song +3
Multimodal processing has attracted much attention lately especially with the success of pre-training. However, the exploration has mainly focused on vision-language pre-training,…
Question-controlled Text-aware Image Captioning
Anwen Hu, Shizhe Chen, Qin Jin
For an image with multiple scene texts, different people may be interested in different text information. Current text-aware image captioning models are not able to generate distin…
ICECAP: Information Concentrated Entity-aware Image Captioning
Anwen Hu, Shizhe Chen, Qin Jin
Most current image captioning systems focus on describing general image content, and lack background knowledge to deeply understand the image, such as exact named entities or concr…
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
Yuqi Huo, Manli Zhang, Guangzhen Liu +32
Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…