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20232025
most citedM3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

18 citations · 53 across the 9 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024★ 2 cited

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…

cs.CV2024

Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding

Yan Shu, Zheng Liu, Peitian Zhang +5

Long video understanding poses a significant challenge for current Multi-modal Large Language Models (MLLMs). Notably, the MLLMs are constrained by their limited context lengths an…

cs.CV2024★ 1 cited

OmniGen: Unified Image Generation

Shitao Xiao, Yueze Wang, Junjie Zhou +7

The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unifi…

cs.CV2024★ 4 cited

MLVU: Benchmarking Multi-task Long Video Understanding

Junjie Zhou, Yan Shu, Bo Zhao +9

The evaluation of Long Video Understanding (LVU) performance poses an important but challenging research problem. Despite previous efforts, the existing video understanding benchma…

cs.CV2024★ 18 cited

M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

Fan Bai, Yuxin Du, Tiejun Huang +2

Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly supported by multi-modal large language models (MLLMs). However, previous research ha…

cs.CV2024

Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability

Xuelin Qian, Yu Wang, Simian Luo +9

Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…

cs.CV2024★ 13 cited

Efficient Multimodal Learning from Data-centric Perspective

Muyang He, Yexin Liu, Boya Wu +4

Multimodal Large Language Models (MLLMs) have demonstrated notable capabilities in general visual understanding and reasoning tasks. However, their deployment is hindered by substa…