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20212026
most citedLarge Multimodal Agents: A Survey

12 citations · 42 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2026

EvoGraph-R1: Self-Evolving Multimodal Knowledge Hypergraphs for Agentic Retrieval

Jiashi Lin, Changhong Jiang, Xiangru Lin +12

Retrieval-augmented generation (RAG) has emerged as a critical paradigm for grounding Multimodal Large Language Models (MLLMs) in external knowledge. Recent GraphRAG methods introd…

cs.CV2025

VLDrive: Vision-Augmented Lightweight MLLMs for Efficient Language-grounded Autonomous Driving

Ruifei Zhang, Wei Zhang, Xiao Tan +4

Recent advancements in language-grounded autonomous driving have been significantly promoted by the sophisticated cognition and reasoning capabilities of large language models (LLM…

cs.CV2025

AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving

Ruifei Zhang, Junlin Xie, Wei Zhang +4

Effectively integrating Large Language Models (LLMs) into autonomous driving requires a balance between leveraging high-level reasoning and maintaining real-time efficiency. Existi…

cs.CV2025★ 1 cited

A Survey on Agentic Multimodal Large Language Models

Huanjin Yao, Ruifei Zhang, Jiaxing Huang +8

With the recent emergence of revolutionary autonomous agentic systems, research community is witnessing a significant shift from traditional static, passive, and domain-specific AI…

cs.CV2024★ 8 cited

HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale

Junying Chen, Chi Gui, Ruyi Ouyang +10

The rapid development of multimodal large language models (MLLMs), such as GPT-4V, has led to significant advancements. However, these models still face challenges in medical multi…

cs.CV2024★ 12 cited

Large Multimodal Agents: A Survey

Junlin Xie, Zhihong Chen, Ruifei Zhang +2

Large language models (LLMs) have achieved superior performance in powering text-based AI agents, endowing them with decision-making and reasoning abilities akin to humans. Concurr…

cs.CL2024★ 4 cited

ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Guiming Hardy Chen, Shunian Chen, Ruifei Zhang +7

Large vision-language models (LVLMs) have shown premise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they require…

cs.CV2023★ 1 cited

Advancing Visual Grounding with Scene Knowledge: Benchmark and Method

Zhihong Chen, Ruifei Zhang, Yibing Song +2

Visual grounding (VG) aims to establish fine-grained alignment between vision and language. Ideally, it can be a testbed for vision-and-language models to evaluate their understand…

eess.IV2023★ 1 cited

Lesion-aware Dynamic Kernel for Polyp Segmentation

Ruifei Zhang, Peiwen Lai, Xiang Wan +4

Automatic and accurate polyp segmentation plays an essential role in early colorectal cancer diagnosis. However, it has always been a challenging task due to 1) the diverse shape,…

cs.CV2023★ 2 cited

Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation

Ruifei Zhang, Sishuo Liu, Yizhou Yu +1

Biomedical image segmentation plays a significant role in computer-aided diagnosis. However, existing CNN based methods rely heavily on massive manual annotations, which are very e…

cs.CV2023★ 12 cited

Adaptive Context Selection for Polyp Segmentation

Ruifei Zhang, Guanbin Li, Zhen Li +3

Accurate polyp segmentation is of great significance for the diagnosis and treatment of colorectal cancer. However, it has always been very challenging due to the diverse shape and…

cs.CL2021★ 1 cited

FastSeq: Make Sequence Generation Faster

Yu Yan, Fei Hu, Jiusheng Chen +7

Transformer-based models have made tremendous impacts in natural language generation. However the inference speed is a bottleneck due to large model size and intensive computing in…