activity
20242026
most citedLinVT: Empower Your Image-level Large Language Model to Understand Videos

1 citations · 1 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2026

AIR: Adaptive Interleaved Reasoning with Code in MLLMs

Cong Han, Xiaohan Lan, Haibo Qiu +1

Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a pivotal research frontier. The…

cs.CV2025

Advancing Visual Large Language Model for Multi-granular Versatile Perception

Wentao Xiang, Haoxian Tan, Cong Wei +3

Perception is a fundamental task in the field of computer vision, encompassing a diverse set of subtasks that can be systematically categorized into four distinct groups based on t…

cs.CL2025

Optimizing Singular Spectrum for Large Language Model Compression

Dengjie Li, Tiancheng Shen, Yao Zhou +7

Large language models (LLMs) have demonstrated remarkable capabilities, yet prohibitive parameter complexity often hinders their deployment. Existing singular value decomposition (…

cs.CV2025

HiMix: Reducing Computational Complexity in Large Vision-Language Models

Xuange Zhang, Dengjie Li, Bo Liu +7

Benefiting from recent advancements in large language models and modality alignment techniques, existing Large Vision-Language Models(LVLMs) have achieved prominent performance acr…

cs.CV2024

Manga Generation via Layout-controllable Diffusion

Siyu Chen, Dengjie Li, Zenghao Bao +4

Generating comics through text is widely studied. However, there are few studies on generating multi-panel Manga (Japanese comics) solely based on plain text. Japanese manga contai…

cs.CV2024

CharGen: High Accurate Character-Level Visual Text Generation Model with MultiModal Encoder

Lichen Ma, Tiezhu Yue, Pei Fu +4

Recently, significant advancements have been made in diffusion-based visual text generation models. Although the effectiveness of these methods in visual text rendering is rapidly…