147 citations · 337 across the 23 of their papers we have counts for
7 papers · 1 filter
FlashSloth: Lightning Multimodal Large Language Models via Embedded Visual Compression
Bo Tong, Bokai Lai, Yiyi Zhou +5
Despite a big leap forward in capability, multimodal large language models (MLLMs) tend to behave like a sloth in practical use, i.e., slow response and large latency. Recent effor…
MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models
Yaxin Luo, Gen Luo, Jiayi Ji +4
Despite the significant progress in multimodal large language models (MLLMs), their high computational cost remains a barrier to real-world deployment. Inspired by the mixture of d…
3D-GRES: Generalized 3D Referring Expression Segmentation
Changli Wu, Yihang Liu, Jiayi Ji +6
3D Referring Expression Segmentation (3D-RES) is dedicated to segmenting a specific instance within a 3D space based on a natural language description. However, current approaches…
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models
Mingrui Wu, Xinyue Cai, Jiayi Ji +7
In this work, we propose a training-free method to inject visual prompts into Multimodal Large Language Models (MLLMs) through test-time optimization of a learnable latent variable…
Deep Instruction Tuning for Segment Anything Model
Xiaorui Huang, Gen Luo, Chaoyang Zhu +4
Recently, Segment Anything Model (SAM) has become a research hotspot in the fields of multimedia and computer vision, which exhibits powerful yet versatile capabilities on various…
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models
Gen Luo, Yiyi Zhou, Yuxin Zhang +3
Despite remarkable progress, existing multimodal large language models (MLLMs) are still inferior in granular visual recognition. Contrary to previous works, we study this problem…