1 citations · 1 across the 2 of their papers we have counts for
5 papers
LMM-Incentive: Large Multimodal Model-based Incentive Design for User-Generated Content in Web 3.0
Jinbo Wen, Jiawen Kang, Linfeng Zhang +5
Web 3.0 represents the next generation of the Internet, which is widely recognized as a decentralized ecosystem that focuses on value expression and data ownership. By leveraging b…
Mixing Importance with Diversity: Joint Optimization for KV Cache Compression in Large Vision-Language Models
Xuyang Liu, Xiyan Gui, Yuchao Zhang +1
Recent large vision-language models (LVLMs) demonstrate remarkable capabilities in processing extended multi-modal sequences, yet the resulting key-value (KV) cache expansion creat…
Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models
Xuyang Liu, Yiyu Wang, Junpeng Ma +1
Video large language models (VideoLLM) excel at video understanding, but face efficiency challenges due to the quadratic complexity of abundant visual tokens. Our systematic analys…
Seeing Sarcasm Through Different Eyes: Analyzing Multimodal Sarcasm Perception in Large Vision-Language Models
Junjie Chen, Xuyang Liu, Subin Huang +2
With the advent of large vision-language models (LVLMs) demonstrating increasingly human-like abilities, a pivotal question emerges: do different LVLMs interpret multimodal sarcasm…
Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model
Ting Liu, Liangtao Shi, Richang Hong +3
The vision tokens in multimodal large language models usually exhibit significant spatial and temporal redundancy and take up most of the input tokens, which harms their inference…