6 papers
A Survey of Token Compression for Efficient Multimodal Large Language Models
Kele Shao, Keda Tao, Kejia Zhang +7
Multimodal large language models (MLLMs) have made remarkable strides, largely driven by their ability to process increasingly long and complex contexts, such as high-resolution im…
HoliTom: Holistic Token Merging for Fast Video Large Language Models
Kele Shao, Keda Tao, Can Qin +3
Video large language models (video LLMs) excel at video comprehension but face significant computational inefficiency due to redundant video tokens. Existing token pruning methods…
Plug-and-Play 1.x-Bit KV Cache Quantization for Video Large Language Models
Keda Tao, Haoxuan You, Yang Sui +2
Video large language models (VideoLLMs) have demonstrated the capability to process longer video inputs and enable complex reasoning and analysis. However, due to the thousands of…
SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device
Yushu Wu, Zhixing Zhang, Yanyu Li +11
We have witnessed the unprecedented success of diffusion-based video generation over the past year. Recently proposed models from the community have wielded the power to generate c…
DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models
Keda Tao, Can Qin, Haoxuan You +2
Video large language models (VLLMs) have significantly advanced recently in processing complex video content, yet their inference efficiency remains constrained because of the high…
Transferable Learned Image Compression-Resistant Adversarial Perturbations
Yang Sui, Zhuohang Li, Ding Ding +4
Adversarial attacks can readily disrupt the image classification system, revealing the vulnerability of DNN-based recognition tasks. While existing adversarial perturbations are pr…