1 citations · 1 across the 7 of their papers we have counts for
8 papers
Fast-Slow Efficient Training for Multimodal Large Language Models via Visual Token Pruning
Dingkun Zhang, Shuhan Qi, Yulin Wu +3
Multimodal Large Language Models (MLLMs) suffer from severe training inefficiency issue, which is associated with their massive model sizes and visual token numbers. Existing effor…
FMVP: Masked Flow Matching for Adversarial Video Purification
Duoxun Tang, Xueyi Zhang, Chak Hin Wang +6
Video recognition models remain vulnerable to adversarial attacks, while existing diffusion-based purification methods suffer from inefficient sampling and curved trajectories. Dir…
MiMo-V2-Flash Technical Report
Core Team, Bangjun Xiao, Bingquan Xia +123
We present MiMo-V2-Flash, a Mixture-of-Experts (MoE) model with 309B total parameters and 15B active parameters, designed for fast, strong reasoning and agentic capabilities. MiMo-…
Attention-Guided Patch-Wise Sparse Adversarial Attacks on Vision-Language-Action Models
Naifu Zhang, Wei Tao, Xi Xiao +5
In recent years, Vision-Language-Action (VLA) models in embodied intelligence have developed rapidly. However, existing adversarial attack methods require costly end-to-end trainin…
FeatureFool: Zero-Query Fooling of Video Models via Feature Map
Duoxun Tang, Xi Xiao, Guangwu Hu +6
The vulnerability of deep neural networks (DNNs) has been preliminarily verified. Existing black-box adversarial attacks usually require multi-round interaction with the model and…
MA-CBP: A Criminal Behavior Prediction Framework Based on Multi-Agent Asynchronous Collaboration
Cheng Liu, Daou Zhang, Tingxu Liu +7
With the acceleration of urbanization, criminal behavior in public scenes poses an increasingly serious threat to social security. Traditional anomaly detection methods based on fe…