collaborators

7 papers

cs.CR2026

SilentDrift: Exploiting Action Chunking for Stealthy Backdoor Attacks on Vision-Language-Action Models

Bingxin Xu, Yuzhang Shang, Binghui Wang +1

Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities remain underexplored. We identify a fundam…

cs.CV2026

VLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image Reasoning

Chaoyang Wang, Wenrui Bao, Sicheng Gao +5

Vision-Language-Action (VLA) models have shown promising capabilities for embodied intelligence, but most existing approaches rely on text-based chain-of-thought reasoning where vi…

cs.LG2026

ButterflyQuant: Ultra-low-bit LLM Quantization through Learnable Orthogonal Butterfly Transforms

Bingxin Xu, Zhen Dong, Oussama Elachqar +1

Large language models require massive memory footprints, severely limiting deployment on consumer hardware. Quantization reduces memory through lower numerical precision, but extre…

cs.CV2026

LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models

Yuzhang Shang, Mu Cai, Bingxin Xu +2

Large Multimodal Models (LMMs) have shown significant visual reasoning capabilities by connecting a visual encoder and a large language model. LMMs typically take in a fixed and la…

cs.CV2024

E-CAR: Efficient Continuous Autoregressive Image Generation via Multistage Modeling

Zhihang Yuan, Yuzhang Shang, Hanling Zhang +7

Recent advances in autoregressive (AR) models with continuous tokens for image generation show promising results by eliminating the need for discrete tokenization. However, these m…

cs.CV2024

freePruner: A Training-free Approach for Large Multimodal Model Acceleration

Bingxin Xu, Yuzhang Shang, Yunhao Ge +2

Large Multimodal Models (LMMs) have demonstrated impressive capabilities in visual-language tasks but face significant deployment challenges due to their high computational demands…