4 papers · 1 filter
Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models
Yuheng Shi, Xiaohuan Pei, Linfeng Wen +2
MLLMs require high-resolution visual inputs for fine-grained tasks like document understanding and dense scene perception. However, current global resolution scaling paradigms indi…
Catching the Details: Self-Distilled RoI Predictors for Fine-Grained MLLM Perception
Yuheng Shi, Xiaohuan Pei, Minjing Dong +1
Multimodal Large Language Models (MLLMs) require high-resolution visual information to perform fine-grained perception, yet processing entire high-resolution images is computationa…
Rethinking Causal Mask Attention for Vision-Language Inference
Xiaohuan Pei, Tao Huang, YanXiang Ma +1
Causal attention has become a foundational mechanism in autoregressive vision-language models (VLMs), unifying textual and visual inputs under a single generative framework. Howeve…
Cross-Self KV Cache Pruning for Efficient Vision-Language Inference
Xiaohuan Pei, Tao Huang, Chang Xu
KV cache pruning has emerged as a promising technique for reducing memory and computation costs in long-context auto-regressive generation. Existing methods for vision-language mod…