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20172026
most citedAccelerating Diffusion Transformers with Token-wise Feature Caching

4 citations · 9 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

Variation-aware Vision Token Dropping for Faster Large Vision-Language Models

Junjie Chen, Xuyang Liu, Zichen Wen +3

Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding tasks. However, the increasing demand for high-resolution image and long-…

cs.CV2024

Filter, Correlate, Compress: Training-Free Token Reduction for MLLM Acceleration

Yuhang Han, Xuyang Liu, Zihan Zhang +6

The quadratic complexity of Multimodal Large Language Models (MLLMs) with respect to context length poses significant computational and memory challenges, hindering their real-worl…

cs.CV2024

M2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension

Xuyang Liu, Ting Liu, Siteng Huang +6

Referring expression comprehension (REC) is a vision-language task to locate a target object in an image based on a language expression. Fully fine-tuning general-purpose pre-train…

cs.CV2024

DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding

Ting Liu, Xuyang Liu, Siteng Huang +5

Visual grounding (VG) is a challenging task to localize an object in an image based on a textual description. Recent surge in the scale of VG models has substantially improved perf…

cs.CV2024

Sparse-Tuning: Adapting Vision Transformers with Efficient Fine-tuning and Inference

Ting Liu, Xuyang Liu, Liangtao Shi +6

Parameter-efficient fine-tuning (PEFT) has emerged as a popular solution for adapting pre-trained Vision Transformer (ViT) models to downstream applications by updating only a smal…

cs.CV2023

VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders

Xuyang Liu, Siteng Huang, Yachen Kang +2

Large-scale text-to-image diffusion models have shown impressive capabilities for generative tasks by leveraging strong vision-language alignment from pre-training. However, most v…

cs.CV2017★ 3 cited

AON: Towards Arbitrarily-Oriented Text Recognition

Zhanzhan Cheng, Yangliu Xu, Fan Bai +3

Recognizing text from natural images is a hot research topic in computer vision due to its various applications. Despite the enduring research of several decades on optical charact…