Image de couverture de livre

Token Pruning using a Lightweight Background Aware Vision Transformer

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sah, Sudhakar, Kumar, Ravish, Rohmetra, Honnesh, Saboori, Ehsan
Format:	Preprint
Publié:	2024
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MCUBench: A Benchmark of Tiny Object Detectors on MCUs
par: Sah, Sudhakar, et autres
Publié: (2024)

STResNet & STYOLO : A New Family of Compact Classification and Object Detection Models for MCUs
par: Sah, Sudhakar, et autres
Publié: (2026)

QAPruner: Quantization-Aware Vision Token Pruning for Multimodal Large Language Models
par: Wang, Xinhao, et autres
Publié: (2026)

ZSPAPrune: Zero-Shot Prompt-Aware Token Pruning for Vision-Language Models
par: Zhang, Pu, et autres
Publié: (2025)

Index-Preserving Lightweight Token Pruning for Efficient Document Understanding in Vision-Language Models
par: Son, Jaemin, et autres
Publié: (2025)

Frequency-Aware Token Reduction for Efficient Vision Transformer
par: Lee, Dong-Jae, et autres
Publié: (2025)

Object-Centric Vision Token Pruning for Vision Language Models
par: Li, Guangyuan, et autres
Publié: (2025)

TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model
par: Li, Ao, et autres
Publié: (2025)

IWP: Token Pruning as Implicit Weight Pruning in Large Vision Language Models
par: Lee, Dong-Jae, et autres
Publié: (2026)

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
par: Sha, Lin, et autres
Publié: (2026)

Grounding-Aware Token Pruning: Recovering from Drastic Performance Drops in Visual Grounding Caused by Pruning
par: Chien, Tzu-Chun, et autres
Publié: (2025)

Beyond Attention Scores: SVD-Based Vision Token Pruning for Efficient Vision-Language Models
par: Apedo, Yvon, et autres
Publié: (2026)

VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models
par: Ji, Huawei, et autres
Publié: (2026)

Balanced Token Pruning: Accelerating Vision Language Models Beyond Local Optimization
par: Li, Kaiyuan, et autres
Publié: (2025)

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models
par: He, Jialuo, et autres
Publié: (2026)

How Lightweight Can A Vision Transformer Be
par: Tan, Jen Hong
Publié: (2024)

PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
par: Meng, Yu, et autres
Publié: (2025)

Evading Visual Aphasia: Contrastive Adaptive Semantic Token Pruning for Vision-Language Models
par: Ma, Jie, et autres
Publié: (2026)

Exploring Token Pruning in Vision State Space Models
par: Zhan, Zheng, et autres
Publié: (2024)

Temporal Object-Aware Vision Transformer for Few-Shot Video Object Detection
par: Kumar, Yogesh, et autres
Publié: (2025)

EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent
par: Li, Jiaao, et autres
Publié: (2025)

ActNAS : Generating Efficient YOLO Models using Activation NAS
par: Sah, Sudhakar, et autres
Publié: (2024)

TokenTrim: Inference-Time Token Pruning for Autoregressive Long Video Generation
par: Shaulov, Ariel, et autres
Publié: (2026)

AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network
par: Kang, Donghwa, et autres
Publié: (2024)

Walk and Read Less: Improving the Efficiency of Vision-and-Language Navigation via Tuning-Free Multimodal Token Pruning
par: Qin, Wenda, et autres
Publié: (2025)

Understanding Pruning Regimes in Vision-Language Models Through Domain-Aware Layer Selection
par: Khaki, Saeed, et autres
Publié: (2026)

OccamToken: Efficient VLM Inference with Training-Free and Budget-Adaptive Token Pruning
par: Li, Geng, et autres
Publié: (2026)

NuWa: Deriving Lightweight Task-Specific Vision Transformers for Edge Devices
par: Wei, Ziteng, et autres
Publié: (2025)

TopV: Compatible Token Pruning with Inference Time Optimization for Fast and Low-Memory Multimodal Vision Language Model
par: Yang, Cheng, et autres
Publié: (2025)

Sharp Eyes and Memory for VideoLLMs: Information-Aware Visual Token Pruning for Efficient and Reliable VideoLLM Reasoning
par: Qin, Jialong, et autres
Publié: (2025)

Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers
par: Lee, Dong Hoon, et autres
Publié: (2024)

TinyDrop: Tiny Model Guided Token Dropping for Vision Transformers
par: Wang, Guoxin, et autres
Publié: (2025)

Detecting Regional Spurious Correlations in Vision Transformers via Token Discarding
par: Kang, Solha, et autres
Publié: (2025)

SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
par: Wang, Hanzhen, et autres
Publié: (2025)

IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs
par: Tan, Yifan, et autres
Publié: (2026)

PQV-Mobile: A Combined Pruning and Quantization Toolkit to Optimize Vision Transformers for Mobile Applications
par: Bhardwaj, Kshitij
Publié: (2024)

MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models
par: Liu, Shengyuan, et autres
Publié: (2026)

When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning
par: Luo, Junwei, et autres
Publié: (2025)

GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation
par: Xu, Xuwei, et autres
Publié: (2023)

CoViPAL: Layer-wise Contextualized Visual Token Pruning for Large Vision-Language Models
par: Tang, Zicong, et autres
Publié: (2025)