Imagen de Portada

Walk and Read Less: Improving the Efficiency of Vision-and-Language Navigation via Tuning-Free Multimodal Token Pruning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Qin, Wenda, Burns, Andrea, Plummer, Bryan A., Betke, Margrit
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Tell Me What's Next: Textual Foresight for Generic UI Representations
por: Burns, Andrea, et al.
Publicado: (2024)

LoRA-Loop: Closing the Synthetic Replay Cycle for Continual VLM Learning
por: Wang, Kaihong, et al.
Publicado: (2025)

ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models
por: Kim, Youngeun, et al.
Publicado: (2025)

MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
por: Cao, Jianjian, et al.
Publicado: (2024)

Web Artifact Attacks Disrupt Vision Language Models
por: Qraitem, Maan, et al.
Publicado: (2025)

RedVTP: Training-Free Acceleration of Diffusion Vision-Language Models Inference via Masked Token-Guided Visual Token Pruning
por: Xu, Jingqi, et al.
Publicado: (2025)

VLA-IAP: Training-Free Visual Token Pruning via Interaction Alignment for Vision-Language-Action Models
por: Cheng, Jintao, et al.
Publicado: (2026)

PanoFree: Tuning-Free Holistic Multi-view Image Generation with Cross-view Self-Guidance
por: Liu, Aoming, et al.
Publicado: (2024)

Attention Debiasing for Token Pruning in Vision Language Models
por: Zhao, Kai, et al.
Publicado: (2025)

HiPrune: Hierarchical Attention for Efficient Token Pruning in Vision-Language Models
por: Liu, Jizhihui, et al.
Publicado: (2025)

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
por: Sha, Lin, et al.
Publicado: (2026)

QAPruner: Quantization-Aware Vision Token Pruning for Multimodal Large Language Models
por: Wang, Xinhao, et al.
Publicado: (2026)

Pruning All-Rounder: Rethinking and Improving Inference Efficiency for Large Vision Language Models
por: Suo, Wei, et al.
Publicado: (2024)

Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers
por: Pham, Chau, et al.
Publicado: (2024)

Towards Joint Quantization and Token Pruning of Vision-Language Models
por: Li, Xinqing, et al.
Publicado: (2026)

HIVTP: A Training-Free Method to Improve VLMs Efficiency via Hierarchical Visual Token Pruning Using Middle-Layer-Based Importance Score
por: Xu, Jingqi, et al.
Publicado: (2025)

EntropyPrune: Matrix Entropy Guided Visual Token Pruning for Multimodal Large Language Models
por: Wang, Yahong, et al.
Publicado: (2026)

ExeChecker: Where Did I Go Wrong?
por: Gu, Yiwen, et al.
Publicado: (2024)

Object-Centric Vision Token Pruning for Vision Language Models
por: Li, Guangyuan, et al.
Publicado: (2025)

Less is More: Token-Efficient Video-QA via Adaptive Frame-Pruning and Semantic Graph Integration
por: Wang, Shaoguang, et al.
Publicado: (2025)

TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models
por: Lee, Jaewoo, et al.
Publicado: (2025)

ChA-MAEViT: Unifying Channel-Aware Masked Autoencoders and Multi-Channel Vision Transformers for Improved Cross-Channel Learning
por: Pham, Chau, et al.
Publicado: (2025)

Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance
por: Liang, Yuxuan, et al.
Publicado: (2025)

VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation
por: Chen, Hanning, et al.
Publicado: (2024)

TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model
por: Li, Ao, et al.
Publicado: (2025)

IWP: Token Pruning as Implicit Weight Pruning in Large Vision Language Models
por: Lee, Dong-Jae, et al.
Publicado: (2026)

Efficient Vision-Language Reasoning via Adaptive Token Pruning
por: Li, Xue, et al.
Publicado: (2025)

Decoupled Similarity for Task-Aware Token Pruning in Large Vision-Language Models
por: Ma, Kexin, et al.
Publicado: (2026)

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models
por: He, Landi, et al.
Publicado: (2026)

ATP-LLaVA: Adaptive Token Pruning for Large Vision Language Models
por: Ye, Xubing, et al.
Publicado: (2024)

Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration
por: Endo, Mark, et al.
Publicado: (2024)

Multi-Cue Adaptive Visual Token Pruning for Large Vision-Language Models
por: Luan, Bozhi, et al.
Publicado: (2025)

METEOR: Multi-Encoder Collaborative Token Pruning for Efficient Vision Language Models
por: Liu, Yuchen, et al.
Publicado: (2025)

LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models
por: Takezoe, Rinyoichi, et al.
Publicado: (2026)

IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning
por: Sun, Zhichao, et al.
Publicado: (2026)

GenEAva: Generating Cartoon Avatars with Fine-Grained Facial Expressions from Realistic Diffusion-based Faces
por: Yu, Hao, et al.
Publicado: (2025)

Gen-AFFECT: Generation of Avatar Fine-grained Facial Expressions with Consistent identiTy
por: Yu, Hao, et al.
Publicado: (2025)

VLN-R1: Vision-Language Navigation via Reinforcement Fine-Tuning
por: Qi, Zhangyang, et al.
Publicado: (2025)

TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models
por: Zhang, Hao, et al.
Publicado: (2025)

LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration
por: Wang, Siqi, et al.
Publicado: (2023)