VLA-IAP: Training-Free Visual Token Pruning via Interaction Alignment for Vision-Language-Action Models
Fuente:
arXiv
Saved in:
| Main Authors: | Cheng, Jintao, Wang, Haozhe, Li, Weibin, Wang, Gang, Zhang, Yipu, Tang, Xiaoyu, Wu, Jin, Chen, Xieyuanli, Liu, Yunhui, Zhang, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models
by: Yang, Yantai, et al.
Published: (2025)
by: Yang, Yantai, et al.
Published: (2025)
ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
by: Sha, Lin, et al.
Published: (2026)
by: Sha, Lin, et al.
Published: (2026)
RobustVLA: Robustness-Aware Reinforcement Post-Training for Vision-Language-Action Models
by: Zhang, Hongyin, et al.
Published: (2025)
by: Zhang, Hongyin, et al.
Published: (2025)
Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference
by: Liu, Ziyan, et al.
Published: (2025)
by: Liu, Ziyan, et al.
Published: (2025)
SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
by: Wang, Hanzhen, et al.
Published: (2025)
by: Wang, Hanzhen, et al.
Published: (2025)
ST4VLA: Spatially Guided Training for Vision-Language-Action Models
by: Ye, Jinhui, et al.
Published: (2026)
by: Ye, Jinhui, et al.
Published: (2026)
VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models
by: Zhang, Jianke, et al.
Published: (2026)
by: Zhang, Jianke, et al.
Published: (2026)
FocusVLA: Focused Visual Utilization for Vision-Language-Action Models
by: Zhang, Yichi, et al.
Published: (2026)
by: Zhang, Yichi, et al.
Published: (2026)
IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning
by: Sun, Zhichao, et al.
Published: (2026)
by: Sun, Zhichao, et al.
Published: (2026)
QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models
by: Zhang, Jingxuan, et al.
Published: (2026)
by: Zhang, Jingxuan, et al.
Published: (2026)
ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models
by: Kim, Youngeun, et al.
Published: (2025)
by: Kim, Youngeun, et al.
Published: (2025)
Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
by: Jin, Ruofan, et al.
Published: (2026)
by: Jin, Ruofan, et al.
Published: (2026)
CRL-VLA: Continual Vision-Language-Action Learning
by: Zeng, Qixin, et al.
Published: (2026)
by: Zeng, Qixin, et al.
Published: (2026)
SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation
by: Ma, Shilin, et al.
Published: (2026)
by: Ma, Shilin, et al.
Published: (2026)
CoA-VLA: Improving Vision-Language-Action Models via Visual-Textual Chain-of-Affordance
by: Li, Jinming, et al.
Published: (2024)
by: Li, Jinming, et al.
Published: (2024)
CV-MOS: A Cross-View Model for Motion Segmentation
by: Tang, Xiaoyu, et al.
Published: (2024)
by: Tang, Xiaoyu, et al.
Published: (2024)
AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention
by: Xiao, Lei, et al.
Published: (2025)
by: Xiao, Lei, et al.
Published: (2025)
VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models
by: Wang, Hao, et al.
Published: (2026)
by: Wang, Hao, et al.
Published: (2026)
EvoVLA: Self-Evolving Vision-Language-Action Model
by: Liu, Zeting, et al.
Published: (2025)
by: Liu, Zeting, et al.
Published: (2025)
CoViPAL: Layer-wise Contextualized Visual Token Pruning for Large Vision-Language Models
by: Tang, Zicong, et al.
Published: (2025)
by: Tang, Zicong, et al.
Published: (2025)
A Pseudo Global Fusion Paradigm-Based Cross-View Network for LiDAR-Based Place Recognition
by: Cheng, Jintao, et al.
Published: (2025)
by: Cheng, Jintao, et al.
Published: (2025)
IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model
by: Jiang, Anqing, et al.
Published: (2025)
by: Jiang, Anqing, et al.
Published: (2025)
VLA-R1: Enhancing Reasoning in Vision-Language-Action Models
by: Ye, Angen, et al.
Published: (2025)
by: Ye, Angen, et al.
Published: (2025)
VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers
by: Wang, Yating, et al.
Published: (2025)
by: Wang, Yating, et al.
Published: (2025)
VLA-Cache: Efficient Vision-Language-Action Manipulation via Adaptive Token Caching
by: Xu, Siyu, et al.
Published: (2025)
by: Xu, Siyu, et al.
Published: (2025)
FreezeVLA: Action-Freezing Attacks against Vision-Language-Action Models
by: Wang, Xin, et al.
Published: (2025)
by: Wang, Xin, et al.
Published: (2025)
VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing
by: Shi, Haoyuan, et al.
Published: (2026)
by: Shi, Haoyuan, et al.
Published: (2026)
FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies
by: Hu, Xintong, et al.
Published: (2026)
by: Hu, Xintong, et al.
Published: (2026)
GeneralVLA: Generalizable Vision-Language-Action Models with Knowledge-Guided Trajectory Planning
by: Ma, Guoqing, et al.
Published: (2026)
by: Ma, Guoqing, et al.
Published: (2026)
RedVTP: Training-Free Acceleration of Diffusion Vision-Language Models Inference via Masked Token-Guided Visual Token Pruning
by: Xu, Jingqi, et al.
Published: (2025)
by: Xu, Jingqi, et al.
Published: (2025)
StereoVLA: Enhancing Vision-Language-Action Models with Stereo Vision
by: Deng, Shengliang, et al.
Published: (2025)
by: Deng, Shengliang, et al.
Published: (2025)
VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models
by: Wang, Zixuan, et al.
Published: (2026)
by: Wang, Zixuan, et al.
Published: (2026)
Token Expand-Merge: Training-Free Token Compression for Vision-Language-Action Models
by: Ye, Yifan, et al.
Published: (2025)
by: Ye, Yifan, et al.
Published: (2025)
DynamicVLA: A Vision-Language-Action Model for Dynamic Object Manipulation
by: Xie, Haozhe, et al.
Published: (2026)
by: Xie, Haozhe, et al.
Published: (2026)
Scale, Don't Fine-tune: Guiding Multimodal LLMs for Efficient Visual Place Recognition at Test-Time
by: Cheng, Jintao, et al.
Published: (2025)
by: Cheng, Jintao, et al.
Published: (2025)
UrbanVLA: A Vision-Language-Action Model for Urban Micromobility
by: Li, Anqi, et al.
Published: (2025)
by: Li, Anqi, et al.
Published: (2025)
QUAR-VLA: Vision-Language-Action Model for Quadruped Robots
by: Ding, Pengxiang, et al.
Published: (2023)
by: Ding, Pengxiang, et al.
Published: (2023)
CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models
by: Zhao, Qingqing, et al.
Published: (2025)
by: Zhao, Qingqing, et al.
Published: (2025)
SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning
by: Zhang, Borong, et al.
Published: (2025)
by: Zhang, Borong, et al.
Published: (2025)
SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration
by: Li, Ye, et al.
Published: (2025)
by: Li, Ye, et al.
Published: (2025)
Similar Items
-
EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models
by: Yang, Yantai, et al.
Published: (2025) -
ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving
by: Sha, Lin, et al.
Published: (2026) -
RobustVLA: Robustness-Aware Reinforcement Post-Training for Vision-Language-Action Models
by: Zhang, Hongyin, et al.
Published: (2025) -
Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference
by: Liu, Ziyan, et al.
Published: (2025) -
SpecPrune-VLA: Accelerating Vision-Language-Action Models via Action-Aware Self-Speculative Pruning
by: Wang, Hanzhen, et al.
Published: (2025)