History-Conditioned Spatio-Temporal Visual Token Pruning for Efficient Vision-Language Navigation

arXiv:2603.06480 · cs.RO · Submitted 2026-03-06 · Read on arXiv

cs.RO

Submitted: 2026-03-06

Updated: 2026-09-24

Comments: International Conference on Intelligent Robots and Systems (IROS) 2026

Project page: https://wqtwjt1996.github.io/publications/2026-vln.html

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Pruning — 87× in this paper · explained in 4 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Vision-Language Navigation — 9× in this paper
• Redundancy — 5× in this paper · explained in 2 episodes
• Success Rate — 5× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Grounding — 4× in this paper · explained in 3 episodes
• Vision-Language-Action (VLA) Models — 4× in this paper · explained in 2 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Recent Vision-Language-Action — 3× in this paper
• Transformer — 3× in this paper · explained in 2 episodes
• VLA Models — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Oracle Success Rate — 2× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• VL-Nav: Neuro-Symbolic Reasoning-based Vision-Language Navigation
• Unified Vision-Language-Action Model

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• ARC: A Reasoning Recipe for Robot Foundation Models
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies