arXiv AI
Jun 30

CLOSER-VLN: Closed-Loop Self-Verified Retrieval-Augmented Reasoning for Aerial Vision-Language Navigation

arXiv:2606. 28397v1 Announce Type: cross Abstract: Vision-language navigation (VLN) has recently advanced with large language and multimodal models, enabling agents to follow natural-language instructions in unseen environments without training a task-specific navigation policy.

By Shaoxuan Li, Xiangyu Dong, Xiaoguang Ma, Junfeng Chen, Haoran Zhao, Yaoming Zhou
arXiv Computer Vision
Sep 3

LookStep: Efficient Vision-Language Navigation with Linguistic Foresight and Event Driven Memory

LookStep is a new end‑to‑end framework for Vision‑Language Navigation that integrates Language‑Centric Future State Modeling with an Event‑Driven Rolling Memory. It uses language labels to predict coarse navigation progress and future states for candidate actions, and autonomously decides which observations to store in a bounded memory with semantic roles. Empirical results show that LookStep outperforms existing methods on VLN‑CE tasks, achieving a 49.7% success rate on R2R‑CE Val‑Unseen while improving memory efficiency and reducing data requirements.

By Kun-Yang Yu, Yingzhe Li, Hongyu Xu, Shi-Yu Tian, Zhi Zhou, Yang Chen, Ming Yang, Sheng Wang, Qing Yu, Lan-Zhe Guo, Yu-Feng Li
arXiv Computer Vision
Oct 12

Robust Vision-Language Navigation with Awareness of Instruction-Execution Progress

The paper introduces VLN-AIEP, a Vision‑Language Navigation framework that integrates instruction‑execution progress awareness into navigation decisions. By linking the visited trajectory to the instruction, it suppresses embeddings of already executed content and matches candidate locations with pending instruction segments. The method employs a landmark‑anchored trajectory representation to encode semantic labels and geometry, enabling progress estimation without explicit supervision and achieving strong results on R2R, RxR, CVDN, and R2R‑CE benchmarks.

By Jiagan Huang, Zikun Zhou, Hongpeng Wang, Guangming Lu, Jun Yu, Wenjie Pei