arXiv:2606. 08992v1 Announce Type: cross Abstract: Vision-and-Language Navigation in continuous environments requires agents to understand the spatial structure of previously unseen environments in order to follow language instructions.
By Yucheng Deng, Pingrui Lai, Xinhai Li, Chenjia Bai, Xiaoheng Deng, Chengnuo Sun, Xuelong Li, Hua Yang
arXiv:2603.26788v3 Announce Type: replace-cross
Abstract: Zero-shot object navigation requires agents to locate unseen targets in unfamiliar environments without prior maps or task-specific training....
By Feng Wu, Wei Zuo, Wenliang Yang, Jun Xiao, Yang Liu, Xinhua Zeng
Building memory is essential for long-horizon planning in zero-shot embodied navigation. Detector-centric scene graphs often compress observations into sparse nodes, discarding fine-grained visual evidence and accumulating noise, while 3D reconstruction-based methods remain computationally prohibitive.
arXiv:2606. 00095v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions.
By Kailing Li, Tianwen Qian, Lijin Yang, Yuqian Fu, Jingyu Gong, Xiaoling Wang, Liang He
Large vision-language models (LVLMs) have shown strong potential for embodied vision-language navigation (VLN), yet their performance degrades on long-horizon trajectories due to context-length limits...
MemoryVLN introduces a memory-driven navigation system that compresses long navigation histories and reuses past spatial experience. It uses forgetting-curve-inspired temporal sampling for long sequence compression, an ego-aware memory representation that fuses 2D semantic, 3D geometric, and 6D pose tokens, and a hierarchical memory bank for in-episode and context-level memory management. The system retrieves top‑K relevant memories to augment current visual tokens, achieving significant improvements on R2R‑CE and RxR‑CE benchmarks.
By Xueyao Wei, Yifei Wang, Delun Li, Shaoan Wang, Junzhi Yu, Wenjie Song, Xingyu Chen