Traj-VLN: Learning Pixel-Space Interaction via Autoregressive Trajectory Generation
Benefiting from the powerful priors embedded in large-scale pre-training data and the emerging commonsense reasoning ability, large language models (LLMs) have shown unprecedented generalization capabilities in many research fields. Recently, projecting visual embeddings into the language space via vision-language models (VLMs) to achieve sim-toreal and cross-scene generalization has become a prevailing paradigm in the field of Vision-and-Language Navigation in Continuous Environments (VLN-CE). VLN requires an embodied agent to navigate through unseen environments following natural linguistic instructions. We emphasize that a VLN task can be decomposed into a sequence of sub-tasks, each c...
| Authors | Changfei Fu, Guangcheng Chen, Aoxiang Gu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 July 2026 |
| Last updated at source | 22 August 2026 |
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