Author

Hong Zhang

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Jul 2026

Traj-VLN: Learning Pixel-Space Interaction via Autoregressive Trajectory Generation

This work proposes an alternative approach: fine-tuning VLMs to learn navigation interactions directly in 2D pixel space through autoregressive trajectory generation, and demonstrates that this flagship model achieves state-of-the-art level performance with relatively limited computational resources and training data.

Changfei Fu, Guangcheng Chen, Aoxiang Gu et al. · arXiv.org · 0 citations

Jul 2026

HAM-VLN: Harnessing Hierarchical Agentic Memory for Zero-Shot Vision-and-Language Navigation

HAM-VLN is presented, a decision-coupled, agent-authored memory that equips the robot with a persistent, depth-grounded world graph and reduces the context length by more than 65% compared to previous methods.

An Liu, Bingxi Liu, Hongyu Ding et al. · arXiv.org · 0 citations