Anticipate Before Acting: Future-State-Conditioned Vision-Language Navigation
End-to-end vision-language navigation (VLN) with causal vision-language models maps instructions and egocentric observations directly to actions, but standard behavior cloning supervises only the next action and does not explicitly encourage the policy state to be predictive of future visual outcomes, limiting long-horizon decision making. A privileged-input diagnostic shows that access to an expert-trajectory future image can substantially improve navigation, indicating that future observations contain rich, actionable cues, though such inputs are unavailable at deployment. Motivated by this signal, we propose Future-State-Conditioned VLN (FSC-VLN), a deployable model that augments a cau...
| Authors | Lingfeng Zhang, Zhanguang Zhang, Liheng Ma et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 July 2026 |
| Last updated at source | 23 July 2026 |
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