Where Did It Go Wrong? Capability-Oriented Failure Attribution for Vision-and-Language Navigation Agents
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918470912835584 |
|---|---|
| author | Chen, Jianming Wang, Yawen Wang, Junjie Xie, Xiaofei Li, Shoubin Wang, Qing Xu, Fanjiang |
| author_facet | Chen, Jianming Wang, Yawen Wang, Junjie Xie, Xiaofei Li, Shoubin Wang, Qing Xu, Fanjiang |
| contents | Embodied agents in safety-critical applications such as Vision-Language Navigation (VLN) rely on multiple interdependent capabilities (e.g., perception, memory, planning, decision), making failures difficult to localize and attribute. Existing testing methods are largely system-level and provide limited insight into which capability deficiencies cause task failures. We propose a capability-oriented testing approach that enables failure detection and attribution by combining (1) adaptive test case generation via seed selection and mutation, (2) capability oracles for identifying capability-specific errors, and (3) a feedback mechanism that attributes failures to capabilities and guides further test generation. Experiments show that our method discovers more failure cases and more accurately pinpoints capability-level deficiencies than state-of-the-art baselines, providing more interpretable and actionable guidance for improving embodied agents. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_25161 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Where Did It Go Wrong? Capability-Oriented Failure Attribution for Vision-and-Language Navigation Agents Chen, Jianming Wang, Yawen Wang, Junjie Xie, Xiaofei Li, Shoubin Wang, Qing Xu, Fanjiang Multiagent Systems Artificial Intelligence Embodied agents in safety-critical applications such as Vision-Language Navigation (VLN) rely on multiple interdependent capabilities (e.g., perception, memory, planning, decision), making failures difficult to localize and attribute. Existing testing methods are largely system-level and provide limited insight into which capability deficiencies cause task failures. We propose a capability-oriented testing approach that enables failure detection and attribution by combining (1) adaptive test case generation via seed selection and mutation, (2) capability oracles for identifying capability-specific errors, and (3) a feedback mechanism that attributes failures to capabilities and guides further test generation. Experiments show that our method discovers more failure cases and more accurately pinpoints capability-level deficiencies than state-of-the-art baselines, providing more interpretable and actionable guidance for improving embodied agents. |
| title | Where Did It Go Wrong? Capability-Oriented Failure Attribution for Vision-and-Language Navigation Agents |
| topic | Multiagent Systems Artificial Intelligence |
| url | https://arxiv.org/abs/2604.25161 |