SOURCE-LINKED INTELLIGENCE
Seeing Through Conflicts: Improving Instruction Hierarchy Alignment in Vision-Language Models
Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in text-only settings, vision-language models (VLMs) introduce new challenges for IH: instructions may be embedded in images, split across modalities, visually transformed, or encountered during agentic tasks. Positing multimodal IH alignment as a reasoning problem, we train VLMs using reinforcement learning with rule-based rewards, comparing text-only, image-only, and mixed-modality supervision. We find that text-only IH training partially transfer
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T04:59:32.000Z
First collected: 2026-09-26T01:22:24.568Z. This is not the publication date.