SOURCE-LINKED INTELLIGENCE
Routing by Reasoning Need: Trajectory-Aware Decoding Control for Diffusion Vision-Language Models
Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and controlled at inference time. However, this controllability creates a reasoning-need mismatch, where a universal generation length is applied to questions with different reasoning demands. Visually closed questions may be harmed by continued refinement after a stable answer has formed, whereas reasoning-sensitive questions may be harmed by premature commitment. We formulate this problem as reasoning-budget mismatch and study it in LLaDA-V. Rather t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T09:41:19.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.