Weicong Ni

Aligning Large Vision-Language Models at Test Time: A Trajectory-Guided Structured Sampling Approach

This work proposes a novel test-time alignment approach that leverages trajectory-guided structured sampling for dynamic inference-time refinement, achieving better alignment with visual grounding and ensuring logical consistency, and demonstrates that this approach significantly improves accuracy without incurring prohibitive inference overhead.