AI RESEARCH
Beyond Single-Sample: Reliable Multi-Sample Distillation for Video Understanding
arXiv CS.CV
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ArXi:2603.11423v1 Announce Type: new Traditional black-box distillation for Large Vision-Language Models (LVLMs) typically relies on a single teacher response per input, which often yields high-variance responses and format inconsistencies in multimodal or temporal scenarios. To mitigate this unreliable supervision, we propose R-MSD (Reliable Multi-Sample Distillation), a framework that explicitly models teacher sampling variance to enhance distillation stability.