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arXiv Computer Vision By Lingteng Zeng

Visual Orchestration Tax in Agentic VLM Pipelines: Auditing and Certifying Visual Evidence Reuse

Read the original on arXiv Computer Vision →

The paper introduces the concept of a visual orchestration tax in agentic vision‑language model (VLM) pipelines, where the same static images are repeatedly processed by multiple agents, creating redundancy. It proposes a measurement‑to‑certification framework that audits visual evidence reuse using metrics M1_trace and M2, and certifies reuse through a SharedVisCache contract. Experiments on SeeingEye and MAMMQA show high redundancy rates (66.8‑75.6%) and demonstrate that certified reuse can reduce vision‑API calls while preserving output fidelity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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