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A Composable Evaluation System for Reproducible Omni-Modal Foundation Model Evaluation

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Building an omni-modal foundation model means evaluating it across text, image, video, and audio. Excellent evaluation toolkits exist for each modality, but their inference engines, prompt conventions, and metric implementations are mutually incompatible, so practitioners end up maintaining separate environments for every toolchain and still struggle to compare results across them. OmniEvaluator grew out of this need in our own model development: rather than reimplementing benchmarks, it connects existing inference engines and curated evaluation libraries at a higher level, exposing four infer

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