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Are Image Generators Zero-Shot Perceivers? A Rigorous Evaluation
Recent work, such as Vision Banana, shows that lightweight instruction tuning can enable an image generator to achieve state-of-the-art performance across multiple visual perception tasks. Motivated by this perspective, we ask how far image generators can go on public visual perception benchmarks in a zero-shot setting. We introduce ProbeGen, a benchmark for zero-shot generative perception that casts monocular depth estimation, referring/reasoning segmentation, and object counting as conditional generation tasks specified through text prompts, and compares 20 models in total---including propri
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- arXiv · AI, language, vision and robotics · 2026-09-07T18:48:57.000Z
First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.