SOURCE-LINKED INTELLIGENCE
Multimodal Taxonomic Conditioning for Generative Plankton Imagery
Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or evaluate classifiers reliably. We generate synthetic plankton imagery conditioned on taxonomy: a CLIP encoder is adapted on a large plankton corpus with a ranked contrastive objective extended to deep, ragged taxonomies, then frozen to condition a parameter-efficient diffusion transformer. We evaluate synthetic sample quality on distributional fidelity and downstream classifier utility.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T15:08:53.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.