Towards AI-Guided Open-World Ecological Taxonomic Classification

• URL: http://arxiv.org/abs/2512.18994v1
• Date: Mon, 22 Dec 2025 03:20:05 GMT
• Title: Towards AI-Guided Open-World Ecological Taxonomic Classification
• Authors: Cheng Yaw Low, Heejoon Koo, Jaewoo Park, Kaleb Mesfin Asfaw, Meeyoung Cha,
• Abstract summary: TaxoNet is an embedding-based encoder with a dual-marginization loss that strengthens learning signals from rare underrepresented taxa.<n>Our findings show that general-purpose multimodal foundation models remain constrained in plant-domain applications.
• Score: 25.577016053193862
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: AI-guided classification of ecological families, genera, and species underpins global sustainability efforts such as biodiversity monitoring, conservation planning, and policy-making. Progress toward this goal is hindered by long-tailed taxonomic distributions from class imbalance, along with fine-grained taxonomic variations, test-time spatiotemporal domain shifts, and closed-set assumptions that can only recognize previously seen taxa. We introduce the Open-World Ecological Taxonomy Classification, a unified framework that captures the co-occurrence of these challenges in realistic ecological settings. To address them, we propose TaxoNet, an embedding-based encoder with a dual-margin penalization loss that strengthens learning signals from rare underrepresented taxa while mitigating the dominance of overrepresented ones, directly confronting interrelated challenges. We evaluate our method on diverse ecological domains: Google Auto-Arborist (urban trees), iNat-Plantae (Plantae observations from various ecosystems in iNaturalist-2019), and NAFlora-Mini (a curated herbarium collection). Our model consistently outperforms baselines, particularly for rare taxa, establishing a strong foundation for open-world plant taxonomic monitoring. Our findings further show that general-purpose multimodal foundation models remain constrained in plant-domain applications.

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