Morphology-Aware Multimodal Representation Learning for Insect Phylogenetic Reconstruction
Morphological traits provide important evidence for phylogenetic reconstruction and evolutionary relationship analysis. Recent image-based approaches have introduced deep learning, particularly convolutional models, to derive morphological features from specimen images, but these methods generally rely on single-modality visual representations and do not explicitly incorporate morphological semantics. This study proposes a morphology-aware multimodal alignment framework for insect phylogenetic reconstruction. The framework combines specimen images with curated morphological descriptions by adapting a vision transformer through parameter-efficient fine-tuning and supervised contrastive lea...
| Authors | Zixuan Liu, Kaijie Yu, Chun He et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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