TaxDistill: Improving Metagenomic Taxonomic Annotation via Distilled Genomic Foundation Models

Excerpt

arXiv:2605.28868v2 Announce Type: replace Abstract: Metagenomic taxonomic annotation is essential for interpreting complex microbial communities, yet reliable annotation remains challenging under reference database incompleteness and ambiguous taxonomic boundaries. Existing similarity-based tools are efficient, but they often produce noisy pseudo-labels in complex environments; learning-based post-hoc correction methods can further inherit this noise when trained on hard pseudo-labels generated