כתבה
arXiv cs.AI ·
TaxDistill: השיפור של TaxDistill באפיון טקסונומי של מטאגנומיקה
TaxDistill: Improving Metagenomic Taxonomic Annotation via Distilled Genomic Foundation Models
TaxDistill משפר אפיון טקסונומי של מטאגנומיקה באמצעות דגימות גנומי נרכבות.
תקציר מקורי באנגליתarXiv:2605.28868v2 Announce Type: replace-cross 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 by upstream classifiers. We propose TaxDistill, a plug-and-play knowledge distillation framework for reliable metagenomic taxonomic recalibration. TaxDistill uses the genomic foundation model GenomeOcean as a semantic teacher and performs one-way online distillation, where the teacher is updat
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