LaGuadia: Language-Guided Adaptive Distillation from Pathology Foundation Models
Pathology Foundation Models (PFMs) offer powerful Whole Slide Image (WSI) representations but suffer from massive computational costs. While Knowledge Distillation (KD) can create efficient student models, existing multi-teacher methods often use suboptimal uniform weighting that ignores tissue heterogeneity. We propose LaGuadia (Language-Guided Adaptive DistillAtion), a framework that develops a compact pathology image encoder by dynamically integrating expertise from multiple PFMs under clinic
Record details
Published: 13 July 2026
Source: arXiv cs.LG
Category: Research
Topics: Children & education
Retrieved: 14 July 2026
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ethics.ai (13 July 2026), “LaGuadia: Language-Guided Adaptive Distillation from Pathology Foundation Models,” evidence record 10206, https://ethics.ai/record/10206 (originally published by arXiv cs.LG).
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