Multi-Teacher Distillation
HoldTechniques
A distillation method that transfers knowledge from multiple teacher models into a smaller student model.
Why it's here
Placed in Hold: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 6InfoQ·9/11/2026researchLinkedIn Uses Multi-Teacher Distillation to Speed Job Search Ranking
LinkedIn described the training pipeline behind its AI-powered job search, centered on multi-teacher distillation. The approach compresses knowledge from larger teacher models into a 0.6B-parameter ranking model, enabling the system to train about 8x faster.