{"slug": "beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation", "title": "Beyond Teacher Assignment: Domain-Normalized Multi-Teacher On-Policy Distillation", "summary": "Multi-teacher on-policy distillation (MOPD) merges specialist language models trained via reinforcement learning into a single model, but the technique suffers from a domain-imbalance problem that the paper addresses with a domain-normalized variant. The work targets the gap between single-skill specialists in mathematics, coding and instruction following and users' need for one model with all of these skills.", "body_md": "Reinforcement learning can turn one language model into several specialists, each excellent at a single skill such as mathematics, coding or following instructions, but users need one model with all of these skills. Multi-teacher on-policy distillation (MOPD) merges them by letting the specialists t", "url": "https://wpnews.pro/news/beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation", "canonical_source": "https://aiflash.com/news/128302/", "published_at": "2026-09-29 06:00:02+00:00", "updated_at": "2026-09-29 06:17:55.631689+00:00", "lang": "en", "topics": ["machine-learning", "large-language-models", "ai-research", "natural-language-processing"], "entities": [], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation", "markdown": "https://wpnews.pro/news/beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation.md", "text": "https://wpnews.pro/news/beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation.txt", "jsonld": "https://wpnews.pro/news/beyond-teacher-assignment-domain-normalized-multi-teacher-on-policy-distillation.jsonld"}}