{"slug": "allspark-weak-to-strong-transfer-via-alternating-chain-of-thought", "title": "Allspark: Weak to Strong Transfer via Alternating Chain of Thought", "summary": "Researchers introduced Allspark, a method that uses an alternating chain of thought to transfer reasoning improvements learned by a small, weak model to a larger, stronger model without generating large-model rollouts, according to the paper's description of the technique. The work targets the high cost of large-scale reinforcement learning, where generating rollouts from frontier models makes even testing RL recipes expensive. The approach aims to let a stronger model benefit from a weaker model's learned reasoning improvements.", "body_md": "Recent progress in frontier models has renewed interest in large-scale reinforcement learning (RL), but the cost of generating large-model rollouts makes even testing RL recipes expensive. We ask whether reasoning improvements learned by a small, weak model can benefit a larger, stronger model witho", "url": "https://wpnews.pro/news/allspark-weak-to-strong-transfer-via-alternating-chain-of-thought", "canonical_source": "https://aiflash.com/news/128753/", "published_at": "2026-09-29 19:00:07+00:00", "updated_at": "2026-09-29 19:20:08.986735+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-research"], "entities": ["Allspark"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/allspark-weak-to-strong-transfer-via-alternating-chain-of-thought", "markdown": "https://wpnews.pro/news/allspark-weak-to-strong-transfer-via-alternating-chain-of-thought.md", "text": "https://wpnews.pro/news/allspark-weak-to-strong-transfer-via-alternating-chain-of-thought.txt", "jsonld": "https://wpnews.pro/news/allspark-weak-to-strong-transfer-via-alternating-chain-of-thought.jsonld"}}