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Dokyoon

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reacted to codelion's post with 🚀 about 6 hours ago
Extended the ICM paper to show cross-model capability transfer - used Qwen3's mathematical reasoning to improve Gemma3 without any human supervision. Key results: Qwen3-0.6B: 63.2 → 66.0 on MATH-500 (+4%) Gemma3-1B: 41.0 → 45.6 on MATH-500 (+11%) The method extracts coherent reasoning patterns from one model via Internal Coherence Maximization, converts them to DPO training data, and uses that to improve a completely different model architecture. This goes beyond the original ICM paper which only improved models using their own labels. We're showing you can transfer capabilities between any models - imagine extracting capabilities from strong models to improve your local ones. Models available: https://huggingface.co/codelion/Qwen3-0.6B-ICM-DPO https://huggingface.co/codelion/gemma-3-1b-it-ICM-DPO Complete collection with code and datasets: https://huggingface.co/collections/codelion/internal-coherence-maximization-687a1bd1c1f5f1d6f76e9b3b Full methodology and results: https://huggingface.co/blog/codelion/internal-coherence-maximization Planning to extend this to code generation next. The approach could enable community-driven capability sharing between different model families without expensive annotation.
liked a model 1 day ago
MetaStoneTec/XBai-o4
liked a model 6 days ago
mistralai/Magistral-Small-2507
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