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OPD excels at transferring reasoning skills over specific answers, revealing a nuanced relationship between teacher-student origins that can complicate multi-teacher setups.
Uncover a model's "digital DNA" – its pretraining data mixture – from its outputs alone, even without access to the training data.
LLMs can learn to reason *worse* from seemingly better training data: models trained on CoT data with lower loss can generalize poorly due to inheriting inefficient, divergent reasoning patterns.