Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation Instruction tuning with loss over instructions Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning RETAINING BY DOING: THE ROLE OF ON-POLICY DATA IN MITIGATING FORGETTING Proximal Gradient and Subgradients Importance-Aware Data Selection for Efficient LLM Instruction Tuning Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective FROM CORRECTION TO MASTERY: REINFORCED DISTILLATION OF LARGE LANGUAGE MODEL AGENTS Merge-of-Thought Distillation More...

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