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Parameter importance isn't forever: dynamically adapting which parameters are frozen during fine-tuning significantly improves generalization and reduces forgetting in LLMs.
Achieve better token efficiency in LLM policy optimization by using a novel FiberPO objective whose Jacobian is block-diagonal over trajectories and reduces to identity on-policy.
