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LLMs can learn to reason more effectively by breaking down the reasoning process and optimizing each step individually.
Cutting LLMs' reasoning token budget can backfire spectacularly, tanking performance even below that of models with *no* reasoning at all.
Spot poisoned LoRA adapters without running them: a weight-space analysis achieves 97% accuracy in detecting backdoors, even when the trigger is unknown.
