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AgentDoG 1.5 proves you can achieve GPT-5.4-level agent safety with open-source models trained on just 1k samples, slashing deployment overhead by two orders of magnitude.
LLMs exhibit a quantifiable "Parametric Memory Law" during LoRA finetuning, where loss reduction scales predictably with effective parameters and sequence length, revealing fundamental limits on how much they can memorize.
