How do I know the open-weight base model I am fine-tuning has not been poisoned?
Opportunity
Backdoors planted in pre-trained model weights persist through full-parameter fine-tuning, adapter training, and RLHF updates because the trigger patterns survive objective-shifting and partial-freezing strategies. These triggers are invisible to standard behavioral safety tests and benchmark evaluation. Detecting them requires white-box weight analysis that the average fine-tuning practitioner never runs, and major model hubs apply no mandatory scanning before a checkpoint is made publicly downloadable. An organization building a production system on a compromised base model has no signal anything is wrong until the trigger fires in deployment.
Why it matters
The open-weight fine-tuning supply chain has no security gate, and the failure mode is a backdoor that survives every standard check.
๊ธฐํ ํ๊ฐ ๋ฐฉ์
The Opportunity Score is my own read, not a measurement: how much it hurts, how often it bites, and how little exists to solve it today. Higher means I think it is more worth building.
How much pain it causes when it shows up.
How often people actually run into it.
How little good tooling exists for it today.
ํด๊ฒฐํ ๊ฐ์น ์๋ ๋ ๋ง์ ๋ฌธ์ ๋ค
ํญ์ ๋ซ๋ ์๊ฐ ๋ชจ๋ AI ์ฑ์ด ๋๋ฅผ ์์ด๋ฒ๋ฆฌ๋ ์ด์ ๋ ๋ฌด์์ผ๊น?
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AI๋น์ ๋ฌธ๊ฐ๋ ์ AI๊ฐ ๋งํ ๋ด์ฉ์ ๊ฒ์ฆํ ์ ์์๊น?
AI๋ชจ๋ธ์ ๋ฒค์น๋งํฌ๋ก ํ ์คํธํ๊ณ ๊ฐ์ผ๋ก ๋ฐฐํฌํ๋ ์ด์ ๋ ๋ฌด์์ผ๊น?
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