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TopicsModel Backdoor Attacks Machine Learning

Longer backdoor-insertion training increases a backdoor's robustness to subsequent untargeted training.

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Advice for making robust-to-training model organismsdenies the claim Untraced · nothing upstream recorded

Sleeper Agent Backdoor Results Are Messy Untraced · nothing upstream recorded

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Separately, we confirm that more red team training generally leads to more robust Sleeper Agents.

Sleeper Agent Backdoor Results Are Messyextraction 0.80

Sweep over red-team checkpoints at 100 to 1600 steps and final, followed by HHH SFT.

However, training longer didn’t seem to help with robustness for the 15 backdoors studied in this post.

Advice for making robust-to-training model organismsdeniesextraction 0.75

Contrasts with the authors' earlier sleeper-agent finding that longer training increased robustness.

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Created by extractor · Nov 11, 2026. Every judgment on this page is accompanied by a reasoning trace.