BARBICAN study finds routed prompt-injection stages can look accurate by chance
Fixing a tokenizer raised arbitration AUC from 0.392 to 0.855 while system recall fell slightly.
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Fixing a tokenizer raised arbitration AUC from 0.392 to 0.855 while system recall fell slightly.
Classifiers using only interpretable SAE features beat neural and stylometric detectors on out-of-distribution text.
Researchers use Thompson Sampling to pick classifiers that balance accuracy and subgroup fairness online.
Paper ties finite-time Lyapunov exponents of deep classifiers to decision-boundary geometry.
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