Claude 3.5 Sonnet Aces Adversarial Data Science Test, Catches Data Leakage Autonomously
hugobowne · x · 2026-08-04
At a recent workshop, a developer tested the newly released Claude 3.5 Sonnet (referred to as Fable) with a synthetic fraud-detection problem rigged with deliberate traps, including feature leakage, temporal ordering requirements, and class imbalance.
While older models blindly exploited the leakage for perfect scores, Claude 3.5 Sonnet autonomously caught the data leakage, respected temporal ordering, and selected appropriate metrics without being explicitly told. Its zero-shot performance matched or beat a three-hour workflow using older models combined with an adversarial reviewer.
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