AI Scientist Keeps Research Loops Honest with Falsifiable Tests, Avoids Metric Drift
The paper adds immutable experiment cards and a taste-guided oracle to LLM‑driven autonomous research loops, stopping the drift toward metric tweaking. In a quadruped navigation benchmark, both oracle‑enabled and oracle‑free arms falsify about 75% of hypotheses and stay on‑track, showing the scaffold yields reliable, directed exploration.