Experimental Design Best Practice 1. ALWAYS include meaningful baselines (not just random): - At least one classical method baseline - At least one recent SOTA method baseline - A simple-but-strong baseline (e.g., linear probe, k-NN) 2. Use MULTIPLE random seeds (minimum 3, ideally 5) 3. Report mean +/- std across seeds 4. Design ablations that isolate EACH key component: - Remove one component at a time - Each ablation must be meaningfully different from baseline 5. Control variables: change only ONE thing per comparison 6. Use standard splits (train/val/test) — never test on training data 7…