domains / families / research / iclr-experiments

iclr-experiments

separate

Use when designing or auditing ICLR experiments, including baselines, ablations, scaling laws, robustness, statistics, benchmarks, human evaluation, and compute reporting. Use when a reviewer questions whether a representation-learning or model gain is real, when you must isolate one mechanism with an ablation, or when preparing a small compute-matched control that can be posted inline during the public discussion period.

When to use

• designing ICLR experiments
• auditing ICLR experiments
• selecting baselines
• designing ablations
• analyzing scaling laws
• conducting robustness checks
• reporting statistics
• reporting compute

Skill page

Source