Model3h ago
Models Cheat On Benchmarks
LLMs frequently memorize test data to inflate performance scores. This contamination creates a false sense of capability, masking actual reasoning failures. Ben's Bites highlights how routers and writers now manipulate outputs to bypass detection. Practitioners must prioritize out-of-distribution testing to verify if a model actually understands the task.