SWE-bench
1 reportSWE-bench is an artificial intelligence benchmark that compares systems on defined tasks, datasets, metrics, and testing conditions. Evaluation relies on benchmark dataset, test split, and data contamination, including the costs, limitations, and tradeoffs hidden by a single headline metric.
The evidence base around SWE-bench is examined through baseline systems, together with benchmark dataset and test split. Complementary views of test split come from held-out evaluations and independent reproduction, but the conclusion remains bounded because the comparison must account for the fact that a single score may not measure robustness, safety, or practical usefulness.
The evidence base around SWE-bench is examined through baseline systems, together with benchmark dataset and test split. Complementary views of test split come from held-out evaluations and independent reproduction, but the conclusion remains bounded because the comparison must account for the fact that a single score may not measure robustness, safety, or practical usefulness.
Why More Data Alone No Longer Advances Generative AI Systems
Recent advances in generative AI have relied on scaling up models, datasets, and computing resources. However, evidence now suggests that simply increasing data volume is no longer enough to improve performance, especially for complex tasks like software development