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Nearly three-quarters of what benchmarks flag as model bias is just prompt-wording noise, but the surviving 25% are deeply entrenched pretraining representations that stubbornly resist post-training alignment.
Style augmentation and texture regularization can significantly improve semantic segmentation robustness in off-road environments facing distribution shifts.
