Filters include language ID, perplexity heuristics, blocklists, NSFW classifiers, and near-duplicate detection. Over-filtering can erase dialects, code, or minority viewpoints; under-filtering leaves spam and leakage. Filtering is a product decision with safety and capability trade-offs, not a neutral cleanup step.