The article presents "Antislop," a framework designed to identify and eliminate repetitive patterns, or "slop," in language models that degrade text quality. It introduces three innovative tools: the Antislop Sampler for suppressing unwanted phrases, an automated profiling pipeline, and Final Token Preference Optimization (FTPO) for fine-tuning token logits, achieving significant slop reduction while maintaining or enhancing performance across various evaluation tasks.