realitydriftproject/constraint-collapse-fidelity-decay-llm-alignment-failure

该数据集包含一篇研究论文，介绍了大型语言模型和其他符号系统中的结构性故障模式——约束崩溃。现代语言模型可以产生连贯、自信的输出，但可能持续错误。这些错误不会中断生成过程或产生内部成本，而是将纠正外部化给用户、评估流程或再训练周期。这导致系统在没有整合反馈的情况下继续运行。约束崩溃描述了反馈持续存在但不再强制执行纠正的情况，从而导致语义保真度随时间逐渐下降。这不是幻觉问题，而是纠正动态的失败。

This dataset contains a research paper introducing constraint collapse, a structural failure mode in large language models and other symbolic systems. Modern language models can produce coherent, confident outputs while being persistently wrong. These errors do not interrupt generation or impose internal cost. Instead, correction is externalized to users, evaluation pipelines, or retraining cycles. This creates a system that continues operating without integrating feedback. Constraint collapse describes the condition where feedback continues to circulate but no longer enforces correction, allowing semantic fidelity to degrade over time. This is not a hallucination problem. It is a failure of correction dynamics.