Weak Ties, Strong Signals: Efficient Training Data Detection in Diffusion LLMs via Independent Token Sampling
ITS is proposed, a query-efficient framework that uses an attention-derived pairwise dependency proxy to approximate the CMI-aware selection criterion and incorporates a diversity-promoting strategy to improve token coverage across sampling rounds, yielding aggregated token-wise signals that are less affected by depend...