arxivcs.LGcs.AIcs.CL2026-07-02
HERMES: A Multi-Granularity Labeling Substrate for Pre-training Data Mixtures
Ziyun Qiao, Yue Min, Ruining Chen, Yujun Li
Most data-mixing methods assume the corpus has already been partitioned into groups, and the choice of those groups determines what a mixer can express. Existing labels, including provenance, topic or format taxonomies, and flat embedding clusters, commit to one semantic axis at…