Automated subject cataloging assigns controlledvocabulary headings to bibliographic records, but LCSH has no standard public benchmark. We introduce LCSHBench: 22,346 books in 15 languages from the openly licensed Harvard, Columbia, and Princeton catalogs. Records enter only when at least two independent cataloging agencies assigned LCSH; we release per-catalog provenance plus union and unanimous answer views. A concordance study of 465,187 works cataloged by all three libraries shows why this design matters: libraries usually agree on the underlying topic (93.3% share a concept-level heading) but often differ in exact expression (39.4% have identical heading sets). LCSHBench therefore scores both exact and concept matches, with set and rank metrics broken down by language and heading type, across open-vocabulary generation and full-vocabulary retrieval. As a first demonstration, a low-rank fine-tune of a 300M on-device embedder improves cross-lingual retrieval and beats a 3,072-dimensional hosted embedder on development exact recall@200 (0.659 vs 0.623). The language panel shows the gain is not uniform, and held-out-test and end-to-end confirmation remain future work.

翻译：自动主题编目为书目记录分配受控词汇标目，但LCSH缺乏标准公开基准。我们提出LCSHBench：包含来自哈佛、哥伦比亚和普林斯顿开放许可目录的15种语言22,346册图书。仅当至少两个独立编目机构分配了LCSH时记录才被纳入；我们发布每个目录的出处信息以及联合和一致答案视图。对465,187部由三所图书馆联合编目作品的语词一致性研究表明，该设计的重要性：图书馆通常就底层主题达成一致（93.3%共享概念级标目），但确切表达常存差异（仅39.4%具有完全相同的标目集）。因此，LCSHBench同时评估精确匹配和概念匹配，通过按语言和标目类型细分的集合与排序指标，涵盖开放词汇生成和全词汇检索。作为首次演示，对3亿参数设备端嵌入器的低秩微调提升了跨语言检索性能，并在开发集精确召回率@200上超越3,072维托管嵌入器（0.659 vs 0.623）。语言面板显示该提升并不均匀，留出测试集验证和端到端确认仍有待未来工作。