发表机构
Huawei Technologies Co., Ltd.（华为技术有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
SIDScope是生成式推荐语义-ID接口的诊断资源，通过多维度分析揭示接口健康度为多信号，发现前缀对齐与检索机制相关、存在目标路径未唯一检索的差距及模型复用需单独交接检查等结论。
AI 中文摘要
语义-ID映射是项目分词器与生成式推荐器之间可复用的接口，但已发布的映射很少说明它们是否连贯、暴露何种结构、生成路径如何解析，或刷新后必须重新验证的内容。SIDScope是用于这些决策的源追踪诊断资源，它对项目到代码的构件进行标准化，验证来源与关联，分析映射结构，比较配对修订版本，并考虑生成轨迹中路径到项目的结果。针对来自七个系列的九个源追踪分词器导出数据（涵盖Amazon和Yelp数据，其中八条可执行路径、一条可审计快照），SIDScope揭示接口健康度是多信号而非标量。其核心发现是机制条件性的：当检索使用SID前缀时，前缀对齐与保留的候选曝光高度相关，而当评分与前缀无关时，这种相关性会减弱。训练后的轨迹核算揭示了第二个隐藏差距：有效目标路径在未唯一检索到目标项目的情况下仍能保留，占比为1.2至3.0个百分点。一个刷新案例确立了第三个结论：仅修复映射本身无法恢复继承的生成器；模型复用需要单独的交接检查。该工具包提供冻结的证据摘要、一致性报告、轨迹标签、表格构建器及仅CPU的验证器，支持模型复用前关于构件就绪性、接口风险及重新验证的决策。
英文摘要
Semantic-ID mappings are reusable interfaces between item tokenizers and generative recommenders, yet released mappings rarely state whether they are coherent, what structure they expose, how generated paths resolve, or what must be revalidated after a refresh. SIDScope is a source-traced diagnostic resource for these decisions. It normalizes item-to-code artifacts, verifies provenance and joins, profiles mapping structure, compares paired revisions, and accounts for path-to-item outcomes in generated traces. Across nine source-traced tokenizer exports from seven families on Amazon and Yelp data - eight executable routes plus one auditable snapshot - SIDScope reveals that interface health is multi-signal rather than scalar. Its central finding is mechanism-conditional: prefix alignment strongly tracks held-out candidate exposure when retrieval consumes SID prefixes, then weakens as scoring becomes prefix-independent. Trained trace accounting exposes a second hidden gap: a valid target path can survive without uniquely retrieving the target item by 1.2-3.0 percentage points. A refresh case establishes a third: repairing the mapping does not by itself restore an inherited generator; model reuse requires a separate handoff check. The package provides frozen evidence summaries, conformance reports, trace labels, table builders, and CPU-only verifiers. It supports decisions about artifact readiness, interface risks, and revalidation before model reuse.
CommentsResource: https://github.com/jdding/sidscope
