研究生成推荐如何突破冷启动，发现现有模型难处理全新语义原子。
Can Generative Recommendation Reach Cold Items? A Temporal Perspective on Semantic-ID Generation
- 基于时间视角分析语义ID生成，区分已见与未见目标
- 模型能偶尔回应已有语义支持的新物品，但难以处理全新语义单元
- 揭示语义生成是分层聚合，非完全开放组合，适合改进推荐系统设计
基于语义ID的生成式推荐将物品表示为共享语义标记序列，实现标记重组超越孤立物品ID。然而，封闭世界重组并不必然带来时间开放的冷启动诱导，即新物品以未见过的原子标记或弱支持的语义路径进入目录。本文在绝对时间协议下重新审视语义ID推荐，分离已见与未见目标，从标记层面诊断冷物品可及性。通过已见/未见命中分析、冷度分类和虚拟前缀探测，发现当前语义ID模型偶尔可响应由观测标记和前缀支持的新物品，但在面对未见原子标记和无支持的语义路径时表现不佳。我们进一步解释此边界：语义ID生成相当于层级语义分桶——早期标记选择粗粒度语义区域，后期标记细化特定路径。结果表明语义生成具有组合性但不完全开放，提示未来方向包括更独立的语义空间、基于评分的接口以及动态文本上下文。
原文摘要 · Abstract (English)
Semantic-ID-based generative recommendation represents items as sequences of shared semantic tokens, enabling token recombination beyond isolated item IDs. However, closed-world recombination does not necessarily imply temporal open-token cold-start induction, where new items enter the item catalog with unseen atomic tokens or weakly supported SID paths. In this work, we revisit SID-based generative recommendation under an absolute-time temporal protocol that separates seen and unseen targets and diagnoses the cold item reachability at the token level. Through seen/unseen-hit analysis, coldness taxonomy, and oracle-prefix probing, we show that current SID-based models can occasionally reach future items supported by observed tokens and prefixes, but struggle with unseen atomic tokens and unsupported SID paths. We further explain this boundary by interpreting SID generation as hierarchical semantic bucketing: early tokens select coarse semantic regions, while later tokens refine item-specific paths. These findings show that SID generation is compositional but not fully open-ended, and suggest future directions in more independent SID spaces, scoring-based interfaces, and dynamic textual context.
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