5 papers · 1 filter
Personalized Task Dependency Graphs for Mitigating Signal Erosion in Multi-Task Recommendation
Fuyuan Liu, Tiandeng Wu, Yaqun Fang +8
Optimizing multiple conversion objectives is a core challenge in industrial recommendation, often limited by signal erosion in rigid architectures. Existing Multi-Task Learning (MT…
Inventory-Grounded Policy-Level Optimization for Training-Free AI Search
Wei Zhou, Tiandeng Wu, Jiandong Ding +2
Early in deployment, an AI search system typically operates over a frequently updated product catalog, so the available items and their properties cannot be treated as stable knowl…
SIDScope: A Diagnostic Resource for Semantic-ID Interfaces in Generative Recommendation
Jiandong Ding, Huijie Qin, Tiandeng Wu +1
Semantic ID tokenizers assign code sequences to catalog items, which generative recommenders predict and resolve back to items. Reusing a released mapping requires checking its cod…
Beyond the Grid: Layout-Informed Multi-Vector Retrieval with Parsed Visual Document Representations
Yibo Yan, Mingdong Ou, Yi Cao +6
Harnessing the full potential of visually-rich documents requires retrieval systems that understand not just text, but intricate layouts, a core challenge in Visual Document Retrie…
Beyond the Flat Sequence: Hierarchical and Preference-Aware Generative Recommendations
Zerui Chen, Heng Chang, Tianying Liu +5
Generative Recommenders (GRs), exemplified by the Hierarchical Sequential Transduction Unit (HSTU), have emerged as a powerful paradigm for modeling long user interaction sequences…