configuration-driven framework 1feature engineering 1generative retrieval 1online inference 1prompt generation 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.IR2026
TSGR: Taobao Search Generative Retrieval
Tianyu Zhan, Gui Ling, Tong Xiong +9
Generative retrieval (GR) has demonstrated strong promise for industrial e-commerce search by training a single autoregressive model to directly generate the Semantic IDs (SIDs) of…
cs.IR2026
Prompt Generation Technical Report
Dan Ou, Gui Ling, Hao Wan +25
The paper introduces Prompt Generation (PG), a configuration‑driven framework that separates feature processing from model architecture for generative retrieval systems, enabling f…
cs.CL2026
UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure
Taoran Fang, Yan Deng, Chunping Wang +3
With the rapid growth of digital data, real-world applications increasingly involve hierarchical information that combines static attributes with dynamic records. Modeling such het…