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cs.IR2026
Computed, not Memorized: Bit-Factorized Identifiers for Efficient Generative Retrieval
I-Fan Lin, Zhen Zhang, Faegheh Hasibi +1
Generative retrieval is known for its efficient end-to-end indexing and retrieval. In particular, numeric Document Identifiers (DocIDs) are generally more efficient because they ar…
cs.IR2025
Exploring Training and Inference Scaling Laws in Generative Retrieval
Hongru Cai, Yongqi Li, Ruifeng Yuan +4
Generative retrieval reformulates retrieval as an autoregressive generation task, where large language models (LLMs) generate target documents directly from a query. As a novel par…
cs.IR2025
Unsupervised Query Routing for Retrieval Augmented Generation
Feiteng Mu, Liwen Zhang, Yong Jiang +4
Query routing for retrieval-augmented generation aims to assign an input query to the most suitable search engine. Existing works rely heavily on supervised datasets that require e…