A Systematic Study of Semantic ID Spaces for Generative Information Retrieval
Generative Information Retrieval (GIR) has emerged as a transformative paradigm, shifting document retrieval from a traditional"retrieve-and-rank"workflow to sequence-to-sequence generation, where a model directly predicts document identifiers (DocIDs). While the semantic design of these DocIDs is known to be critical...