SIDInspector provides a standardized adapter contract and mapping-level probes for Semantic-ID tokenizers, with empirical contrasts showing high aliasing in GRID-style exports and superior prefix alignment from deterministic controls on Musical items.
InProceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’25)
3 Pith papers cite this work. Polarity classification is still indexing.
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DREAM proposes intent-aware tokenization, frozen-model evaluation, and dynamic beams to refine early SID assignments and improve cold-start performance in generative recommenders on Amazon benchmarks.
GLAN replaces CQL bootstrapping with Decision Transformer sequence modeling for PLPM, using global inter-day (L-RTG) and local session (HRM) modules to achieve +0.158% DAU and +0.108% LT gains in Kuaishou online tests.
citing papers explorer
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SIDInspector: A Mapping-First Diagnostic Resource for Semantic-ID Tokenizers
SIDInspector provides a standardized adapter contract and mapping-level probes for Semantic-ID tokenizers, with empirical contrasts showing high aliasing in GRID-style exports and superior prefix alignment from deterministic controls on Musical items.
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DREAM: Dynamic Refinement of Early Assignment Mappings
DREAM proposes intent-aware tokenization, frozen-model evaluation, and dynamic beams to refine early SID assignments and improve cold-start performance in generative recommenders on Amazon benchmarks.
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From Bootstrapping to Sequence Modeling: A Unified Generative Framework for Personalized Landing-Page Modeling
GLAN replaces CQL bootstrapping with Decision Transformer sequence modeling for PLPM, using global inter-day (L-RTG) and local session (HRM) modules to achieve +0.158% DAU and +0.108% LT gains in Kuaishou online tests.