PrefixMem encoder for Semantic IDs improves deepest-level accuracy by up to 46% relative and full-SID retrieval recall by up to 22% relative on Pinterest data across LLM families.
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MVIGER integrates complementary knowledge from diverse prompts and indices in generative recommenders via a variational model with learnable prior over latent sources, showing superior performance on three datasets.
VirtualMLE deploys an LLM agent with execution-reflection-memory to tune sequential recommenders, reaching competitive quality on Amazon benchmarks with fewer trials and transferring heuristics across datasets.
citing papers explorer
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LLMs Need Encoders for Semantic IDs Too
PrefixMem encoder for Semantic IDs improves deepest-level accuracy by up to 46% relative and full-SID retrieval recall by up to 22% relative on Pinterest data across LLM families.
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MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender
MVIGER integrates complementary knowledge from diverse prompts and indices in generative recommenders via a variational model with learnable prior over latent sources, showing superior performance on three datasets.
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VirtualMLE: A Virtual ML Engineer that Optimizes Sequential Recommenders
VirtualMLE deploys an LLM agent with execution-reflection-memory to tune sequential recommenders, reaching competitive quality on Amazon benchmarks with fewer trials and transferring heuristics across datasets.